Hybrid channel estimation for MIMO relay systems with D oppler offset influences

Summary The abundant benefits of Orthogonal Frequency‐Division Multiplexing and its high flexibility have resulted in its widespread applications in many telecommunication standards. One important parameter for improving wireless system's efficiency is the accurate estimation of channel state information. In the literatures, many techniques have been studied in order to estimate the channel state information. Nowadays, the techniques based on intelligent algorithms such as genetic algorithm and particle swarm optimization (PSO) have attracted attention of researchers. With a very low pilot overhead, these techniques are able to estimate the channel frequency response properly only using the received signals. Unfortunately, each of these techniques suffers a common weakness: they have a slow convergence rate. In this paper, a new intelligent and different method has been presented for channel estimation using learning automata, entitled LA estimator, where the learning automata are search agents, and each pair is responsible for searching 1 complex coefficient of the channel frequency response. This method can achieve an accurate channel estimation with a moderate computational complexity in comparison with GA and PSO estimators. Furthermore, with higher convergence rate, our proposed method is capable of providing the same performance as GA and PSO. For a 2‐path fast fading channel, simulation results demonstrate the robustness of our proposed scheme according to the bit error rate and the mean square error.

\overset{h}{true} ([],, k, n)

( k = 1,…, K ).…”

Section: System Modelmentioning

confidence: 99%

Channel estimation based on learning automata for OFDM systems

Salehi

Majidi

Neda

2018

“…For the case of perfect channel estimation, (18) can be further simplified into For the case of perfect channel estimation, (18) can be further simplified into…”

Section: Impacts Of Cfo and Channel Estimation Errors On Output Snrmentioning

confidence: 99%

“…Based on the advantages of the foregoing techniques, the integration of cooperative OFDM and the space-time block coding (STBC) 8 is convinced to be a powerful scheme for the physical layer of wireless communications. 18 In Thiagarajan et al, 19 a maximum likelihood (ML) estimation with reduced complexity is developed for the multiple CFOs and channel where cooperative communication systems with relays having a common source are considered. However, these benefits created by the combined system can be achieved only when both of perfect frequency synchronization and channel estimates are reached.…”

Section: Introductionmentioning

confidence: 99%

Analysis and design of joint CFO/channel estimate techniques for a cooperative STBC‐OFDM system

Lin

Hwang

2018

This paper studies the joint estimation technique of carrier frequency offset (CFO) and channel information for a distributed decode-and-forward (DF) cooperative space-time block-coded (STBC) orthogonal frequency division multiplexing (OFDM) system. For the considered relay system, we provide theoretical analysis of the effects upon the output signal-to-noise ratio (SNR), which is caused by the CFO/channel estimation error. Based on the provided analytical results, a joint CFO/channel estimation scheme is then developed, where the CFO estimate is achieved by a multiple-dimensional linear search algorithm. Furthermore, we propose an alternative estimation solution with iteration approach being designed for the CFO estimation prior to the channel estimation. In contrast to the former estimator, the iterative method enjoys the advantage of the substantially reduced implementation complexity without sacrificing the estimate performance. The conducted computer simulation results verify the effectiveness of the proposed schemes. KEYWORDS carrier frequency offset (CFO) and channel estimation, cooperative relaying, least square (LS), mean square error (MSE), orthogonal frequency division multiplexing (OFDM) Int J Commun Syst. 2019;32:e3845.wileyonlinelibrary.com/journal/dac

“…Karnik‐Mendel (KM) algorithm is a widely adopted type reduction method . In the KM algorithm, the smallest and largest values of the centroids of the embedded type‐1 fuzzy models are calculated in an iterative manner, and then the average of the two values is taken . However, this type of reduction approach is computationally extensive.…”

Section: Hybrid Interval Type‐2 Fuzzy Kalman Filtermentioning

confidence: 99%

Interval type‐2 fuzzy Kalman filter aided individual channel estimation in MIMO relay systems

Kaur

Khosla

Sarin

2018

Self Cite

Summary For a multiple input multiple output relay system, the overall system performance is dependent on the effectiveness of the channel estimation technique adopted. In real time, communicating nodes have Doppler offset influences associated with them owing to high mobility that largely affects the characteristics of underlying channels. Thus, for the complete characterisation of the channel under fast time varying fading conditions, the estimation of the Doppler offset influences along with the channel coefficients becomes inevitable. However, the combined estimation of the channel and the Doppler influences renders the overall estimation problem nonlinear. In literature, majority of the channel estimation methods assume that the Doppler offset influences are already known to the receiver node or nodes are assumed to be stationary. In this paper, a novel hybrid interval type‐2 fuzzy aided Kalman filter method is proposed for the nonlinear channel estimation problem in one‐way two‐hop multiple input multiple output relay system. This channel estimation issue is represented as a nonlinear state space model, and the proposed hybrid method that combines the merits offered by the interval type‐2 fuzzy interpolation and the Kalman filter approach is applied to address the issue. For type reduction, Nie‐Tan method is adopted which is a low computational load extension of the widely used Karnik‐Mendel approach. Furthermore, a computational complexity analysis has been performed. The proposed hybrid interval type‐2 fuzzy based Kalman filter approach shows good performance‐complexity trade off under fast time varying channel conditions for one‐way two‐hop multiple input multiple output relay system.