CAJ | 학술논문

在多输入多输出正交频分复用(MIMO-OFDM)系统中,信号经过频率选择性衰落的信道后,在接收端需要进行均衡和相干信号的检测,故准确的信道估计量必不可少.传统的信道估计方法均基于信道抽头是密集型的假设,利用线性重构算法,如最小二乘(LS)或最小均方误差(MMSE)等,可以达到Cramer-Rao下界(CRLB).然而,通过物理信道测量发现,在实际通信系统中,宽带信道抽头分布通常表现出稀疏特性.通过充分利用信道的稀疏特性,该文将压缩感知中的CoSaMP重构算法应用于MIMO-OFDM系统的稀疏多径信道估计.在达到与传统的信道估计方法相同性能的前提下,基于CoSaMP的信道估计方法以非常小的计算复杂度为代价,大大减少了导频信号开销,从而提高了频谱资源利用率.
재다수입다수출정교빈분복용(MIMO-OFDM)계통중,신호경과빈솔선택성쇠락적신도후,재접수단수요진행균형화상간신호적검측,고준학적신도고계량필불가소.전통적신도고계방법균기우신도추두시밀집형적가설,이용선성중구산법,여최소이승(LS)혹최소균방오차(MMSE)등,가이체도Cramer-Rao하계(CRLB).연이,통과물리신도측량발현,재실제통신계통중,관대신도추두분포통상표현출희소특성.통과충분이용신도적희소특성,해문장압축감지중적CoSaMP중구산법응용우MIMO-OFDM계통적희소다경신도고계.재체도여전통적신도고계방법상동성능적전제하,기우CoSaMP적신도고계방법이비상소적계산복잡도위대개,대대감소료도빈신호개소,종이제고료빈보자원이용솔.
Channel equalization and coherent detection require accurate channel state information (CSI) at the receiver for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. The conventional linear recovery methods, such as least squares (LS) and minimum mean square error (MMSE), are widely adapted in channel estimation under the assumption of rich multipath. However, numerous physical measurements have verified that the practical multipath channels tend to exhibit sparse structures. In this paper, exploiting the channel sparsity, we propose a compressive sensing-based CoSaMP recovery algorithm for MIMO-OFDM sparse channel estimation. Simulations show that the compressive sensing estimation method can obtain the accurate CSI with fewer pilots than conventional linear estimation for MIMO-OFDM systems at the cost of less computational complexity. The proposed method can greatly improve the spectrum efficiency for MIMO-OFDM systems.