Beamforming for Bidirectional Mimo Full Duplex Under the Joint Sum Power and Per Antenna Power Constraints

Abstract

This paper considers a bidirectional (BD) full-duplex (BD-FD) communication system design under the joint sum-power and per-antenna power constraints. The sum-power constraints are naturally imposed by regulation to limit the total transmit power, and the per-antenna power constraints consider the physical limits of the power amplifiers (PAs). We propose a novel beamforming design to maximize the weighted sum-rate (WSR) with alternating optimization under the limited dynamic range (LDR) noise model. At each iteration, we use minorization-maximization approach to optimize the beamformers and power allocation. Simulation results show significant performance gain compared to a half-duplex BD system or FD system with only sum-power constraints. However, the gains are limited by the maximum of the thermal noise variance or the LDR noise variance.

ZF Precoding-Based Spatial Domain SIC Method for MIMO Full Duplex Systems: A Performance Analysis Under CSI Errors

“…) where ∆H eq = W H RF,eq ∆HF RF . Since the conventional matrix product only consists of linear operations, it can be easily deduced from (7) that the (m,n)th coefficient of the equivalent channel matrix ∆H eq,m,n follows a zero-mean Gaussian distribution as for Ψ m,n . We then denote ν 2 m,n the variance of ∆H eq,m,n which is constructed as a linear combination of σ 2 m,n and depends on the different steering angles defined in (2) and the FD transceiver antenna numbers, so that each coefficient of the equivalent channel matrix obeys a centered Gaussian distribution (i.e.…”

“…By replacing H ′ eq by its definition in (7) and by factorising by H H eq H eq , ( 12) can be further developed as:…”

“…The method has proven to be highly efficient in terms of SIC performance and enables an interference-free environment for the considered MIMO FD transceiver. However, similarly to [6], [7], a perfect channel state information (CSI) is considered in [5], which may be an overly idealistic assumption. In fact, in practice, the CSI should be considered as imperfect due to the CSI estimators and the presence of the additive noise.…”