Large-Scale Antenna Systems With UL/DL Hardware Mismatch: Achievable Rates Analysis and Calibration

Abstract

This paper studies the impact of hardware mismatch (HM) between the base station (BS) and the user equipment (UE) in the downlink (DL) of large-scale antenna systems. Analytical expressions to predict the achievable rates are derived for different precoding methods, i.e., matched filter (MF) and regularized zero-forcing (RZF), using large system analysis techniques. Furthermore, the upper bounds on achievable rates of MF and RZF with HM are investigated, which are related to the statistics of the circuit gains of the mismatched hardware. Moreover, we present a study of HM calibration, where we take zero-forcing (ZF) precoding as an example to compare two HM calibration schemes, i.e., Pre-precoding Calibration (Pre-Cal) and Post-precoding Calibration (Post-Cal). The analysis shows that Pre-Cal outperforms Post-Cal schemes. Monte-Carlo simulations are carried out, and numerical results demonstrate the correctness of the analysis.

A Closed-Loop Reciprocity Calibration Method for Massive MIMO in Terrestrial Broadcasting Systems

“…Using pre-precoding calibration in [11], the UL channel estimation results used for precoding will bẽ…”

“…Hence, the impairments of TD are assumed to be approximate to 0 with remaining calibration error a T and a R respectively. Using pre-precoding calibration in [11], the UL channel estimation results used for precoding will beH…”

“…By utilizing spatial multiplexing, a massive MIMO base station can serve multiple users simultaneously through multi-user beamforming (see [10], [11] and references therein). In order to use multi-user beamforming, the BS needs to know the downlink channel state information.…”

Modeling and estimation of massive MIMO channel non-reciprocity: Sparsity-aided approach

“…In this respect, [5] provides a downlink sum-rate analysis for a general multi-user MIMO system with zero-forcing (ZF) or eigen-beamforming based DL precoding under channel nonreciprocity due to FR mismatch. Then, [8], [9] investigate the achievable downlink sum-rates for maximum-ratio transmission (MRT) and ZF precoding schemes in massive MIMO systems, demonstrating significant performance degradation under practical values of channel non-reciprocity parameters. It is evident that the results of such studies clearly show the need to estimate the channel non-reciprocity parameters in order to mitigate the non-reciprocity problem.…”

Cooperative TDD reciprocity calibration with diversity combining for distributed large-scale MIMO systems

“…Fortunately, the RF mismatches at the receivers can be ignored since they have a negligible influence on system performance [8] . Thus, only a partial calibration was necessary to compensate for the RF mismatches at the transmitters [9] . For distributed systems, the LS (Least Squares) method was presented in Ref.…”