TY - JOUR
T1 - Distributed MIMO systems for nomadic applications over a symmetric interference channel
AU - Simeone, Osvaldo
AU - Somekh, Oren
AU - Vincent Poor, H.
AU - Shamai, Shlomo
N1 - Funding Information:
Manuscript received December 09, 2007; revised December 26, 2008. Current version published November 20, 2009. This work was supported in part by a Marie Curie Outgoing International Fellowship and the NEWCOM++ network of excellence both within the 7th European Community Framework Programme, by the Israel Science Foundation, and by the U.S. National Science Foundation under Grants CNS-06-25637, CNS-06-26611, ANI-03-38807, and CCF-0914899.
PY - 2009/12
Y1 - 2009/12
N2 - A single source communicates with a single destination via a remote wireless multiple-antenna (multiple-input multiple-output (MIMO)) transceiver. The source has access to each of the transmit antennas through a finite-capacity link, and likewise the destination is connected to the receiving antennas via capacity-constrained channels (e.g., as for wired or time-division multiple access (TDMA) channels). Targeting a nomadic communication scenario, in which the remote MIMO transceiver is designed to serve different standards or services, it is assumed that transmitters and receivers are oblivious to the encoding function shared by source and destination. Assuming a Gaussian symmetric interference network as the channel model (as for regularly placed transmitters and receivers), achievable rates are investigated and compared with an upper bound (that holds also for codebook-dependent operation). Closed-form expressions are derived for large numbers of antennas (and in some cases large signal-to-noise ratios (SNRs)), and asymptotics of the achievable rates are studied with respect to either link capacities or SNR. Overall, the analysis points to effective transmission/reception strategies for the distributed MIMO channel at hand, which are optimal under specified conditions. In particular, it is concluded that in certain asymptotic and nonasymptotic regimes there is no loss of optimality in designing the system for nomadic applications (i.e., assuming oblivious transmitters and receivers). Numerical results validate the analysis.
AB - A single source communicates with a single destination via a remote wireless multiple-antenna (multiple-input multiple-output (MIMO)) transceiver. The source has access to each of the transmit antennas through a finite-capacity link, and likewise the destination is connected to the receiving antennas via capacity-constrained channels (e.g., as for wired or time-division multiple access (TDMA) channels). Targeting a nomadic communication scenario, in which the remote MIMO transceiver is designed to serve different standards or services, it is assumed that transmitters and receivers are oblivious to the encoding function shared by source and destination. Assuming a Gaussian symmetric interference network as the channel model (as for regularly placed transmitters and receivers), achievable rates are investigated and compared with an upper bound (that holds also for codebook-dependent operation). Closed-form expressions are derived for large numbers of antennas (and in some cases large signal-to-noise ratios (SNRs)), and asymptotics of the achievable rates are studied with respect to either link capacities or SNR. Overall, the analysis points to effective transmission/reception strategies for the distributed MIMO channel at hand, which are optimal under specified conditions. In particular, it is concluded that in certain asymptotic and nonasymptotic regimes there is no loss of optimality in designing the system for nomadic applications (i.e., assuming oblivious transmitters and receivers). Numerical results validate the analysis.
KW - Distributed processing
KW - Multiple-inpute multipleoutput (MIMO) systems
KW - Multirelay channels
KW - Oblivious cooperation
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U2 - 10.1109/TIT.2009.2032730
DO - 10.1109/TIT.2009.2032730
M3 - Article
AN - SCOPUS:77955600903
SN - 0018-9448
VL - 55
SP - 5558
EP - 5574
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
IS - 12
ER -