상세정보
학술지
Joint User Scheduling and Adaptive Intercell Interference Cancelation for MISO Downlink Cellular Systems
- 저자
- 문성현, 이창희, 이상림, 이인규
- 발행일
- 201301
- 출처
- IEEE Transactions on Vehicular Technology, v.62 no.1, pp.172-181
- ISSN
- 0018-9545
- 출판사
- IEEE
- 초록
- 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. © 2012 IEEE.
- KSP 제안 키워드
- Cellular system, Channel State Information(CSI), Feedback system, Low Computational Complexity, Low-complexity algorithm, MISO downlink, Multiple-input single-output(MISO), Optimal Solution, Partial channel state information, Proportional Fair Scheduling, Throughput performance