Channel (broadcasting)

Operating system

Topology (electrical circuits)

MIMO

Ideal (ethics)

Mathematics

Wireless

Computer science

Channel state information

Limit (mathematics)

Philosophy

Telecommunications

Algorithm

Control (management)

Coherence (philosophical gambling strategy)

Combinatorics

Artificial intelligence

Coherence time

Control theory (sociology)

Statistics

Epistemology

Mathematical analysis

Overhead (engineering)

IEEE Transactions on Communications

In practical massive MIMO systems, a substantial portion of system resources are consumed to acquire channel state information (CSI), leading to a drastically lower system capacity compared with the ideal case, where perfect CSI is available. In this paper, we show that the overhead for CSI acquisition can be largely compensated by the potential gain due to the sparsity of the massive MIMO channel in a certain transformed domain. To this end, we propose a novel blind detection scheme that simultaneously estimates the channel and data by factorizing the received signal matrix. We show that by exploiting the channel sparsity, our proposed scheme can achieve a degree of freedom (DoF) very close to the ideal case, provided that the channel is sufficiently sparse. Specifically, the achievable DoF has a fractional gap of only 1/T from the ideal DoF, where T is the channel coherence time. This is a remarkable advance for understanding the performance limit of the massive MIMO system. We further show that the perform...

Blind Signal Detection in Massive MIMO: Exploiting the Channel Sparsity