吉林大学学报(工学版)

• • 上一篇    下一篇

一种OFDM系统的自适应配置干扰抵消方法

刘召伟,沈瑞静,王宗欣   

  1. 复旦大学 通信工程系,上海 200433
  • 收稿日期:2006-02-26 修回日期:2006-09-20 出版日期:2007-01-01 发布日期:2007-01-01
  • 通讯作者: 王宗欣

Adaptive allocation MPIC algorithm for multi-carrier system

Liu Zhao-wei,Shen Rui-jing,Wang Zong-xin   

  1. Department of Communication Science and Engineering,Fudan University,Shanghai 200433,China

  • Received:2006-02-26 Revised:2006-09-20 Online:2007-01-01 Published:2007-01-01
  • Contact: Wang Zong-xin

摘要: 分析了目前OFDM系统中当信道时延大于保护间隔时,采用信道压缩方法后
存在的问题,指出了信道压缩后目标信道某些频点产生深衰落的可能性,提出了一种
OFDM传输系统中双重自适应配置的多径干扰抵消方法。通过自适应配置与信道压缩相结合
的方法克服了压缩后由目标信道频率深衰落产生的较低信噪比的子载波在频域均衡时的影
响,在减少系统保护间隔开销的同时进一步改善了误码率;通过蒙特卡洛(MONTE CARLO
)方法在无线信道条件下对算法进行了模拟,模拟结果显示该方法能有效改善系统性能。

关键词: 自适应配置, 多径干扰抵消, 时域均衡, 循环前缀保护间隔

Abstract: The problem of Time Domain Equalization (TEQ) in multi-carrier system when channel spread time is longer than guard interval was analyzed, and the probability of heavy-fading in some sub-carriers in target channel after channel shortening was given. A new doubly Adaptive Allocation Multi-path Interference canceller (AL-MPIC) algorithm for multi-carrier system combating lower SNR frequency effect of heavy-fading sub-channels caused from channel shortening was proposed. The method combining the TEQ and adaptive allocation is not only able to suppress Cyclic Prefix Guard Interval (CP-GI) but also to improve system BER performance. The simulations of the algorithm under wireless channel condition using MONTE CARLO method were presented and show the effective improvement of the system performance.

Key words: communication, orthogonal frequency division multiplexing (OFDM), adaptive allocation (AL), multi-path interference canceller (MPIC), time domain equalization (TEQ), cyclic prefix guard interval (CP-GI)

中图分类号: 

  • TN911.4
[1] 应文威, 欧勇恒, 蒋宇中, 张伽伟, 陈聪. 新型自适应非高斯接收机设计[J]. 吉林大学学报(工学版), 2013, 43(06): 1685-1689.
[2] 张成文;张中兆;马永奎 . 基于多用户空间相关性的MIMOOFDM 下行链路资源分配[J]. 吉林大学学报(工学版), 2008, 38(03): 719-0725.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!