29 signal degradation, hence, reduces ICI. Moreover, it can be observed clearly that with low user transmit powers, there is a significant reduction in ICI compared to th e high transmission powers. It is further interesting to note that the performance of greedy scheduling with PC always remain better than the greedy scheme in terms of incurred ICI, average fairness (see Fig. 11part(a)) and average power consumption of the users . The top figure in Fig. 11 quantifies the average fairness of th e greedy with and without PC and round robin schedulers. With the increase of transmit powers, far users can also adapt their power which increases the average fairness among users. For high user transmit powers, the greedy scheduling with PC achieves the fairness of round robin scheme as is also evident from Fig. 9. However, it is important to note that the capacity (see Fig. 11part(b)) and power preservation remains better than the round robin scheme in which power savings are zero. The bottom figure in Fig. 11 demonstrate the network capacityof interference limited systems (i.e., thermal noise is neglected). Without PC, the performance of greedy and round robin scheduling remains independent of the transmit power as the factor of P$_{max}$ cancels out in the capacity calculation. However, since the greedy scheduling with PC have less ICI then the greedy scheduler, the network capacity is expected to increase which is not the case as the corresponding user transmit powers are also lowered along with the interfering powers. The main reason of the capacity degradation with the increase in transmit power budget is that the greater transmission power more users can compensate path loss which reduces the number of users transmitting with their maximum powers. This phenomena on one hand increase average power savings whereas on the other hand degrades overall system capacity. REFERENCES [1] B. Pijcke, M. Z-Colin, M. Gazalet, M. Gharbi, and P. Corlay, “An analytical model for the intercell interference powe r in the downlink of wireless cellular networks,” arXiv:1107.4199v1 , July 2011. [2] K.W. Sung, H. Haas, and S. McLaughlin, “A semianalyticalPDF of downlink SINR for femtocell networks,” EURASIP Journal on Wireless Communications and Networking , Jan. 2010. [3] S. Plass, X.G. Doukopoulos, and R. Legouable, “Investig ations on link-level inter-cell interference in OFDMA systems,” IEEE Symposium on Communications and Vehicular Technology , pp. 49–52, Liege, Nov. 2006. [4] Z. Xu, G. Y. Li, and C. Yang, “Optimal threshold design forFFR Schemes in multi-cell OFDMA networks,” IEEE International Conference on Communications (ICC’11) , pp. 1–5, 2011. [5] C. Seol and K. Cheun, “A statistical inter-cell interfer ence model for downlink cellular OFDMA networks under log-normal shadowing and multipath Rayleigh fading,” IEEE Transactions on Wireless Communications , vol. 57, no. 10, pp. 3069–3077, Oct. 2009. [6] S. Elayoubi, B. Haddada, and B. Fourestie, “Performanceevaluation of frequency planning schemes in OFDMA based networks,” IEEE Transactions on Wireless Communications , vol. 7, no. 5, pp. 1623–1633, May 2008.