Structured Compressive Sensing-Based Spatio-Temporal Joint Channel Estimation for FDD Massive MIMO

Zhen Gao,Linglong Dai,Wei Dai,Byonghyo Shim,Zhaocheng Wang IEEE 2016 IEEE TRANSACTIONS ON COMMUNICATIONS Vol.64 No.2

<P>Massive MIMO is a promising technique for future 5G communications due to its high spectrum and energy efficiency. To realize its potential performance gain, accurate channel estimation is essential. However, due to massive number of antennas at the base station (BS), the pilot overhead required by conventional channel estimation schemes will be unaffordable, especially for frequency division duplex (FDD) massive MIMO. To overcome this problem, we propose a structured compressive sensing (SCS)-based spatio-temporal joint channel estimation scheme to reduce the required pilot overhead, whereby the spatio-temporal common sparsity of delay-domain MIMO channels is leveraged. Particularly, we first propose the nonorthogonal pilots at the BS under the framework of CS theory to reduce the required pilot overhead. Then, an adaptive structured subspace pursuit (ASSP) algorithm at the user is proposed to jointly estimate channels associated with multiple OFDM symbols from the limited number of pilots, whereby the spatio-temporal common sparsity of MIMO channels is exploited to improve the channel estimation accuracy. Moreover, by exploiting the temporal channel correlation, we propose a space-time adaptive pilot scheme to further reduce the pilot overhead. Additionally, we discuss the proposed channel estimation scheme in multicell scenario. Simulation results demonstrate that the proposed scheme can accurately estimate channels with the reduced pilot overhead, and it is capable of approaching the optimal oracle least squares estimator.</P>

Tensor-Based Channel Estimation Approach for One-Way Multi-Hop Relaying Communications

( Shuangzhi Li ),( Xiaomin Mu ),( Xin Guo ),( Jing Yang ),( Jiankang Zhang ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.12

Multi-hop relaying communications have great potentials in improving transmission performance by deploying relay nodes. The benefit is critically dependent on the accuracy of the channel state information (CSI) of all the transmitting links. However, the CSI has to be estimated. In this paper, we investigate the channel estimation problem in one-way multi-hop MIMO amplify-and-forward (AF) relay system, where both the two-hop and three-hop communication link exist. Traditional point-to-point MIMO channel estimation methods will result in error propagation in estimating relay links, and separately tackling the channel estimation issue of each link will lose the gain as part of channel matrices involved in multiple communication links. In order to exploit all the available gains, we develop a novel channel estimation model by structuring different communication links using the PARAFAC and PARATUCK2 tensor analysis. Furthermore, a two-stage fitting algorithm is derived to estimate all the channel matrices involved in the communication process. In particular, essential uniqueness is further discussed. Simulation results demonstrate the advantage and effectiveness of the proposed channel estimator.

셀룰라시스템에서 D2D 통신 전력제어

오창윤(Changyoon Oh) 한국컴퓨터정보학회 2018 韓國컴퓨터情報學會論文誌 Vol.23 No.8

In this paper, we investigate the impact of channel estimation error on the D2D power control algorithm. In the previous work, D2D power control algorithm has been proposed under the assumption that the channel between the transmitter and the corresponding receiver is perfectly estimated. In reality, the channel estimation error is more often the case. The first question is that the power control algorithm designed for perfect channel estimation is still valid under the channel estimation error environment ? The second question is , if it is not valid, what could be the possible remedy for the channel estimation error? In this paper, to answer the first question, we investigate the impact of the channel estimation error on the power control algorithm. We first review the D2D power control algorithm designed for perfect channel estimation. Then, we model the channel estimation error. Finally, we summarize the main results observed from the analysis of the simulation.

A Simple Sparse Channel Estimation Method for Single-Carrier Frequency Domain Equalization Based on Noise Space

Yuanhong Zhong,Yao Zhou,Qilun Lei 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.9

It is widely accepted that SC-FDE (Single-Carrier Frequency Domain Equalization) is an excellent candidate for broadband wireless systems. Channel estimation is one of the key challenges in SC-FDE, since accurate channel estimation can significantly improve the equalization at the receiver and consequently enhance the communication performances. In this paper, we proposed a simple sparse channel estimation method for SC-FDE system based on noise space, through sorting the results of the Least-squares (LS) channel estimation, channel tap locations and value are evaluated. The proposed system can realize channel estimation at a very low complexity, and simulation result shows that it can achieve significantly improved performance in frequency selective fading sparse channel.

고속 시변 채널 OFDM을 위한 저복잡도 LS 채널 예측의 성능 개선

임동민 대한전자공학회 2012 電子工學會論文誌-TC (Telecommunications) Vol.49 No.8

본 논문에서는 고속 시변 채널 OFDM을 위한 저복잡도 LS(Least Squares) 채널 예측의 성능 개선 방안을 제안한다. 저복잡도 LS 채널 예측을 위해 사용하는 CE-BEM(Complex Exponential-Basis Expansion Model) 채널 모델의 경우 채널 모델 자체의 문제점으로 인하여 채널 예측 성능 저하가 발생한다. 본 논문에서는 우선 시간 영역 윈도우를 이용하여 데이터 심볼에 의한 ICI(Interchannel Interference)의 영향을 제거한다. LS 채널 예측 결과에서 샘플을 취하여 윈도우의 영향을 제거한 후 특성이 채널 변화의 표현에 적합한 DPSS(Discrete Prolate Spheroidal Sequences)를 기저함수(basis function)로 하는 보간(interpolation) 방식으로 채널 응답을 복원하여 CE-BEM의 문제점을 해결한다. 컴퓨터 모의실험을 통한 성능 확인 결과 제안된 채널 예측 방식은 기존의 방식과 비교하여 특히 고속 시변 채널에서 우수한 성능 개선 효과를 보여주며, 선택된 기저함수의 형태뿐만 아니라 기저함수의 개수의 설정이 성능을 크게 좌우하는 또 다른 요소임을 확인하였다. In this paper, we propose a method for improving the performance of low complexity LS channel estimation for OFDM in fast time varying channels. The CE-BEM channel model used for the low complexity LS channel estimation has a problem on its own and deteriorates channel estimation performance. In this paper, we first use time domain windowing in order to remove the effect of ICI caused by data symbols. Then samples are taken from the results of the LS channel estimation and the effects of the windowing are removed from them. For resolving the defect of CE-BEM, the channel responses are recovered by interpolating the resultant samples with DPSS employed as basis functions the characteristics of which is well matched to the time variation of the channel. Computer simulations show that the proposed channel estimation method gives rise to performance improvement over conventional methods especially when channel variation is very fast and confirm that not only which type of functions is selected for the basis but how many functions are used for the basis is another key factor to performance improvement.

Sparsity Adaptive Expectation Maximization Algorithm for Estimating Channels in MIMO Cooperation systems

( Aihua Zhang ),( Shouyi Yang ),( Jianjun Li ),( Chunlei Li ),( Zhoufeng Liu ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.8

We investigate the channel state information (CSI) in multi-input multi-output (MIMO) cooperative networks that employ the amplify-and-forward transmission scheme. Least squares and expectation conditional maximization have been proposed in the system. However, neither of these two approaches takes advantage of channel sparsity, and they cause estimation performance loss. Unlike linear channel estimation methods, several compressed channel estimation methods are proposed in this study to exploit the sparsity of the MIMO cooperative channels based on the theory of compressed sensing. First, the channel estimation problem is formulated as a compressed sensing problem by using sparse decomposition theory. Second, the lower bound is derived for the estimation, and the MIMO relay channel is reconstructed via compressive sampling matching pursuit algorithms. Finally, based on this model, we propose a novel algorithm so called sparsity adaptive expectation maximization (SAEM) by using Kalman filter and expectation maximization algorithm so that it can exploit channel sparsity alternatively and also track the true support set of time-varying channel. Kalman filter is used to provide soft information of transmitted signals to the EM-based algorithm. Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.

주파수 선택적 채널에서의 OFDM 시스템을 위한 PSAM 채널 추정 기법의 성능 개선

김영수(Young Soo Kim),배정국(Jeong Gook Bae) 한국전자파학회 2012 한국전자파학회논문지 Vol.23 No.2

본 논문에서는 주파수 선택적 채널 환경의 OFDM 시스템에서 파일럿 심볼을 이용한 채널 추정 기법인 pilot Symbol Assisted Modulation(PSAM) 채널 추정 성능을 개선하는 방법을 제안한다. OFDM시스템에서는 채널 추정에 쓰이는 파일럿의 밀도가 적을수록 시스템의 유효 데이터량과 전력 효율이 증가되는 장점이 있다. 이를 위해 송신단에서는 채널 추정에 사용되는 파일럿의 수를 적게 사용하는 것이 좋다. 본 논문에서의 수신단에서는 인접한 파일럿 중간에 위치한 채널값이 먼저 추정된 후, 기존의 파일럿 값과 추정된 중간값을 사용하여 나머지 채널값을 추정한다. 그 후 채널의 최대 응답 길이를 고려하여 설계된 보호 구간의 길이를 이용하여 추정된 채널값의 오차를 줄여준다. 제안된 채널 추정 기법의 평균 제곱 오차(MSE) 성능은 기존의 PSAM 채널 추정 방법에 비해 신호대 잡음비 면에서 약 2 dB 정도의 개선 효과를 보여주었다. In this paper, we propose a method to improve performance of pilot symbol assisted modulation(PSAM) channel estimation method for OFDM systems over frequency selective channel. When channel values are estimated, the low pilot density used for channel estimation increases not only the effective data rate but also power efficiency. Thus, the lower pilot density which is used for channel estimation is better for OFDM system. At first, we estimate the channel values which are located at the middle of adjacent pilots, and then all of the possible channel values are estiamted by using original pilot values and previously estimated pilot values. Furthermore, the error of estimated channel values is reduced by introducing guard interval which is designed acccording to maximum channel delay. Performance achieved with the proposed method is illustrated by simulation experiments in comparison with the existing methods in terms of mean squared error(MSE).

Performance Evaluation of Pilotless Channel Estimation with Limited Number of Data Symbols in Frequency Selective Channel

Wang, Hanho The Korea Contents Association 2018 International Journal of Contents Vol.14 No.2

In a wireless mobile communication system, a pilot signal has been considered to be a necessary signal for estimating a changing channel between a base station and a terminal. All mobile communication systems developed so far have a specification for transmitting pilot signals. However, although the pilot signal transmission is easy to estimate the channel,(Ed: unclear wording: it is easy to use the pilot signal transmission to estimate the channel?) it should be minimized because it uses radio resources for data transmission. In this paper, we propose a pilotless channel estimation scheme (PCE) by introducing the clustering method of unsupervised learning used in our deep learning into channel estimation.(Ed: highlight- unclear) The PCE estimates the channel using only the data symbols without using the pilot signal at all. Also, to apply PCE to a real system, we evaluated the performance of PCE based on the resource block (RB), which is a resource allocation unit used in LTE. According to the results of this study, the PCE always provides a better mean square error (MSE) performance than the least square estimator using pilots, although it does not use the pilot signal at all. The MSE performance of the PCE is affected by the number of data symbols used and the frequency selectivity of the channel. In this paper, we provide simulation results considering various effects(Ed: unclear, clarify).

Research on Estimation Techniques for Rician Fading Multiple-Input and Multiple-Output Channels : A Theoretical Approach

Wenzhun Huang,Shanwen Zhang 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.3

In this paper, the performance of the single-estimation and multiple-estimation is investigated in multiple-input multiple-output (MIMO) Rician flat fading channels using the traditional least squares estimator and the Bayesian minimum mean square error estimator. In high-speed mobile environment, relatively severe channel conditions change, at this point, the sender is difficult to obtain more accurate of the instantaneous channel state information, for the implementation of adaptive MIMO transmission under this scenario. The MIMO techniques can be combined with space-time coding technique for coding diversity gain and also can use a simple multiplexing transmission in order to improve the transmission rate. The pseudo random sequence is certain, but it has many properties similar to that of the random binary data. Such as any two pseudo random sequence of cross correlation is small. In the research, we combine the basic theory of the state-of-the algorithm to propose our method. In the experimental part, we compare our method with other related state-of-the-art algorithms. The result proves the effectiveness and feasibility of the proposed method. In the near future, we plan to conduct more literature review and theoretical analysis to modify and optimize our current method.

Frequency Domain Channel Estimation for MIMO SC-FDMA Systems with CDM Pilots

Kim, Hyun-Myung,Kim, Dongsik,Kim, Tae-Kyoung,Im, Gi-Hong The Korea Institute of Information and Commucation 2014 Journal of communications and networks Vol.16 No.4

In this paper, we investigate the frequency domain channel estimation for multiple-input multiple-output (MIMO) single-carrier frequency-division multiple-access (SC-FDMA) systems. In MIMO SC-FDMA, code-division multiplexed (CDM) pilots such as cyclic-shifted Zadoff-Chu sequences have been adopted for channel estimation. However, most frequency domain channel estimation schemes were developed based on frequency-division multiplexing of pilots. We first develop a channel estimation error model by using CDM pilots, and then analyze the mean-square error (MSE) of various minimum MSE (MMSE) frequency domain channel estimation techniques. We show that the cascaded one-dimensional robust MMSE (C1D-RMMSE) technique is complexity-efficient, but it suffers from performance degradation due to the channel correlation mismatch when compared to the two-dimensional MMSE (2D-MMSE) technique. To improve the performance of C1D-RMMSE, we design a robust iterative channel estimation (RITCE) with a frequency replacement (FR) algorithm. After deriving the MSE of iterative channel estimation, we optimize the FR algorithm in terms of the MSE. Then, a low-complexity adaptation method is proposed for practical MIMO SC-FDMA systems, wherein FR is performed according to the reliability of the data estimates. Simulation results show that the proposed RITCE technique effectively improves the performance of C1D-RMMSE, thus providing a better performance-complexity tradeoff than 2D-MMSE.