ISSN 1000-1239 CN 11-1777/TP

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庞 迪1,2 周继华3 胡金龙1 董江涛1 石晶林1,2   

  1. 1(中国科学院计算技术研究所 北京 100190) 2(中国科学院研究生院 北京 100049) 3(重庆金美通信有限责任公司 重庆 400030) (
  • 出版日期: 2009-11-15

Uplink Resource Allocation in Wireless MIMO Systems

Pang Di1,2, Zhou Jihua3, Hu Jinlong1, Dong Jiangtao1, and Shi Jinglin1,2   

  1. 1(Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190) 2(Graduate University of Chinese Academy of Sciences, Beijing 100049) 3(Chongqing Jinmei Communication Co., Ltd., Chongqing 400030)
  • Online: 2009-11-15

摘要: 在存在同信道干扰的无线MIMO系统中,为具有多种QoS需求的调度业务分配资源是一个具有挑战性的问题.提出一种实用的、基于SDMA的贪婪资源分配(SGRA)算法.在高效的干扰管理基础上,SGRA算法可以执行两阶段启发式计算和搜索.在第1阶段,包括上行调度和子信道分配的贪婪资源分配首先在时域-频域二维进行;在第2阶段,资源分配被扩展到时域-频域-空域三维进行.SGRA的算法复杂度低,适用于实际无线通信系统.仿真结果表明,与同类算法相比,SGRA算法可以提高系统吞吐量,更好地保证实时业务的时延和最小数据速率需求,同时兼顾系统公平性.

关键词: 低复杂度, 上行链路, 资源分配, 多输入多输出, 正交频分多址, 空分多址

Abstract: Multiple input multiple output (MIMO) technologies can improve spectrum efficiency, and are considered to be one of the core technologies in future wireless communication systems. In a wireless MIMO system taking into account co-channel interference (CCI), resource allocation for scheduling services with multiple QoS requirements is a challenging problem. The CCI suppression, bandwidth and slot allocation problem in the uplink of a MIMO system are studied in this paper. Regarding the improvement of system throughput as an optimization target and QoS requirements and system fairness as constraints, the authors propose a practical SDMA-based greedy resource allocation (SGRA) algorithm. Based on interference management, CCI can be efficiently suppressed and the complicated problem with multiple constraints can be decomposed. Then a two-phase heuristic calculation and searching is carried out in SGRA. In the first phase, greedy resource allocation, primarily involving uplink scheduling and subchannel allocation, is performed in the time-frequency domain. In the second phase, the resource allocation is extended to the space-time-frequency domain. SGRA has low complexity and is applicable to practical wireless communication systems. Simulation results show that compared with conventional algorithms, SGRA can improve system throughput, and better guarantee delay and minimum data rate requirements of real-time services, while at the same time giving consideration to system fairness.

Key words: low complexity, uplink, resource allocation, MIMO, OFDMA, SDMA