IEEE Transactions on Information Theory · 2004 · 695 citations · 20 references
EngineeringCommunicationElectrical EngineeringAntennasSchedulingWireless CommunicationsChannel CapacityChannel EstimationCommunication SchedulingMimo AntennasMutual InformationWireless Channel ModelingCentral Limit TheoremsChannel Capacity ApproximationsMimoMimo Channel ModelingMimo SystemsRayleigh FadingShadow FadingThroughput
Wireless data traffic is projected to grow rapidly, and multiple‑antenna (MIMO) systems are a leading candidate to achieve high spectral efficiencies in rich scattering environments, especially when combined with scheduling and rate‑feedback algorithms to boost throughput. The study analyzes the gains from scheduling and the number of bits required for rate feedback, and discusses the implications of channel hardening for data and voice services, scheduling, and rate‑feedback. The authors approximate the distribution of MIMO channel mutual information by proving a central‑limit theorem for large‑antenna Rayleigh‑fading channels, and briefly consider the effect of shadow fading. They find that, although average mutual information increases with antenna count, the variance of mutual information grows very slowly or may even shrink, indicating channel hardening.
Wireless data traffic is expected to grow over the next few years and the technologies that will provide data services are still being debated. One possibility is to use multiple antennas at base stations and terminals to get very high spectral efficiencies in rich scattering environments. Such multiple-input/multiple-output (MIMO) channels can then be used in conjunction with scheduling and rate-feedback algorithms to further increase channel throughput. This paper provides an analysis of the expected gains due to scheduling and bits needed for rate feedback. Our analysis requires an accurate approximation of the distribution of the MIMO channel mutual information. Because the exact distribution of the mutual information in a Rayleigh-fading environment is difficult to analyze, we prove a central limit theorem for MIMO channels with a large number of antennas. While the growth in average mutual information (capacity) of a MIMO channel with the number of antennas is well understood, it turns out that the variance of the mutual information can grow very slowly or even shrink as the number of antennas grows. We discuss implications of this "channel-hardening" result for data and voice services, scheduling, and rate feedback. We also briefly discuss the implications when shadow fading effects are included.
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