Compressive sensing based channel estimation for NC-OFDM systems in cognitive radio context

Xue-yun HE; Rong-fang SONG; Ke-qin ZHOU

doi:1000-436X(2011)11-0085-10

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Compressive sensing based channel estimation for NC-OFDM systems in cognitive radio context

Papers | 更新时间：2024-06-05

- Compressive sensing based channel estimation for NC-OFDM systems in cognitive radio context
- Journal on Communications Vol. 32, Issue 11, Pages: 85-94(2011)
- 作者机构：
  
  1. 南京邮电大学通信与信息工程学院，江苏南京210003
  2. 东南大学移动通信国家重点实验室，江苏南京210096
- 作者简介：
- 基金信息：
- DOI：1000-436X(2011)11-0085-10
  CLC： TN911.23
- Online First：2011-11，
  
  Published：25 November 2011
- 稿件说明：
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Xue-yun HE, Rong-fang SONG, Ke-qin ZHOU. Compressive sensing based channel estimation for NC-OFDM systems in cognitive radio context[J]. Journal on Communications, 2011, 32(11): 85-94.
DOI：

Xue-yun HE, Rong-fang SONG, Ke-qin ZHOU. Compressive sensing based channel estimation for NC-OFDM systems in cognitive radio context[J]. Journal on Communications, 2011, 32(11): 85-94. DOI： 1000-436X(2011)11-0085-10.

摘要

提出了一种基于压缩感知（CS

compressive sensing）理论的不连续子载波正交频分复用（NC-OFDM

non-contiguous orthogonal frequency division multiplexing）系统信道估计新方法，全面研究了认知无线电NC-OFDM系统CS信道估计的理论框架、导频图案的设计、信道估计算法，并依据CS测量矩阵设计理论提出了测量矩阵互相关最小化的导频图案优化准则。仿真结果表明，同已有的NC-OFDM系统信道估计方法相比，CS信道估计能够在多种禁用子载波场景下，使用较少导频获得很好的信道估计性能。

Abstract

A new channel estimation based on compressive sensing(CS)in non-contiguous orthogonal frequency division multiplexing(NC-OFDM)system was proposed.As for NC-OFDM systems in cognitive radio context

the infrastructure of CS-based channel estimation

the design of pilot patterns and the algorithm of channel estimation were explored.Especially

a criterion of optimizing pilot pattern in the CS-based channel estimation was proposed by minimizing the mutual coherence of the measurement matrix in CS theory.Simulations show that

under many patterns of deactivated subcarriers

CS-based channel estimation obtains much better performance than existing NC-OFDM channel estimation methods in terms of the mean square error of the channel estimate as well as the bit error rate of the system.

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Keywords

references

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