Joint Automatic Gain Control and MMSE Receiver Design for Quantized Multiuser MIMO Systems

Abstract

This paper presents the development of a joint optimization of an automatic gain control (AGC) algorithm and a linear minimum mean square error (MMSE) receiver for multiuser multiple input multiple output (MU-MIMO) systems with coarsely quantized signals. The optimization of the AGC is based on the minimization of the mean square error (MSE) and the proposed receive filter takes into account the presence of the AGC and the effects due to quantization. Moreover, we provide a lower bound on the capacity of the MU-MIMO system by deriving an expression for the achievable rate. The performance of the proposed Low-Resolution Aware MMSE (LRA-MMSE) receiver and AGC algorithm is evaluated by simulations, and compared with the conventional MMSE receive filter and Zero-Forcing (ZF) receiver using quantization resolution of 2, 3, 4 and 5 bits.

Joint AGC and Receiver Design for Quantized Large-Scale MU-MIMO Systems with C-RANs

“…The elements of n FH are considered to be i.i.d ZMCSCG random variables with variance σ 2 τ . From (34) and (35) the digital signal vector at the CU can be expressed as…”

“…The distortion produced by the quantization process and its impact on the performance of communication systems has been studied in the literature [14], [15], [22], [18], [17], [19], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [33], [20], [31], [32], [34]. Nevertheless, few studies address the design of AGCs.…”

“…Unlike existing approaches with deterministic AGCs [24] and modified MMSE receive filters [24], [21], [23], the proposed AGC-LRA-MMSE approach jointly optimizes the AGCs and the receive filters based on a statistical criterion using alternating optimization. We report in [34] optimistic results of the proposed joint optimization of the AGC and linear receivers in a MU-MIMO scenario. However, [34] does not consider the SIC detection scheme, the imperfect CSI, the imperfect knowledge about the AGC coefficients at the CU, and does not evaluate the performance of the proposed technique in a large-scale MU-MIMO system in C-RANs that are considered by this paper.…”

“…We report in [34] optimistic results of the proposed joint optimization of the AGC and linear receivers in a MU-MIMO scenario. However, [34] does not consider the SIC detection scheme, the imperfect CSI, the imperfect knowledge about the AGC coefficients at the CU, and does not evaluate the performance of the proposed technique in a large-scale MU-MIMO system in C-RANs that are considered by this paper. We also derive expressions for the achievable sum rates and evaluate the computational complexity of the proposed AGC-LRA-MMSE approach.…”

Joint AGC and receiver design for large‐scale MU‐MIMO systems with low‐resolution signals in C‐RANs

“…The distortion produced by the quantisation process and its impact on the performance of communication systems has been studied in the literature [14–33]. Nevertheless, few studies address the design of AGCs.…”