部分信道状态信息下MIMO-OFDM的跨层资源分配算法

计算机应用 ›› 2012, Vol. 32 ›› Issue (05): 1211-1216.

部分信道状态信息下MIMO-OFDM的跨层资源分配算法

黄玉清¹,李城鑫²,李强¹

1. 西南科技大学信息工程学院，四川绵阳 621010
2. 西南科技大学信息工程学院，四川绵阳621010

收稿日期:2011-10-08 修回日期:2011-12-04 发布日期:2012-05-01 出版日期:2012-05-01
通讯作者: 黄玉清
作者简介:黄玉清(1962-)，女，四川绵阳人，教授，主要研究方向：认知无线电、信息处理、人工智能；李城鑫(1984-)，男，四川广安人，博士研究生，主要研究方向：无线通信、正交频分复用；李强(1982-)，男，四川资阳人，副教授，博士，主要研究方向：信号检测与分析、无线测控。
基金资助:
国家自然科学基金资助项目(61072046);四川省科技厅资助项目（2010jy0173）

Cross-layer resource allocation algorithm of MIMO-OFDM systems with partial channel state information

HUANG Yu-qing,LI Cheng-xin,LI Qiang

School of Information Engineering, Southwest University of Science and Technology, Mianyang Sichuan 621010, China

Received:2011-10-08 Revised:2011-12-04 Online:2012-05-01 Published:2012-05-01
Contact: HUANG Yu-qing

摘要/Abstract

摘要： 针对跨层多用户多输入多输出-正交频分复用（MIMO-OFDM）系统，以系统最大吞吐量为目标，给出一种基于部分信道状态信息的跨层资源分配算法。该优化问题设计的目标函数包括功率限制、传输速率、子载波占用、不同业务的服务质量需求与数据链路层的队列状态信息等约束条件。在数据链路层存在有限缓存条件下，通过均值反馈模型描述信道状态信息的反馈过程，推导出相应的跨层资源分配准则。仿真结果表明，所提算法与现有方案相比，满足了不同业务用户的QoS要求，并获得了好的吞吐率，降低了丢包率。

关键词: 多输入多输出-正交频分复用, 均值反馈模型, 跨层资源分配, 信道状态信息, 服务质量

Abstract: Cross-layer design is an effective technique for future mobile communication systems. A cross-layer resource allocation algorithm with partial channel state information was explored to maximize the total system throughput for multi-user MIMO-OFDM （Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing） system. The objective function of the optimization problem was designed based on the power limitation constraint, transmission rate, average queue length and sub-carrier occupancy, Quality of Service (QoS) requirements of different services and queue state information of data link layer. Under the condition of finite-length user buffer in data link layer, the mean feedback model was utilized to describe the feedback process of channel state information, and then the corresponding cross-layer resource allocation criteria could be derived. The simulation results show that compared with the existing schemes, the proposed algorithms obtain reasonable throughput performance and reduce lost package rate while providing better QoS requirement for each user of different services.

Key words: Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM), mean feedback model, cross-layer resource allocation, Channel State Information (CSI), Quality of Service (QoS)

中图分类号:

TN929.5

黄玉清李城鑫李强. 部分信道状态信息下MIMO-OFDM的跨层资源分配算法[J]. 计算机应用, 2012, 32(05): 1211-1216.

HUANG Yu-qing LI Cheng-xin LI Qiang. Cross-layer resource allocation algorithm of MIMO-OFDM systems with partial channel state information[J]. Journal of Computer Applications, 2012, 32(05): 1211-1216.

参考文献

［1］SUN QIAOYUN, TIAN HUI, DONG KUN, et al. Cross layerscheduling for real-time traffic in multiuser MIMO-OFDMA systems［J］.The Journal of China University of Posts and Telecommunications, 2009, 16(3): 24-29.

［2］SUN QIAOYUN, TIAN HUI, WANG SHUANG, et al. Novel resource allocation algorithms for multiuser downlink MIMO-OFDMA of FuTURE B3G systems［J］. Progress in Natural Science, 2009, 19 (9): 1141-1146.

［3］XU ZHIQIANG, ZHAI MINGYUE, LU JUN. Crosslayer optimization of user scheduling and resource allocation in power-line communication systems［J］. IEEE Transactions on Power Delivery, 2011, 26(3): 1449-1458.

［4］李强，李城鑫，黄玉清，等.相关信道下基于多用户STBC-OFDM系统的子载波分配［J］. 计算机应用, 2011, 31(7): 1948-1952.

［5］LIN QINGWEN, WANG XIN, GIANNAKIS G B. A cross-layer scheduling algorithm with QoS support in wireless networks［J］. IEEE Transactions on Vehicular Technology, 2006, 55(3): 839-847.

［6］SONG GUOCONG， LI YE. Cross-layer optimization for OFDM wireless networks-partⅡ: algorithm development［J］. IEEE Transactions on Wireless Communication, 2005, 4(2): 625-634.

［7］KANEKO M, POPOVSKI P, DAHL J. Proportional fairness in multi-carrier system: upper bound and approximation algorithms［J］. IEEE Communications Letters, 2006, 10 (6): 462-464.

［8］惠毅, 周志杰, 张文强，等. 一种基于业务优先级的跨层资源分配算法［J］. 系统仿真学报, 2009, 21(17): 5391-5395.

［9］ZHOU SHENGLI, GIANNAKIS G B. Optimal transmitter eigen-beamforming and space-time block coding based on channel mean feedback［J］. IEEE Transactions on Signal Processing, 2002, 50(10): 2599-2613.

［10］HORN R A, JOHNSON C R, Matrix analysis［M］. Cambridge, UK: Cambridge University Press, 1985: 167-256.

［11］GOLDSMITH A. Wireless communications ［M］. Cambridge, UK: Cambridge University Press, 2005: 299-326, 116-153.

［12］WONG I C, SHEN Z, EVANS B L, et al. A low complexity algorithm for proportional resource allocation in OFDMA systems［C］// IEEE International Signal Processing Systems Workshop. Washington, DC: IEEE Computer Society, 2004: 1-6.

［13］SONG GUOCONG. Cross-layer resource allocation and scheduling in wireless multicarrier networks［D］. Atlanta: Georgia Institute of Technology, 2005.

［14］XIA PENGFEI, ZHOU SHENGLI, GIANNAKIS G B. Adaptive MIMO-OFDM based on partial channel state information［J］. IEEE Transactions on Signal Processing, 2004, 52(1): 202-213.

［15］ITU-R. M.1225 Guideline for evaluation of radio transmission technologies for IMT-2000［S］. Geneva, International Telecommunications Union, 1997.

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