text:
|Publication number
|Publication type
|Application number
|Publication date
|Mar 22, 2005
|Filing date
|Dec 15, 1999
|Priority date
|Dec 15, 1999
|Fee status
|Also published as
|Publication number
|Pete A. Boyer, David F. Freeman, Pablo A. Vicharelli, Philip G. Rossoni
|Original Assignee
|Verizon Laboratories Inc.
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (22), Non-Patent Citations (14), Referenced by (34), Classifications (23), Legal Events (5)
|External Links: USPTO, USPTO Assignment, Espacenet
The present application is co-pending with and related to U.S. patent application Ser. No. 09/461,990, filed Dec. 15, 1999, currently pending.
1. Field of the Invention
This application generally relates to cellular networks, and more particularly to techniques for planning and tuning a cellular network.
2. Description of Related Art
Cellular networks may be used in a variety of applications. For example, cellular networks are used in cellular telephone communications. Cellular networks include, for example, digital and analog cellular networks that operate in accordance with one or more protocols or standards, such as Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), IS-95, or Advanced Mobile Phone Service (AMPS). Generally, cellular networks are configured prior to operation in accordance with certain quality standards, conditions and constraints. Examples of the foregoing include., minimizing interference to base stations or sectors. Additionally, the FCC defines frequency ranges that may be assigned and used for transmissions in cellular networks. A base station may be defined as including one or more sectors. Each sector may be viewed as a point from which, or through which, transmissions within the cellular network may be made.
One problem with cellular networks is how to configure the cellular network having multiple sectors, and assigning or associating channels or frequencies with each of these sectors. In other words, part of the configuration of the cellular network is defining at what frequencies different sectors may operate. Sectors may be assigned channels related to information transmissions, such as cellular telephone calls, as well as particular ones for communications related to transmission set up. This association of one of more of one or more channels or frequencies with each of the sectors is determined prior to operation of the cellular network. Additionally, only certain ranges may be used as defined, for example, in accordance with FCC regulations. The FCC defines bands of frequencies that include a limited number of channels which are divided among the various sectors within the cellular network for transmissions.
In a heavily loaded cellular system, the limited number of frequencies or channels may be a problem. One solution is to reuse certain frequencies and assign the same frequency or channel to more than one sector. However, reusing channels when configuring the cellular network may cause the task of system configuration to become increasingly complex due to the constraints that are considered in system configuration. For example, two sectors which are adjacent may generally not be assigned the same frequency due to the extensive interference and operational problems that may be introduced.
Consequently, part of the process of configuring a cellular network may include determining what frequencies may be reassigned to which sectors while trying to minimize the interference which may be introduced by having multiple sectors or base-stations operating at the same frequency. Determining which frequencies may be reassigned or associated with multiple sectors is considered in accordance with quality of service standards, for example, such that a signal is transmitted at a certain power with minimal interference.
Thus, there is required a technique for configuring a cellular network in accordance with input configurations constraints as well as quality of service constraints to achieve a high degree of quality signals by minimizing the interference in a specific set of output configuration data.
In accordance with principles of the invention, disclosed is a method and computer program product for determining channel assignments for a cellular network. Requested channel assignments are determined. A sector is selected in accordance with sector selection criteria. A channel is selected in accordance with frequency selection criteria. It is determined if an additional requested channel assignments may be filled in accordance with predetermined criteria. A value included in one of the sector or frequency selection criteria is adjusted if all requested channel assignments have not been filled.
In accordance with yet another aspect of the invention is a method and computer program product for determining a channel assignment for a cellular network. A sector is selected in accordance with sector selection criteria. A minimum channel threshold is determined and associated with each sector identifying a minimum quantity of acceptable channel assignments.
In accordance with yet another aspect of the invention is a method and computer program product for determining color codes. A channel is selected. Sectors associated with the channel are identified. A channel assignment technique is used to assign color codes to sectors using the channel.
Features and advantages of the present invention will become more apparent from the following detailed description of exemplary embodiment thereof taken in conjunction with the accompanying drawings in which:
Referring now to
It should be noted that the cellular device may include, for example, a cellular telephone or other device which transmits signals in a cellular network. Each of the sectors A through D have stations that operate within the cellular network 174 for transmissions between the cellular device and the sectors, such as making telephone calls from a cellular telephone.
It should be noted that other embodiments of a system 170 may include more base stations and sectors, as well as include multiple cellular devices in operation. The system of
Referring now to
Referring now to
It should be noted that the embodiment of the system 170 in
As known to those skilled in the art, the FCC defines certain channels or frequencies that may be assigned or used in transmissions within a cellular network. There is a relatively small number of channels or frequencies that may be assigned. Thus, part of the problem of configuring the system 170 includes how to divide the different channels that are used within the cellular network. Various tools, such as GRANET ("Graphical Radio Network Engineer Tool") as used by GTE Corporation may be used to configure and tune cellular systems,such as the system 170 of
What will be described in paragraphs that follow are techniques for tuning and configuring this system in accordance with certain input data and criteria or constraints. For example, the constraints may relate to quality of service, such as requiring information transmissions to be of a certain power level. Various input configuration information, such as the geographic constraints, is also considered when doing channel assignments and information transmissions. It should be noted that other constraints and input may be considered as known to those skilled in the art, for example population, in a particular area. Population may be an indicator of the number of channel assignments required for a particular sector.
Referring now to
Referring now to
It should also be noted that, similar to the variety of network connections and computer systems that may be used in a particular embodiment, a variety of data storage devices 20 may be included in the particular embodiment as known to those skilled in the art.
Referring now to
Generally speaking, the input configuration data includes that input information which may be relevant to a particular embodiment and should be considered when determining the configuration of the cellular network. Requested channel assignments 30 is basically a request of the number of frequencies or channels to be associated with each particular base station or sector. Generally, channel assignments may be determined for example by estimation using the population information or it may be alternatively be based on past use. It should be noted that the types of information included in each of the foregoing may vary with embodiment in accordance with each particular application and implementation.
The channel separation matrix 24 is a representation of the minimum channel separation between any two base stations or sectors. In this particular embodiment in the channel separation matrix 24, an N×N dimensioned matrix may be used. In this embodiment there are N base stations or sectors. Each entry in the matrix represents the minimum channel separations between the two sectors as indicated by, respectively, a particular row and column pair. Typical entries in the matrix are one of a 0, 1 or a 2. A channel separation of 0 indicates there is no separation between frequencies or channels that may be assigned to particular base stations. A 1 indicates that there must be at least a plus or a minus of 1 channel difference in assignments between two particular sectors. Similarly, a 2 indicates that no adjacent sectors may be assigned the same frequency or channel.
Generally, the term "neighbor" is used to describe how one sector and its base stations relates to another sector and its base stations. It is generally known in the art that if a call may be "handed off" to a sector from another sector, those two sectors may qualify as neighbors. With regard to the channel separation matrix, a neighbor may be reflected in the channel separation matrix by a minimum separation of 2 indicated between a pair of sectors or base stations.
Referring now to
Generally, traffic channels 32 are those channels or frequencies assigned or associated to a particular sector for transmissions when in operation. These channels may generally be described as operation transmission frequencies, for example, those frequencies that may be used in information transmissions between a cellular device and a sector during transmission of a cellular telephone call. Set-up channels 34 are those channels each associated with a sector at which the sector may operate to set-up an initial communication with a cellular device. For example, referring to
The SATs are generally an assignment of one of three particular tones associated with each frequency or channel assigned, and assist with the identification of a particular base station or sector. The DCCs relate to the set-up channels between a base station and a handset or cellular device. The DCC is two bits of information assigned to each set-up channel and placed into in the transmission stream.
Referring now to
The best server region indicates for a particular area what base station or sector is best suited to handle or serve calls from that particular region. The best server region module 44 is used to determine the best sector to serve or handle an incoming call in accordance with signal strength. The pairwise C/I module 42 performs determinations in accordance with hypothetical or simulated conditions, e.g., a "what if" scenario, that are considered when assigning frequencies or channels. The pairwise C/I module 42 determines the strength of a signal transmitted at a frequency if sectors A and B are both assigned the same frequency and if no other frequencies are assigned. Generally, the pairwise C/I considers what the strength of a signal from a first sector operating in a first frequency or channel in conjunction with the interference generated by a second sector also operating at that same frequency or channel. Generally, the pairwise C/I considers the hypothetical situation in this assignment as a condition in determining whether to perform a certain frequency assignment as an input to the frequency assignment module 50. Determining frequency assignments from the pairwise C/I module 42 is used by looking at each point in a best server region and considering the strength of the desired or carrier signal as well as the strength of the interference. This will be described in more detail in paragraphs that follow. It should generally be noted that the pairwise C/I requirements produced by the pairwise C/I module 42 in considering frequency assignments relate to quality of service. In other words, the pairwise C/I module 42 produces hypothetically input in accordance with a particular channel assignment configuration. This may generally be viewed as an estimation of interference as related to a particular frequency assignment. This is considered as an input to the frequency assignment module 50 in conjunction with the quality of service input 54 which dictates, for example, quality of service required for a particular system configuration. The pairwise C/I module 42 considers the interference components for hypothetical pairs of frequency assignments.
Output produced by the best server module 44 is also input to the probable neighbors module 46. Generally, the probable neighbors module 46 may be used to produce input to determine what two sectors are, or may be considered, "neighbors". This is used as input in producing the channel separation matrix by the channel separation module 48. Additionally, switch neighbor data 52 may also serve as an input in producing the channel separation matrix by module 48. Generally, switch neighbor data is a snapshot of the channel separation as known to the existing switching systems as may be included in an embodiment of the system 170 of FIG. 1. It should be noted that both actual switch neighbor data 52 as well as output from the probable neighbors module 46 may serve as input to the module 48 in producing the channel separation matrix. The switch neighbor data 52 represents the actual description of what sectors are considered neighbors by the switches currently in operation. However, it is often the case that an embodiment may want to add sectors or base stations. Thus, performing using the actual switch neighbor data 52 does not suffice to accurately describe the neighbor relationship between all sectors in this instance. For example, where an additional base station or sector is to be added, input for this future configuration may come from the probable neighbors module 46 and serve as input for module 48 to produce the channel separation matrix as previously described.
In this embodiment, the channel separation matrix may include information as will be described below. Generally, two sectors have a minimum separation of 2 if a call can be "passed off" between the two sectors, qualifying the two sectors as neighbors. If two sectors have the same neighbor, for example sectors C and D may have a common neighbor A, then C and D have a separation of 1 as may be indicated in the channel separation matrix. Otherwise, a zero (0) is indicated as an entry in the channel separation matrix by the switch neighbor data 52. A channel separation matrix may be used as an input to the frequency assignment module 50. Generally, the frequency assignment module 50 takes into account those sectors which are neighbors as well as hypothetical interference in accordance with a particular frequency assignment. The frequency assignment module 50 uses this information to produce a configuration of channel assignments associated with each particular sector, for example, in producing the traffic channel assignment set 32.
Additionally, threshold tests may be made in accordance with QOS input 54 such that a particular configuration operates in accordance with predetermined QOS requirements 54. The frequency assignment module 50 outputs configuration data, for example, such as traffic channel configuration information 32 of
Referring now to
It should also be noted that indication of the same best server may be scattered throughout the best server map. In other words, there are areas or portions of the best server map which may not be contiguous in representing those portions for which A, B C, or D are the best servers. For example, note that cell number 5 contains an A and cell numbers 3 and 4 contains B's. Thus, those geographic areas associated with cell number 5 indicate A is the best server. However, this is separate from, and not contiguous with, that portion of the map defined by 110 which includes a block or group of cells shown in the left portion of the map 100. In particular, the area 110 represents a contiguous portion of the best server map for which A has been designated the best server. This portion 110 is disjoint and separate from other single cells, such as cell number 5 and cell number 27 that also indicate A as the best server.
Generally, such disjoint representations may occur, for example, due to various geographic details such water, land or particular urban areas. For certain geographic locations such as those with certain elevation or mountainous terrains, there may be disjoint best server groupings or gaps between those geographic areas associated with the same best server.
Referring to
Referring to
Referring to
At step 142, the contiguous regions of the best servers are determined. As previously described in conjunction with
At step 144, the total and common boundaries of the contiguous regions are determined. In other words, the total boundary for a particular contiguous region such as 110 is determined. This may be indicated, for example, by the darkened line surrounding the portion 110 of map 100, indicating the total boundary for this contiguous region. Also determined at step 144 is that portion of the boundary which is common between two contiguous regions in which each contiguous indicates a different server. In this example, line 111 indicates a common boundary for example between the contiguous area 110 and another contiguous area which has not been defined and determined in the best server map 100.
At step 146, probable neighbors are determined in accordance with total and common boundaries as well as a predetermined boundary threshold value. What will now be described in paragraphs that follow are more detailed descriptions for the steps of the flow chart 140 of FIG. 11. Referring now to
Referring now to
At step 162, it is determined for each pair of sectors A and B having a common boundary, is the common boundary or percentage of the common boundary to the total boundary greater than some threshold for both the total boundaries of A and B. If it is determined at step 162 that such a condition is true, control proceeds to step 166 where it is determined that sectors A and B are probable neighbors due to the large percentage of common boundaries shared between the two sectors indicated by the pair A and B. If it is determined at step 162 that the portion of common boundary between A and B is less than or equal to the boundary threshold for both the total boundaries of A and B, control proceeds to step 164 where it is determined that sectors A and B are not probable neighbors.
Included below is a pseudo code representation of an implementation of the probable neighbors technique generally described in the flowcharts of
Included below is the PROBABLE_NEIGHBORS pseudo code.
* Set small gap threshold
boundary_width = 200m /* default value for gap threshold */
width = max( (floor(boundary_width/unit_x) + 1/2), 1)
/* convert to pixels */
* Set ″common boundary threshold
boundary_fraction = .05 /* define default threshold for ″common
boundary″ */
* Initialize
for place = map_start to map_end /* scan by pixels */
if not_a_best_server (place) or over_water (place)
pixel_flag[place] = IGNORE
pixel_flag[place] = UNPROCESSED
* Find Largest contiguous region for each server
for place = map_start to map_end
if pixel_flag[place] = UNPROCESSED
best = best_server[place]
biggest_size = 0
for new_place = place to map_end
if(pixel_flag[new_place] = UNPROCESSED and
best_server[new_place] = best)
* Find all pixels contiguous with current one
size_fragment = find_fragment(new_place,best,width,
if biggest_size < size_fragment
biggest_size = size_fragment
biggest_place = new_place
* Mark smaller fragments as seen/processed in largest contiguous region
for new_place = place to map_end
if pixel_flag[new_place] = PROCESSED
if new_place = biggest_place
flag = best /* mark biggest fragment by best server */
flag = IGNORE /*ignore other fragments */
mark_fragment (new_place,best,width,pixel_flag,flag)
/* finding size of border
for sector_a = first_sector to last_sector
* Initialize
for sector_b = first_sector to last_sector
n_pixels[sector_a, sector_b] = 0
neighbor_matrix[sector_a, sector_b] = 0
for place = map_start to map_end
if pixel_flag[place] NOT_EQUAL IGNORE
sector_a = pixel_flag[place]
* conversion between pixels and rows and columns
row = find_row(place)
col = find_colplace)
* look to the east for counting pixels in the border
for other_col = col+1 to min (col+width_1, col_end)
other_place = find_pixel(row,other_col)
if pixel_flag[other_place] NOT_EQUAL IGNORE
sector_b = pixel_flag[other_place]
* boundary is found
if sector_a NOT_EQUAL sector_b
n_pixels[sector_a, sector_b]++
* look to the north for counting pixels in the border
for other_row = row+1 to min(row+width+1, row_end)
other_place = find_pixel(other_row,col)
if pixel_flag[other_place] NOT_EQUAL IGNORE
sector_b = pixel_flag[other_place]
* boundary is found
*/ if sector_a NOT_EQUAL sector_b
n_pixels[sector_a, sector_b] ++
* Symmetrize counts and sums over border — if a-b is border, so is b-a
for sector_a = first_sector to last_sector
for sector_b = first_sector to last_sector
if sector_a < sector_b
n_pixels[sector_a, sector_b] = n_pixels[sector_a, sector_b] +
n_pixels[sector_b, sector_a
n_pixels[sector_b, sector_a] = n_pixels[sector_a sector_b]
if sector_a NOT_EQUAL sector_b
n_pixels[sector_a, sector_a] = n_pixels[sector_a, sector_a] +
n_pixels[sector_a, sector_b]
* not neighbors of the border doesn't meet threshold requirements
for sector_a = first_sector to last_sector
for sector_b = sector_a+1 to last_sector
* this implementation is conservative - total boundary threshold
* is the smallest total boundary
* length of base station/sector pair
boundary_length_threshold = max(boundary_fraction *
min(n_pixels[sector_a, sector_a],
n_pixels[sector_b, sector_b])
if n_pixels[sector_a, sector_b] >= boundary_length_threshold
neighbor_matrix[sector_a, sector_b] = 1
/* A and B are neighbors == 1
neighbor_matrix[sector_b, sector_a] = 1 /* they are neighbors == 1
The foregoing pseudo code generally identifies a connected set of pixels for each best server. Sectors with neighboring sets of pixels are determined to be probable neighbors. In this embodiment, best server areas are notably fragmented at the pixel level. In particular, as previously discussed in conjunction with a best server map, a phenomenon that may be termed speckling may occur in which isolated pixels far from a sector have an indication of the same best server. This is in fact an artifact, for example, of small fluctuations in path loss estimation, and such isolated pixels may be excluded from probable neighbors calculation. In one embodiment, best server areas may be composed of a number of disconnected fragments each of which appears to the eye as a connected whole. For computation of contiguous regions, this may be formalized or taken into consideration. A fragment may be defined as a maximal set of piecewise connected pixels with the same best server. The pixel is in a fragment if and only if it is within the boundary width of at least one other pixel in the fragment. These fragments may be found by the find fragment function which will be described in more detail below. The point of the boundary in the probable neighbors in the probable neighbors pseudo code is to unify fragments which may be separated by insignificant gaps. As indicated in the pseudo code, the current default value for such a gap is 200 meters. Other values may also be used.
In order to consider in an embodiment the fact of widely scattered fragments which may introduce spurious probable neighbors, only the largest fragment for each best server is considered in the foregoing pseudo code. This is done by means of the MARK_FRAGMENT function which will also be described below.
Once a single fragment is identified for each best server, the number of neighboring pixels with all other best server fragments is counted. A neighboring pixel is one within the boundary along the east-west or north-south line. The point of the boundary in this particular example is to remove the effect of insignificant gaps. Best server regions with enough neighboring pixels are deemed probable neighbors. This count must be at least as large as a specified fraction of the largest possible count in accordance with the predefined threshold. In the foregoing description the default value or threshold is indicated at 5%.
Indicated below is the pseudo code for the FIND_FRAGMENT routine which is used by the probable neighbors pseudo code.
FIND_FRAGMENT(place, best, width, pixel_flag)
row_start = find_row(place)
/* push starting place onto the stack
size = 1
while stack <> NULL
new_place = pop()
row = find_row(new_place)
col - find_col(new_place)
/* look within width of new_place for connected pixels,
but not before starting row
for other_row = max(row-width row_start)
to min(row+width, row_end)
for other_col = max(col-width, min_col) to min (col+width,
other_place = find_pixel(other_row, other_col)
if pixel_flag[other_place] = UNPROCESSED
if best_server[other_place] = best
pixel_flag[other_place] = PROCESSED
The method or technique for finding fragments in best server areas is used in the probable neighbors pseudo code description and may be referred to as a flooding technique. For any pixel in a fragment, all adjoining pixels with the same best server are also made part of the same fragment. In this particular example, adjoining is defined as above within the boundary width. As each such pixel is found it is marked as being processed and pushed onto the stack. When a pixel is popped from the stack, adjoining unprocessed pixels are sought for it. The process stops when the stack is empty, indicating no more unprocessed neighboring pixels can be found. Additionally, FIND_FRAGMENT counts the number of pixels within the fragment so that the largest fragment may be subsequently identified as indicated in the probable neighbor pseudo code.
Included below is a pseudo code representation of the MARK_FRAGMENT routine which may be used in conjunction with the PROBABLE_NEIGHBORS and FIND_FRAGMENT pseudo code.
MARK_FRAGMENT(place,best,width,pixel_flag, flag)
row_start = find_row(place)
/* push starting place onto stack
push (place)
while stack <> NULL
new_place = pop()
row = find_row(new_place)
col = find_col(new_place)
/* look within the width of new_place for connected pixels but not before
starting row
for other_row = max(row-width,row_start) to min(row+width,
for other_col = max(col-width, min_col) to min(col+width,
other_place = find_pixel(other_row, other_col)
if pixel_flag[other_place] = PROCESSED
if best_server[other_place] = best
pixel_flag[other_place] = flag
It should be noted that a flooding technique as previously mentioned with FIND_FRAGMENT is also used to mark fragments in the MARK_FRAGMENT pseudo code pixel by pixel after the largest fragment is identified. That fragment is marked by the sector identifier for the best server. All other fragments are subsequently ignored. In the foregoing description of PROBABLE_NEIGHBORS, it should be noted that a threshold is established as a common boundary percentage. Additionally, a gap threshold is determined as indicated by the parameter with, both of these threshold conditions may be modified in accordance with each particular implementation or embodiment. Additionally, the foregoing implementation only considers the largest contiguous region for each server when determining neighboring sectors. It should also be noted that the foregoing pseudo code implementation of the general flow chart described in conjunction with
What will now be described are calculations involving the C/I statistics that may be computed, for example, by the pairwise C/I module 42 of FIG. 7. These calculations may be used, for example, in performing frequency assignments by the frequency assignment module 50.
The technique that will be described may be used in improving the accuracy of frequency assignments and channel assignments. Pairwise C/I values may be especially useful as a "figure of merit" for evaluating various frequency assignment scenarios, as may be performed in configuring the network 170. This figure of merit may be used to assess channel quality, and optimize the assignment for total interference requirements in accordance with quality service requirements, for example, as may be input to the channel assignment module.
As previously described, the pairwise C/I may be measured as the ratio of carrier power to interference power between two sectors using the same channel, or in other words, having the same channel assignment. Two pairwise C/I values exist for every pair of sectors A and B, where A is the carrier and B is the interferer, as well as where B is the carrier and A is the interferer. As will be described in paragraphs that follow, a data structure, such as a matrix, may be used to store C/I values and other associated data during the channel assignment process.
It should be noted that the interference as expressed in the C/I values may depend on such factors, for example, as coverage areas from the traffic distribution, and received power distribution. As will be described, it is assumed that measurements of power may be accurately modeled as having a lognormal distribution when the short distance fluctuations are averaged out. The power, as may expressed in decibels, is normally distributed with some predicted mean and standard deviation that are verified by measurements. Consequently, the C/I in decibels is the difference between two normal random variables with given means and standard deviations. Hence, the distribution of the C/I is normal. The mean is the difference between the mean carrier power and the mean interfering power. The standard deviation may be found by knowing the correlation co-efficient between the carrier power and the interfering power.
The statistical correlation that exists between the carrier power and the interfering power depends on the relative angle of arrival to the geographic areas being considered. Measurements may indicate that the correlation co-efficient, as will also be described, may be empirically estimated as a function of the magnitude of the angle between the paths to the point of interest in a coverage area. In this instance, the correlation co-efficient is a maximum of 0.9 at an angle of 0, and drops off linearly to 0 at a 180 degrees.
Once a C/I distribution is found at each point, the distribution is weighted proportionally to the estimated traffic for the area in the neighborhood of the point, and averaged over all the points covered by the carrier sectors coverage area. An overall distribution of C/I is thus formed. The pairwise C/I estimate may be defined as a percentile from this distribution, for example, the 10th percentile may be used.
Referring now to
where the sum Σ in the above formula is for all k such that channel i is assigned to sector k. It should be noted that C/Iji, the left hand side of the foregoing equation, is the total interference at sector on channel I. Additionally, C/Ikj pairwise is the pairwise interference at sector j due to sector k.
Similarly, the adjacent channel C/I may be computed as:
where the sum Σ in the above formula is for all k such that channel i−1 or channel i+1 is assigned to sector k. Generally, as will be described in paragraphs that follow, these two types of total C/I calculations involving co-channel and adjacent channel C/I may be used as C/I constraints that may be considered when performing frequency selection, for example, using channel assignments techniques.
At step 206, frequency or channel assignments are performed in accordance with C/I calculations as performed in step 204. In particular, as will be described in conjunction with other Figures, the C/I calculations may serve as constraints in a particular embodiment of the system and may affect whether a particular channel or frequency is assigned to a particular sector or sectors. At step 208, a C/I map may be generated. Generally, the C/I map is produced as an analysis tool for assessing the quality of channel assignments. A C/I map calculation is a representation where, for each pixel representing a certain geographic area, the "worst" assignment made for a particular channel is examined. For example, in one embodiment the "worst" channel assignment may be determined in accordance with the weakest signal strength. This may assist in presenting a graphical representation of how well channels were assigned to particular sectors in accordance with certain criteria, such as strength for resulting signals, for particular channel assignments.
Referring now to
What will now be described is determining the pairwise C/I calculations as may be used in computing the total C/I for co-channel and adjacent channel constraints in determining whether to perform channel assignments.
Referring now to
Referring now to
As previously described in conjunction with
A measure of goodness of the assignment in terms of co-channel C/I is found by assuming all channels are in use and that the interference from each sector using the same channel is that given by a pairwise C/I estimate, as previously discussed in conjunction with the co-channel and adjacent channel C/I calculations.
Included below is a pseudo code description of the pairwise C/I calculations as may be included in an embodiment.
form_pairwise_CtoI (pairwise_CtoI, percent_worse)
for interferer = first_subsector to last_subsector
for best = first_subsector to last_subsector
/** initialize cumul_dist */
for grid_point - first_grid_point to last_grid_point
cumul_dist[best, grid_point] = 0
read_path_list(interferer) /** get pixel maps, best server **/
for pixel = first_pixel[interferer] to last_pixel[interferer]
best = best_server(pixel)
if best <> NO_BEST_SERVER
weight = traffic(pixel)
/** compute mean E by computing difference between C and I values
for normal distribution **/
mean = server_power_dB(pixel) -
interferer_power_dB (interferer, pixel)
cor = correlation(best, interferer, pixel)
/* sigma is standard deviation **/
sigma = DEFAULT_SIGMA * SQRT(2(1-cor))
grid_value = GRID_START
for grid_point = first_grid_point to last_grid_point
/** compute probability density **/
cumul_dist[best, grid_point] = cumul_dist[best, grid_point]
+ weight * cumulative(grid_value, mean, sigma)
grid_value = grid_value + GRID_SPACING
for best = first_subsector to last_subsector
threshold = percent_worse * total_traffic(best)
grid_point = first_grid_point
grid_value = GRID_START
/** threshold is the percentile **/
while(cumul_dist[best,grid_point] < threshold and grid_point <=
grid_point ++;
grid_value = grid_value + GRID_SPACING
pairwise_CtoI[interferer, best] = grid_value
With regard to the foregoing pseudo code, a number of assumptions have been made about the available ancillary functions. In particular, the function read_path_loss(sub_sector) makes available the path loss for all the pixels that are sufficiently close to a given subsector together with associated ranges of pixels. The function interfere_power_dB(sub_sector, pixel) uses the path loss previously made available by read_path_loss to compute the received power from a given subsector at the given pixel. The function server_power_DB(pixel) also computes the received power at the given pixel. Here, the transmitting subsector is the best server for that pixel. The corresponding path loss is not made available by a call to read_path_loss. The function traffic (pixel) gives the traffic for a given pixel which is assumed to be allocated to the best server subsector for the pixel. Recall that traffic relates to a weighted use of population information. The function total_traffic (sub_sector) gets the total traffic supported by the given subsector. It is assumed that this is equal to the total of the traffic for all the pixels for which the given subsector is the best server.
It should also be noted that the forgoing pseudo-code forms an unnormalized cumulative distribution function. The percentile threshold is normalized rather than the distribution function simply because in this particular embodiment it requires less computation. However, other embodiments may vary from this by using techniques known to those skilled in the art for each particular implementation. The normalization factor given by the foregoing function total_traffic (best) is not equal to the sum of traffic given by the function traffic (pixel) this is because the pixels within the range of a given interfere need not include all the pixels for a given best server area. It should also be noted that omitted pixels are not explicitly treated in the above pseudo-code. The omitted pixels for example correspond to pixels for which the means C/I should be very large. If they were included in the above pseudo code the shape of the cumulative distribution function may be affected only at the high end. This omission thus effects the percentile only when the C/I is large so that it does little more than indicate that there is effectively no interference from a corresponding subsector.
A note should also be made regarding the correlation. When the propagation path from the desired signal and the interferer are nearly identical, the lognormal fading of the two are highly correlated. Consequently, the standard deviation of the resulting C/I distribution is reduced. The technique for finding the angle between two propagation paths may use the angle to compute the correlation coefficient. In one embodiment, the angle between the two directions of arrival is computed using vector projection. Another embodiment may use the law of cosines which may be more computationally intensive than using vector projection. Subsequently, correlation is now a linear function of the angle when using vector projection, interpolating between a "peak value" at 0 degrees, and zero at 180 degrees. In one embodiment, such as in the GRANET embodiment, the configuration tool may be "hardwired" to use a for peak value of 0.9 for correlation coefficient. Recall, that a correlation coefficient with a peak of 0.9 for a maximum was previously described in conjunction with box 314 of
It should be noted that a pairwise C/I calculation previously described uses the ratio of carrier strength to the strength of an interfering signal for a second sector assuming the second sector is transmitting on the same frequency as the first sector. Techniques have been described which take as input traffic map or LULC information, as well as best server area path loss information, site, sector, and as well as antenna information. The foregoing techniques produce a C/I matrix representing the pairwise C/I calculations for a particular pair of sectors. Also as previously described in the foregoing, the pairwise C/I calculations as may be store for example in the C/I matrix are used in producing total or power sum C/I calculations. The total C/I may be computed for a co-channel assignment and/or adjacent channel assignment representing the ratio of the carrier power from the server on a channel to the power of all interfering signals on that channel or on adjacent channels. Total C/I may be computed for the following sets of channel assignments including, but not limited to, voice channels, signaling channels, voice channels with the same SAT, and signaling channels with the same DCC. Inputs used computing the total C/I calculations in frequency planning are the assigned frequencies per sector in the pairwise C/I calculation.
A C/I map may be generated from completed frequency plans. Generally, as previously described the C/I map represents, given a pixel in a particular best server area, the propagation functionality being used to estimate the received power from the best server and from all possible interferers. The sector with the strongest of these interferers is identified together with corresponding C/I ratio. Recall, that the C/I ratio is the difference in decibels between desired signal and interference.
Two different forms of C/I maps may be formed. For co-channel C/I, the interference comes from any sector that is assigned or any channel assigned to the best server. For adjacent channel C/I interference comes from any sector that is assigned any channel adjacent to a channel assigned to the best server. For the C/I map computations, the inputs include frequency planning or assignments as well as path loss information. Using the foregoing C/I techniques, a C/I map may be output for the strongest interferer in the particular interfere.
It should be noted that the total C/I is meaningful in the context of a particular frequency plan and may be computed for example by summing the previously computed pairwise C/I values directly. Summation may be formed as though there are constant C/I values by summing them.
Referring now to
At step 230, quality of service (QOS) input requirements may be obtained or calculated as needed, such as those related to C/I calculations (i.e, co-channel C/I and adjacent channel C/I). At step 232, a channel and a sector are selected. At step 234 a determination is made with respect to the particular channel and sector at step 232. A determination is made at step 234 as to whether, for each channel assignment, is the total C/I for that channel assignment greater than the QOS requirements. In other words, at step 234 a test is made considering the total C/I requirements, such as co-channel and adjacent channel C/I, to determine whether or not this channel assignment is acceptable by resulting in a total C/I computation above a predetermined QOS requirement, such as signal strength. If a determination is made at step 234 that the total C/I is greater than the quality of input, control passes to step 238 where the channel assignment is made. Otherwise, control passes to step 236 where the channel assignment is not performed. In other words, a determination has been made by proceeding to step 236 not to perform a channel assignment because predetermined QOS input constraints have not been met.
At step 240, a determination is made as to whether channel assignments are complete. If so, control proceeds to step 242 where the channel assignments are complete and the channel or frequency assignment technique stops. Otherwise, if channel assignments are not complete control proceeds to step 232 to the top of the loop where a new channel and sector are chosen.
Referring now to
At step 250, initialization is performed, for example, of any variables used in performing subsequent steps. At step 252, a sector is selected using sector selection criteria (SSC). Generally, SSC sets forth certain rules that may be used to select a particular sector. Various SSCs are described in paragraphs that follow in conjunction with other Figures. At step 234, a channel is selected using frequency selection criteria (FSC). Generally, FSC are rules which assist in selecting a particular frequency to be associated with a sector selected at step 252. At step 256, a test is made as to whether more requests for channel assignments as may be input may be filled. If a determination is made at step 256 that more requests may be filled, control proceeds to step 252 where another sector and channel are selected. If a determination is made at step 256 that more requests cannot be filled, a determination is made at step 260 as to whether all requests that have been made are filled. In other words, at step 260, a test is made to determine whether all the requested channel assignments have been made. If a determination at step 260 is made that all the requests have been filled in accordance with input configuration parameters, control proceeds to step 262 where the method of
It should be noted that the general flow of
The foregoing technique of
As will be described in conjunction with selection criteria, perhaps on a subsequent iteration, a different sector may be chosen as the sector candidate for the next assignment as an alternative, for example, to attempt another assignment to the same sector. The sector selection process may be applied considering the effects of the most recent assignment. For example, the newly assigned frequency may reduce the pool of frequencies available for assignment to some of the sectors and create adjacent and co-channel interference to frequencies in other sectors. Consequently, the taking into account this sector assignment in sector selection criteria may yield a different decision for the next sector.
If there are still unfilled requests at the end of execution of the loop of
Referring now to
Referring to
It should be noted that various criteria, such as SSC I, which takes into account a "bias" that is an accumulated bias over past iterations determined by criteria adjustment. In other words, "bias" represents a feedback metric or learning quantity as may be used as a weighting factor when choosing a particular sector. This bias may be increased or decreased with regard to whether a sector has had recent difficulties in prior iterations. This bias is updated in the adjustment criteria 422. Thus, the bias being adjusted in step 264 of
Referring now to
It should be noted that using this shortage percentage or shortage threshold may be used as an alternative to techniques which either succeed or fail. In other words, this shortage threshold provides for a range of acceptable configurations rather than a binary indication of success or failure for a single set of channel requests.
It should also be noted that this threshold value may be useful in instances, for example, when an impossible configuration is initially requested. In other words, an initially requested channel assignment request may be impossible to produce in accordance with constraints. Thus, having a shortage threshold may allow the channel assignment technique to possibly find other acceptable alternatives.
It should be noted that other embodiments may include one or more of the foregoing selection criteria for frequency and sector selection as well as different adjustment criteria, such as bias, that are used and updated when performing subsequent sector and channel selections. Other embodiments may use different criteria than that which has been described in the example tables in
It should be noted that the bias used in the foregoing description and figures may refer to a bias that represents an integer quantity. Other embodiments may include a bias expressed in a different numeric or other form. It should also be noted that the FSC and SSC may both be adjusted using the same global bias. Alternatively, an embodiment may use a first bias for FSC and a second different bias for SSC.
Referring now to
The foregoing techniques may use complex criteria requiring computationally intensive calculations for performing and evaluating channel assignments. Generally, as known to those skilled in the art, the channel assignment problem is an N-P complete problem. Further, calculations such as those included in performing C/I calculations may be very computationally time consuming. Thus, it may be desirable to choose specific SSC and/or FSC in accordance with this time consideration. In other words, in effect, the amount of time is a cost or constraint to be considered when determining the level of complexity of the selection criteria used in the channel assignment techniques.
In one embodiment, an acceptable amount of time or time threshold may be used. This time threshold may be expressed in, for example, but not limited to, an amount of CPU time, an amount of elapsed time, or other form.
Referring now to
What will now be described is a technique that may be used in generating color code assignments, such as DCCs or SATs, using channel assignment techniques. Color codes as previously described may be used in determining which sector is responsible for a signal received at a mobile unit. Generally, a channel assignment may be reused, for example, such that two or more sectors operate at the same channel or frequency. Use of a color code in combination with a channel frequency is one technique that may be used to distinguish between signals generated by these two or more sectors. A color code may be chosen for each frequency that is reused. Thus, a color code may be selected for a sector associated with a channel since the channel is used multiple times.
Assigning color codes may be done with a variation of the previously described channel assignment techniques. In the previously described channel assignment techniques, QOS input including constraints may be input to the configurator 12. For a color code assignment, there are modifications to these inputs previously described.
One modification is in the C/I calculations. The total co-channel C/I and total adjacent channel C/I formulas are modified to include reference to a color code "1". Referring now to
Another modification that may be included involves the channel separation matrix. In this embodiment, the channel separation matrix represents a color code separation matrix. In this use, the channel separation matrix is tightened. In particular, for each entry in the matrix which represents a common neighbor having a zero in the matrix entry, it is replaced with a 1. Recall that a zero indicates that two sectors could be assigned or use the same frequency. Replacing the zero with a 1 indicates that the same color code cannot be used for sectors associated with the matrix entry. Generally, common neighbor refers to the sector B that is a common neighbor to both sectors A and C. In other words, sector B may be handed off a signal from both sector A and sector C. A portion of the constraint or channel separation matrix may be used as will also be described in more detail in paragraphs that follow.
Referring now to
At step 922, a current channel variable "i" is assigned the first channel requiring color code assignments. Control proceeds to step 924 where sectors having channel i assigned to it and channels currently having color codes are assigned are identified. As a result of step 924, two subsets of sectors are identified. A first subset of sectors are those sectors associated with channel i requiring a color code assignment on this loop iteration. A second subset of sectors are those sectors associated with an adjacent channel to channel i, (e.g., channel i−1 and i+1) and pre-existing assignments, in which the sector already has a color code associated with the sector.
At step 926, pairwise C/I values are determined. In one embodiment, the pairwise C/I values are a submatrix or subset of the previously described C/I matrix. This submatrix may be represented by a square matrix having a dimension that is equal to or less than the existing C/I matrix previously described. This submatrix includes those pairwise C/I values having subscripts of sectors i,j corresponding to sectors identified in step 924. In other words, for every pair of sectors i and j identified in step 924, the pairwise C/I values corresponding to subscripts i,j and j,i are included in the submatrix. If this first embodiment of the pairwise C/I values is used, the modified cochannel and adjacent channel total C/I formulas 900 and 902 may be included and used in performing color code assignments in step 930, which is described in following paragraphs.
A second embodiment of step 926 determines pairwise C/I values by adjusting a portion of the pairwise C/I values as may be included in the pairwise C/I matrix. In particular, the pairwise C/I values for those adjacent channel sectors as identified in step 924 are adjusted. The C/I values correspond to those values associated with the second subset of sectors identified in step 924. These C/I values are adjusted by a predetermined value. In one instance this predetermined value may be the difference between the co-channel and adjacent channel thresholds that may serve as QOS inputs in a channel assignment process. If this second embodiment of the pairwise C/I values is used, the channel assignment technique which assigns the color codes to the sectors performs such that the comparison of the total C/I adjacent channel threshold test always succeeds. Additionally, the similar total co-channel C/I threshold test takes into account the co and adjacent channel C/I by using the adjusted C/I values just described.
Generally, step 926 takes into account filtering of a signal by transmitters and receivers. This may be performed, for example as in the second step 926 embodiment, by adding to the pairwise C/Is the difference between co-channel and adjacent channel constraints.
At step 928, a subset constraint or channel separation matrix is formed. This constraint matrix is also a subset of the previously described channel separation matrix. This subset channel separation matrix produced as a result of step 928 may include the more stringent channel separations for those sectors identified in step 924. Alternatively, the subset channel separation matrix may include a subset of the original channel separation matrix without being modified to include more stringent channel separations. It should be noted that this subset matrix may be used in step 930 in determining color code assignment.
Control proceeds to step 930 where a channel assignment technique is used to assign color codes to sectors. In a channel assignment technique, frequencies or channels, and sectors are the two sets of items being associated. Alternatively, in this instance for color code assignments, there is a set of color codes to be assigned, and a set of sectors to which these may be assigned. The set of color codes is the set of all possible color codes available. The set of sectors are those sectors produced as a result of step 924, the first subset of sectors which are associated with channel i and require a color code assignment on this iteration using the channel assignment technique at step 930.
At step 932, a determination is made as to whether all channels or frequencies have been processed. If so, control proceeds to step 934 where the method 920 stops. Otherwise, control proceeds to step 936 where "i" is assigned the next channel for which color codes are assigned.
It should be noted that the foregoing suggests modifications to the channel assignment technique to assign or associate color codes with sectors. The following summarized some of the analogous items and steps previously described as used in channel assignment and the color code assignment elements.
Channel assignment
Color code assignment
associates a sector with a
associates a color code with
a sector
a sector is chosen from a set of
a sector is chosen from a set
sectors requiring channel
of sectors requiring a color
code assignment for the
channel currently being
a channel is chosen from a set
a color code is chosen from a
of system channels
set of system color codes
channel separation matrix
subset of channel separation
matrix (note may include
modified separation values)
pairwise C/I values
subset of pairwise C/I values
(note may include adjusted
C/I values or just subset of
original values.
While the invention has been disclosed in connection with preferred embodiments shown and described in detail, their modifications and improvements thereon will become readily apparent to those skilled in the art. Accordingly, the spirit and scope of the present invention should be limited only by the following claims.
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|U.S. Classification
|455/450, 455/456.1, 455/452.1, 455/449, 455/456.2, 455/448, 455/447, 455/453, 455/464, 455/456.3, 455/446
|International Classification
|Cooperative Classification
|European Classification
|Feb 22, 2000
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I am not a big Perry Mason fan, but this is the movie that got me hooked more on the movie series than the tv series. It starts out with a pretty good ghost story which I wanted to know a lot more about than the murder. We don't even see much of this spooky old edifice that the plot revolves around, but what we do see has a wonderful shadowy "Dark Shadows" Collinwood kind of feel. The murder mystery, don't get me wrong, is excellant; it has more twists and turns than a politician in a confessional booth. Raymond Burr and Barbera Hale fit into their old roles very well, but William Katt will always remind me of "The Greatest American Hero." Robert Stack emotes a great character just a few shades away from his character of Elliot Ness and Dwight Schultz plays a nervous and slightly shady character not that far unlike Lt. Barclay of Star Trek. Kim Delaney's acting reminds me too much of too many other actresses, particularly that of Joanna Going, but it may be because of too many Dark Shadows parallels: the spooky location, the ghosts, the painting, hidden rooms and the squirrely maintenance man who is almost too similar to John Karlen's Willie Loomis. In short, if it hadn't been for my fondness for ghosts and that series, I might never have seen this movie at all.


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Affiliate Membership
To extend the benefits of Devon Chamber membership to other local Chambers in the South West Peninsula we offer the opportunity to become an Affiliate member of Devon Chamber of Commerce.
Devon Chamber is committed to fostering a positive economic climate in the South West where local companies can grow both through their own efforts and on the back of economic development projects encouraged by the Chamber. A strong business community is a vital catalyst in securing economic growth and by encouraging a peninsula Chamber movement we can have greater impact as we speak with a single voice.
As the accredited Chamber for Devon as part of the British Chambers of Commerce (BCC) network, Devon Chamber has unique access to senior government ministers, policy makers, a network of over 80,000 UK businesses and 40 overseas markets. Through Devon Chamber Affiliate membership local Chambers and their members can participate in the BCC network and gain access to the benefits that are reserved only for BCC members.
The Affiliation scheme will also allow local Chambers to gain direct access to a number of Devon Chamber benefits that are normally only available to our members. Our many programmes and events will increase exposure of Affiliate Chambers, educate local Chamber members and provide countless networking opportunities, offering great value for local Chambers and their members.
What are the benefits of Affiliate Membership?
Becoming an Affiliate member of Devon Chamber opens up a range of new benefits to your members, including:
10 Copies of Chamberlink (to the Chamber itself)
Submit editorials for Chamberlink
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Directory listing for Chamber on the website
Access to free events – except City Conversations
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Our Affiliate member rates are designed to be affordable for local Chambers, meaning that your Chamber could become an Affiliate Chamber for a basic annual fee of just £230 plus a 'per member' fee* of £1.00 per member.
*we will ask you to update us with your membership numbers at each renewal.
Join now or call us on 01752 220471 to discuss affiliate membership in more detail.
Have a question about Chamber membership? Visit our FAQ page or contact us.
See Also:
Business Charter
British Chambers of Commerce
Business Support
events and training
Meet The Chamber: Plymouth
Join us for the Devon Chamber's FREE networking event, Meet The Chamber. This event is designed to: Welcome members that are new...
Thursday 27/04/2017
Crunchy Breakfast
Join us for our monthly networking breakfast event to debate the county's crunchy topics. Date: Wednesday 3rd MayTime: 07:30-09:00Venue: The Grange Resturant Buckfast Abbey Cost: Members: £12+VAT/ Non-Members: £24+VAT
Wednesday 03/05/2017
MP Round Table: Oliver Colvile (Plymouth, Sutton and Devonport Constituency)
Devon Chamber of Commerce are delighted to invite members to a round table discussion with local MP; Oliver Colvile. You will be joining other Chamber members from a variety...
Friday 05/05/2017


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Baldwin Lake Stables has been guiding trail rides in the heart of the San Bernardino Forest since 1988. They offer one or two-hour trail rides across a variety of terrains in Big Bear Valley. Three-hour and half-day rides along the Pacific Coast Rim offer expansive views of the Mojave Desert. Sunset and private rides are available with reservations. The outfitter is open year-round and also provides horseback rides through Big Bear's winter wonderland. The stables have hand-led pony rides for the little ones and a petting zoo with a variety of animals.
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Tonight is the premiere of Otello in Opernhaus Dortmund. I have a lot of fond memories wrapped around Otello, and I'm very happy to be singing in the chorus of our fantastic production tonight. Toi toi toi to all involved.
Premiere: Hamlet – Sein oder Nichtsein
Today is the premiere of Hamlet: Sein oder Nichtsein at the Kinder und Jugend Theater Dortmund. This is a new work by Timo Jouko Herrmann and André Meyer based on the Hamlet story, though it diverges in a few meaningful ways.
In December I wrote this on Facebook:
And that remains mostly true. It's not as atonal as I originally thought (Ophelia has some especially lovely and melodious passages), and it's actually meant for teenagers from the age of 14 and up (this hews much closer to Hamlet than, for example, The Lion King).
But I had thought that I'd never get to do any of Hamlet's famous speech, and here we are singing it in the chorus in a dark but colorful and rich production. This is an exciting work visually, thematically and aurally (the sounds coming from the orchestra are especially thrilling).
Toi toi toi to all involved!
Premiere: Die Blume von Hawaii
Heute Abend im Opernhaus Dortmund findet die Premiere von Paul Abrahams Die Blume von Hawaii statt. Ich singe die Kombi-Rolle Kanako Hilo und Kaluna (Kanako spricht und Kaluna singt, obwohl praktisch bin ich Kanako Hilo die ganze Zeit).
Wie Roxy und ihr Wunderteam ist die Musik eine Jazz und Operette Mischung. Man kann klassische Stimmen und Stepptanz von der Bühne hören, aber es gibt viel mehr dazu zu erleben. Viele Farben. Viel Humor. Viel, das schön und kreativ ist.
Ich freue mich sehr auf die Premiere. Toi toi toi an allen Beteiligten!
Tonight in Opernhaus Dortmund is the premiere of Paul Abraham's Die Blume von Hawaii. I'm singing a combination role of Kanako Hilo and Kaluna (Kanako talks while Kaluna sings, but practically speaking I'm Kanako Hilo the whole time if that makes any sense).
Like Roxy und ihr Wunderteam, this contains a mixture of jazz and operetta musical influences. The audience will hear classical voices and tap dancing very near to one another, but there's much more to experience. Many colors. Lots of humor. Much beauty and creativity.
I'm very much looking forward to it. Toi toi toi to all!
Mehr Infos/More Information
Thank You, President Obama
Thank you, President Barack Obama, for the last eight years. I and many other Americans wish you the best as you transition to back to normal-ish citizen life, and although I'm sad that you will no longer be president, I am excited to see what you and your family will do next.
Smell the Roses 1: Getz, Elzhi, Patience
Here are some things that caught my attention this past week that you might enjoy as well.
Stan Getz's Jazz Samba Encore! and Johnny Patience's California Dreaming photos
Jazz Samba Encore! is probably the greatest album I've ever heard for instantly curing winter blues. Germany gets very dark, cold and wet in the winter, and I've always been affected by seasonal depression.
Enter Stan Getz, and it's an instant transformation. A grey day seems light and breezy, and the grey days shift to light pastels in my inner eye. Combine this with looking at the beautiful film photo set called "California Dreaming" from Johnny Patience, and it's a great way to brighten up your inner world.
"Samba de Duas Notas" and "Menina Flor" are particular favorites, though the whole album is terrific.
Lead Poison by Elzhi
I heard the track "Two 16's" as the final selection on the Mr. Choc Takeaway Abstract Radio episode, and I was immediately taken. It's hard for me to speak intelligently about hip hop, but the backup tracks are musically engaging in their own right, and the lyrics are adventurous and self-aware.
The whole album is strong, but I keep returning to a few tracks. The first track "Medicine Man" is a startlingly strong argument for creativity as the answer to inner turmoil. "Two 16s" has backup vocals that might trick you into thinking the subject is lighter than it actually is. "She Sucks" is, cough cough, not what you might think it's about, and there's something about horror-themed tracks that I find really fun. There may also be some commentary on addiction in it as well. Also be sure to check out "Introverted", "CoSIGN" and "Keep Dreaming", which is both confrontational and inspirational.
Yes, there are some explicit words on this album, though not every track earns an "Explicit" warning.
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