Abstract
We study the performance of a single-cell massive multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) system that uses linear precoding to serve multiple users on the same time-frequency resource. To minimize overhead, the channel estimates at the base station are obtained via comb-type pilot tones during the training phase of a time-division duplexing system. Polynomial regression is used to interpolate the channel estimates within each coherence block. We show how such regressors can be designed in an offline fashion without the need to obtain channel statistics at the base station, and we assess the downlink performance over a wide range of system parameters.
Highlights
Multi-user multiple-input multiple-output (MU-MIMO) systems with large number of base station antennas hold the promise of high throughput communications for emerging wireless deployment [1–4]
While the benefits of spatial multiplexing may be fully realized when the number of base station antennas is equal to the number of scheduled user terminals, MU-MIMO systems with an excessively large number of antennas, known as massive MIMO, have recently gained attention owing in part to the following benefits [5]:
We study the effects of regression-based interpolation of channel state information (CSI) and its effects on the accuracy of linear precoding in a downlink massive MIMO system
Summary
Multi-user multiple-input multiple-output (MU-MIMO) systems with large number of base station antennas hold the promise of high throughput communications for emerging wireless deployment [1–4]. Coherent massive MIMO systems require channel state information (CSI) at the base station in order to compute linear precoder filters for the downlink and equalization filters for the uplink. Such systems are typically designed for a time-division duplexing (TDD) scheme where the uplink and downlink share the transmission bandwidth. For multi-user systems, the base station may use the estimated CSI obtained from uplink pilots to construct linear precoders (and equalizers). We propose polynomial regression as a way to interpolate the multiplexed pilots in the uplink into a single channel estimate over a block of bandwidth, i.e., over a coherence block These regressors may be computed in an offline fashion without any knowledge of the channel.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have