Title :
Reliable Uncoded Communication in the SIMO MAC
Author :
Chowdhury, Mashrur ; Goldsmith, Andrea
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
Abstract :
A single-input multiple-output multiple access channel, with a large number of uncoded noncooperating single-antenna transmitters and joint processing at a multiantenna receiver is considered. The minimum number of receiver antennas per transmitter that is needed for perfect recovery of the transmitted signals with overwhelming probability is investigated. It is shown that in the limit of a large number of transmitters, and in a rich scattering environment, the per-transmitter number of receiver antennas can be arbitrarily small, not only with the optimal maximum likelihood decoding rule, but also with much lower complexity decoders. Comparison with the ergodic capacity of the channel in the limit of a large number of transmitters suggests that uncoded transmissions achieve the Shannon-theoretic scaling behavior of the minimum per-transmitter number of receiver antennas. Thus, the diversity of a large system not only makes the performance metrics for some coded systems similar to that of uncoded systems, but also allows efficient decoders to realize close to the optimal performance of maximum likelihood decoding.
Keywords :
MIMO communication; antenna arrays; channel capacity; electromagnetic wave scattering; maximum likelihood decoding; multiuser channels; probability; radio receivers; radio transmitters; telecommunication network reliability; wireless channels; Shannon-theoretic scaling; channel capacity; lower complexity decoder; maximum likelihood decoding rule; multiantenna receiver; probability; rich scattering environment; single antenna transmitter; single input multiple output multiple access channel; uncoded communication reliablility; Maximum likelihood decoding; Receiving antennas; Reliability; Transmitting antennas; Convex programming; Maximum likelihood detection; Multiuser detection; Spatial diversity; convex programming; maximum likelihood detection; multiuser detection;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2014.2371040