Joint User Scheduling and Adaptive Intercell Interference Cancelation for MISO Downlink Cellular Systems

• Published in: IEEE transactions on vehicular technology 2013-01, Vol.62 (1), p.172-181
• Main Authors: MOON, Sung-Hyun, LEE, Changhee, LEE, Sang-Rim, LEE, Inkyu
• Format: Article
• Language: English
• Subjects: Applied sciences; Array signal processing; Complexity theory; Coordinated multipoint (CoMP); Detection, estimation, filtering, equalization, prediction; Downlink; Equipments and installations; Exact sciences and technology; Information, signal and communications theory; intercell interference (ICI) cancelation; Interference; joint scheduling; limited feedback; MIMO; Mobile radiocommunication systems; network multiuser multiple-input-multiple-output (MIMO); Organization and planning of networks (techniques and equipments); Radiocommunications; Signal and communications theory; Signal to noise ratio; Signal, noise; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Transmission and modulation (techniques and equipments); Vectors
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2012.2217363

Recently, an adaptive intercell interference (ICI) mitigation technique has been proposed for downlink cellular systems as a means to increase throughput with low system complexity. However, in the prior work, the issue of intercell user scheduling has not been considered. In this paper, we study multiple-input-single-output (MISO) downlink cellular systems that jointly design adaptive ICI cancelation (ICIC) and intercell user scheduling assuming that partial channel state information (CSI) is shared among base stations (BSs). Since the optimal solution would require high complexity, we investigate a new low-complexity algorithm that selects the best users and their beamforming strategies in terms of maximizing the weighted sum rate (WSR). To this end, we first develop a simple threshold criterion for each user to decide the preferred beamforming strategy based on the derivation of the expected signal-to-interference-plus-noise ratio (SINR). Then, according to users' feedback about their decisions, a successive user and beamforming selection algorithm is performed at the BSs. From simulation results, we show that, combined with proportional fair scheduling, the proposed scheme provides excellent throughput performance with very low computational complexity and the amount of inter-BS CSI exchange. Furthermore, we discuss an extension of the proposed scheme to limited feedback systems and observe that our algorithm also provides similar advantages over conventional schemes with quantized feedback.