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A sender wishes to broadcast a message of length $n$ over an alphabet to $r$ users, where each user $i$, $1 \leq i \leq r$ should be able to receive one of $m_i$ possible messages. The broadcast channel has noise for each of the users (possibly different noise for different users), who cannot distinguish between some pairs of letters. The vector $(m_1, m_2,...s, m_r)_{(n)}$ is said to be feasible if length $n$ encoding and decoding schemes exist enabling every user to decode his message. A rate vector $(R_1, R_2,..., R_r)$ is feasible if there exists a sequence of feasible vectors $(m_1, m_2,..., m_r)_{(n)}$ such that $R_i = \lim_{n \mapsto \infty} \frac {\log_2 m_i} {n}, {for all} i$. We determine the feasible rate vectors for several different scenarios and investigate some of their properties. An interesting case discussed is when...
Comment: 10 pages, 3 figures; accepted by Wireless Personal Communications
Comment: This paper has been withdrawn by the author for submission to another journal
Comment: Submitted to IEEE Transactions on Signal Processing (partially presented at Allerton 2010)
Sparse Code Division Multiple Access (CDMA), a variation on the standard CDMA method in which the spreading (signature) matrix contains only a relatively small number of non-zero elements, is presented and analysed using methods of statistical physics. The analysis provides results on the performance of maximum likelihood decoding for sparse spreading codes in the large system limit. We present results for both cases of regular and irregular spreading matrices for the binary additive white Gaussian noise channel (BIAWGN) with a comparison to the canonical (dense) random spreading code.
Given a multiple-input multiple-output (MIMO) channel, feedback from the receiver can be used to specify a transmit precoding matrix, which selectively activates the strongest channel modes. Here we analyze the performance of Random Vector Quantization (RVQ), in which the precoding matrix is selected from a random codebook containing independent, isotropically distributed entries. We assume that channel elements are i.i.d. and known to the receiver, which relays the optimal (rate-maximizing) precoder codebook index to the transmitter using B bits. We first derive the large system capacity of beamforming (rank-one precoding matrix) as a function of B, where large system refers to the limit as B and the number of transmit and receive antennas all go to infinity with fixed ratios. With beamforming RVQ is asymptotically optimal, i.e., no...
Comment: 5 pages, 1 figure, Proceedings of the 2007 IEEE International Symposium on Information Theory, Nice, France, June 24-29, 2007
Comment: 22 pages, 8 figures, submitted to IEEE Trans. Inform. Theory
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