Emergent Mind

QoS-Based Linear Transceiver Optimization for Full-Duplex Multi-User Communications

(1612.04958)
Published Dec 15, 2016 in cs.IT and math.IT

Abstract

In this paper, we consider a multi-user wireless system with one full duplex (FD) base station (BS) serving a set of half duplex (HD) mobile users.To cope with the in-band self-interference (SI) and co-channel interference, we formulate a quality-of-service (QoS) based linear transceiver design problem. The problem jointly optimizes the downlink (DL) and uplink (UL) beamforming vectors of the BS and the transmission powers of UL users so as to provide both the DL and UL users with guaranteed signal-to-interference-plus-noise ratio performance, using a minimum UL and DL transmission sum power.The considered system model not only takes into account noise caused by non-ideal RF circuits, analog/digital SI cancellation but also constrains the maximum signal power at the input of the analog-to-digital converter (ADC) for avoiding signal distortion due to finite ADC precision. The formulated design problem is not convex and challenging to solve in general. We first show that for a special case where the SI channel estimation errors are independent and identically distributed, the QoS-based linear transceiver design problem is globally solvable by a polynomial-time bisection algorithm.For the general case, we propose a suboptimal algorithm based on alternating optimization (AO). The AO algorithm is guaranteed to converge to a Karush-Kuhn-Tucker solution.To reduce the complexity of the AO algorithm, we further develop a fixed-point method by extending the classical uplink-downlink duality in HD systems to the FD system.Simulation results are presented to demonstrate the performance of the proposed algorithms and the comparison with HD systems.

We're not able to analyze this paper right now due to high demand.

Please check back later (sorry!).

Generate a summary of this paper on our Pro plan:

We ran into a problem analyzing this paper.

Newsletter

Get summaries of trending comp sci papers delivered straight to your inbox:

Unsubscribe anytime.