Channel Estimation for Time-Varying MIMO Relay Systems

Chiong, Choo W. R.; Rong, Yue; Xiang, Yong

doi:10.1109/twc.2015.2459700

Cited by 20 publications

(8 citation statements)

References 29 publications

(41 reference statements)

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“…In this section, some of the existing channel estimation approaches for the MIMO relay system are discussed. In Zhang et al 10 and Chiong et al, 13,14 the time-varying channel behavior is represented as a basis exponential model, where the time invariant coefficients modify the superimposed basis functions used for representing the channel variations. 10 For a high-mobility OFDM relay system with time-varying fading, a time frequency model was adopted 11 to estimate the time-varying channels.…”

Section: Related Workmentioning

confidence: 99%

“…12 But both 11,12 only compute the estimates of the composite channel and not the individual channels. In Zhang et al 10 and Chiong et al, 13,14 the time-varying channel behavior is represented as a basis exponential model, where the time invariant coefficients modify the superimposed basis functions used for representing the channel variations. A complex-exponential basis expansion model approach based on Fourier bases to represent the individual time-varying channels was considered to solve the channel estimation problem in a time-varying scenario in Wang et al 15 In Zhang et al, 16 the Bayesian Cramér-Rao lower bounds for individual channel estimates for a time-varying amplify-and-forward (AF) relay network are derived.…”

Section: Related Workmentioning

confidence: 99%

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Hybrid channel estimation for MIMO relay systems with Doppler offset influences

Kaur

Khosla

Sarin

2017

Int J Communication

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The design of the channel estimation method in a multiple-input multiple-output (MIMO) relay system plays a highly crucial role in deciding the overall system performance. For the realistic scenarios specifically, with fast time-varying channel conditions due to highly mobile communicating nodes, the degree of accuracy to which the channel estimates are obtained for MIMO relay systems influences the communication system reliability significantly. However, most of the channel estimation approaches proposed in literature for MIMO relay systems assume that the Doppler offset contributed by highly mobile nodes is already known to the receiver, ignoring the resulting nonlinear system dynamics. Hence, a novel hybrid algorithm is proposed to address the issue of timevarying channel estimation under fast-fading channel condition with Doppler offset influences contributed by high-mobility communicating nodes for a 1way 2-hop MIMO amplify-and-forward relaying system. The problem is first formulated as a nonlinear state-space model, and then an algorithm is developed to estimate the individual source-to-relay and relay-to-destination channels in the presence of the associated dynamic Doppler offset. In the proposed method, a set of superimposed orthogonal pilots is used for aiding in the updation of the channel gains, since Kalman filter-based updation may lead to accumulation of estimation and prediction error. A detailed computational complexity analysis of the proposed hybrid algorithm is presented, which shows that the algorithm has moderate computational complexity with a good performance in fast time-varying channel conditions with high node mobility in a dual-hop MIMO relay system. KEYWORDS channel estimation, Doppler offset, Kalman filter, multiple-input multiple-output (MIMO) relay system, Takagi-Sugeno (T-S) fuzzy model | INTRODUCTIONTo improve the network coverage and power efficiency of a multiple-input multiple-output (MIMO) communication system, 1 relay nodes are added between the source-destination pair. The concept of relaying was first introduced by van der Meulen. 2 Because of the numerous advantages such as reducing the effects of path loss and shadowing 3-6 offered by relays, this study has gained a lot of momentum in research recently. To reap the aforementioned benefits that

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Hybrid channel estimation for MIMO relay systems with Doppler offset influences

Kaur

Khosla

Sarin

2017

Int J Communication

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“…To capture the rapid variation of ψ k,q (n)'s, the complex componential basis expansion model (CE-BEM) [3] is applied in this paper so that during any time interval of N T s , ψ k,q (n)'s can be modeled as [7], [8]…”

Section: A System Modelmentioning

confidence: 99%

Spatial-Temporal BEM and Channel Estimation Strategy for Massive MIMO Time-Varying Systems

Xie

Gao

Zhang

et al. 2016

2016 IEEE Global Communications Conference (GLOBECOM)

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This paper proposes a new channel estimation scheme for the multiuser massive multiple-input multiple-output (MIMO) systems in time-varying environment. We introduce a discrete Fourier transform (DFT) aided spatial-temporal basis expansion model (ST-BEM) to reduce the effective dimensions of uplink/downlink channels, such that training overhead and feedback cost could be greatly decreased. The newly proposed ST-BEM is suitable for both time division duplex (TDD) systems and frequency division duplex (FDD) systems thanks to the angle reciprocity, and can be efficiently deployed by fast Fourier transform (FFT). Various numerical results have corroborated the proposed studies. Index Terms-Massive MIMO, spatial-temporal BEM, DFT, DOA, angle reciprocity.

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“…The research has then continued into full-duplex ones (for even more spectrally efficient systems) [8], [9] and expanded to relaying with Massive MIMO (MMIMO) [10] and cloud based multi-way MIMO TWRNS [11]. Distributed beamforming [12], energy efficiency of millimeter-wave TWRNs [13] and time-varying MIMO dual hop relay (though onedirectional) channel estimation [14] have also been investigated. One advantage of TWRN AF protocol is that no signal processing is required at the relay (R) node, in that R just amplifies its received signal signal and transmits it to both the terminal nodes T 1 , T 2 .…”

Section: Introductionmentioning

confidence: 99%

Novel blind full multipath Two Way Relay Network (TWRN), OFDM channel estimation using Machine Learning

De¹

2023

Preprint

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Most two way relay network (TWRN) half-duplex channel estimation algorithms have been developed for single path channels, except for those in frequency domain OFDM systems. We derive a novel time-domain, blind Maximum A posteriori Probability (MAP) estimation method for multipath estimation in TWRN OFDM systems. Since a TWRN half-duplex system is a cascade of two/more bidirectional transmission systems, there are multiple forward and reverse, individual, as well as composite/cascade (of two individual) channels (unlike only one channel in traditional transmission). The situation is further complicated in the case of multipath channels. Additionally, TWRN systems suffer from having noise components at different nodes, including colored (non-white) at the receiver terminal node. Thus most recent research works concentrate on the easier task of estimating single-path (flat frequency) channels, that too by pilot-based, and sometimes, even by suboptimal least squares (LS) methods. However, in this paper, forward, composite/individual mulipath channel estimators developed are semiblind (for enhanced spectral efficiency), and which turn out to be nonlinear. Moreover, an unique "Factor Analysis Alternating Maximization" method (used in psychometrics and some Machine Learning (MLe) applications, but not in signal processing, communication/TWRN systems), is used, in a novel manner, to overcome the colored noise problem, allowing one to derive novel, closed-form, analytical expressions for reverse individual channel h estimation, (with its convergence provided), which is unavailable in existing literature. Non-trivial Cramer Rao bounds have also been derived for these novel multipath channel estimators. Comprehensive simulation results show the novel forward, reverse, composite and individual channel estimation methods perform much better than the existing ones.

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Channel Estimation for Time-Varying MIMO Relay Systems

Cited by 20 publications

References 29 publications

Hybrid channel estimation for MIMO relay systems with Doppler offset influences

Hybrid channel estimation for MIMO relay systems with Doppler offset influences

Spatial-Temporal BEM and Channel Estimation Strategy for Massive MIMO Time-Varying Systems

Novel blind full multipath Two Way Relay Network (TWRN), OFDM channel estimation using Machine Learning

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