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BROADCAST CHANNEL TRANSMISSION CAPACITY

The most important studies of well-known Broadcast Communication Channels (BCC) models are associated with obtaining accurate information efficiency estimates(IE). Earlier, the coding problem was stated, the joint information measure (JI) of the proposed BCC model was introduced and investigated. Then the information capacity (IC) was introduced and the conditions for maximizing the average JI were defined, the uncertainty concept was defined, and an evidence-based adjustment of the Feinstein inequality for the channel model under study was made. In the present paper, the general information accurate estimate transmitted via the BCC by proving the fundamental coding theorems is obtained. On the basis of the previously obtained results, the inverse coding theorem for BCC was proved, which determines the condition for the code error average probability striving to one, which consists in choosing a code with a speed exceeding IE BCC. The Feinstein inequality role on the basis of which the direct coding theorem roof is carried out is determined. The theorem states that there are codes with a low error probability, provided that the code rate does not exceed the channel's IE. The coding theorems cumulative result proves that the IE and the throughput (BC) coincide. An accurate estimate of BC BCC is obtained. The results obtained do not contradict and extend the well-known IE studies of various BCC models and can be used by designers to assess the synthesized communication systems potential capabilities, including BCC channels. The purpose of further research is the gain estimate through IE channel transmission in comparison with the successive transmission through the component channels, which will outline the conditions for the preferred use of the BCC.