Influence Of Channel Estimation Error Research Articles

Deep Expectation-Maximization for Joint MIMO Channel Estimation and Signal Detection

To overcome the influence of channel estimation error on signal detection, this paper presents a model-driven deep learning method for joint channel estimation and signal detection in multiple-input multiple-output (MIMO) wireless communication systems. To improve the robustness of the method, we use the Student's <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</i> -distribution to model the environment noise, and model the joint problem probabilistically by taking the channel state information (CSI) as a latent variable, then derive a generalized expectation maximization (GEM) algorithm to fit the model. In GEM, the expectation step is used for robust CSI estimation while the maximization step detects the transmitted signal with the estimated CSI. To reduce the computational complexity of GEM, we unfold it into a deep neural network. The network contains only a few trainable parameters, which is easy to train and has low space complexity. Based on our experimental results, we find that the proposed GEM algorithm outperforms a variety of signal detection algorithms which take the CSI estimation and signal detection as independent modules. Further, we find empirically that the proposed GEM network outperforms state-of-the-art deep learning based joint channel estimation and signal detection methods and has a good generalization ability against the number of antennas, the modulation mode, the level of signal-to-noise ratio and channel correlation.

Secure Performance of Cooperative System with Channel Estimation Error

Traditional two-hop and multiple relaying and forwarding cooperative communication system, in the presence of illegal eavesdropping users, the secure transmission of system information relies on the acquisition of instantaneous channel state information to a great extent. Due to the broadcasting and time variability of wireless channel, it is almost impossible to obtain instantaneous channel state information. In view of this problem, this paper uses partial relay selection as the selection criterion, taking the security outage probability and security capacity as reference basis, the simulation verifies the influence of channel estimation error on the secure performance of the cooperative system.

Linear Pre-coding Base on Imperfect CSI in Massive MIMO

The estimation of channel state information at the base station in large scale MIMO system directly affects the design of downlink pre-coding matrix and affects the performance of the system. Aiming at the problem of Rayleigh fading channel and Rician Fading Channel estimation error, this paper firstly studies the influence of channel estimation error on the system, and then designs the pre-coding matrix based on the minimum mean square error criterion. The simulation results show that the proposed algorithm is superior to the traditional pre-coding algorithm.

Power Amplifier Energy Efficiency Enhancement via Adaptive Polarization-QAM Modulation Scheme in OFDM Systems

In this paper, an adaptive polarization-QAM modulation (APQAM) scheme is proposed to improve the power amplifier (PA) energy efficiency (EE) in orthogonal frequency division multiplexing (OFDM) systems. Since we found that polarization modulation (PM) has better EE performance than QAM in the nonlinear region of PA while QAM outperforms PM in the linear region, we can combine these two modulation schemes together and adjust their modulation orders adaptively to obtain higher EE performance. First, a truncated Taylor series model is used to represent PA nonlinearity, so the effects of both the in-band distortions and the out-of-band emissions on the OFDM signals can be analyzed. Second, two APQAM algorithms are investigated in both AWGN channel and depolarization channel with power-dependent loss. Furthermore, symbol error rate performance of the APQAM scheme is obtained in different channel conditions, and the influence of channel estimation error is analyzed to testify the robustness of the proposed APQAM scheme. Simulation results show that, if perfect channel state information is obtained, the EE of the proposed scheme is nearly 50% more than that of the traditional QAM scheme in OFDM systems.

Performance of Open-Loop Transmit Diversity with Intra-Subframe Frequency Hopping and Iterative Decision-Feedback Channel Estimation for DFT-Precoded OFDMA

Open-loop (OL) transmit diversity is more subject to the influence of channel estimation error than closed-loop (CL) transmit diversity, although it has the merit of providing better performance in fast Doppler frequency environments because it doesn't require a feedback signal. This paper proposes an OL transmit diversity scheme combined with intra-subframe frequency hopping (FH) and iterative decision-feedback channel estimation (DFCE) in a shared channel for discrete Fourier transform (DFT)-precoded orthogonal frequency division multiple access (OFDMA). We apply intra-subframe FH to OL transmit diversity to mitigate the reduction in the diversity gain under high fading correlation conditions among antennas and iterative DFCE to improve the channel estimation accuracy. Computer simulation results show that the required average received signal-to-noise power ratio at the average block error rate (BLER) of 10-2 of the space-time block code (STBC) with intra-subframe FH is reduced to within approximately 0.8dB compared to codebook-based CL transmit diversity when using iterative DFCE at the maximum Doppler frequency of fD =5.55Hz. Moreover, it is shown that STBC with intra-subframe FH and iterative DFCE achieves much better BLER performance compared to CL transmit diversity when fD is higher than approximately 30Hz since the tracking ability of the latter degrades due to the fast fading variation in its feedback loop.

Analysis of the Performance of the Two-way Relaying under the Influence of Channel Estimation Error and Co-channel Interference

In this paper, the performance of the two-way relaying under the influence of channel estimation error and co-channel interference is analyzed. At the very beginning, based on the expression of the received signal-to-interference-plus-noise ratio (SINR), we work out the cumulative probability distribution function and the exact closed-form and approximate expressions of the outage probability. Then, we further derive the bit error rate (BER) of system. Finally, in order to reduce the impact of channel estimation error and interference on the system, we propose an appropriate power allocation scheme to reach a compromise between the outage probabilities of the two terminals. Our theoretical analysis is justified by the result of numerical simulation.

Channel estimation algorithms for cooperative spectrum sensing in amplify‐and‐forward cooperative system

ABSTRACTIn amplify‐and‐forward (AF)‐based cooperative spectrum sensing system, the bit‐error‐rate (BER) performance and detection probability will decrease because of the existence of channel estimation error. In this paper, the influence of channel estimation error on system performance is firstly deduced, and then, linear minimum mean‐square error (LMMSE) channel estimation algorithm with filtering delay time‐domain windowing (LMMSE‐filtering‐DTW) technique and modified singular value decomposition‐based LMMSE algorithm are proposed to improve the channel estimation performance for code division multiple access system and orthogonal frequency division multiplexing system in AF cooperative scenario, respectively. Simulation results verify the effectiveness of the two proposed channel estimation algorithms in cooperative spectrum sensing, and when Eb/ N0 is bigger than 20 dB, given the required false alarm probability smaller than 15%, the difference of detection probability between the channel obtained using the proposed channel estimation algorithms and the ideal channel is less than 2.5%, respectively. Copyright © 2012 John Wiley &amp; Sons, Ltd.

Improved SISO MMSE Detection for Joint Coded-Precoded OFDM under Imperfect Channel Estimation

An improved soft-input soft-output (SISO) minimum mean-squared error (MMSE) detection method is proposed for joint coding and precoding OFDM systems under imperfect channel estimation. Compared with the traditional mismatched detection which uses the channel estimate as its exact value, the signal model of the proposed detector is more accurate and the influence of channel estimation error (CEE) can be effectively mitigated. Simulations indicate that the proposed scheme can improve the bit error rate (BER) performance with fewer pilot symbols.

A Virtual Channel-Based Approach to Compensation of I/Q Imbalances in MIMO-OFDM Systems

Multiple-input multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) scheme has been considered as the most promising physical-layer architecture for the future wireless systems to provide high-speed communications. However, the performance of the MIMO-OFDM system may be degraded by in-phase/quadrature-phase (I/Q) imbalances caused by component imperfections in the analog front-ends of the transceivers. I/Q imbalances result in inter-carrier interference (ICI) in OFDM systems and cause inaccurate estimate of the channel state information (CSI), which is essential for diversity combining at the MIMO receiver. In this paper, we propose a novel approach to analyzing a MIMO-OFDM wireless communication system with I/Q imbalances over multi-path fading channels. A virtual channel is proposed as the combination of multi-path fading channel effects and I/Q imbalances at the transmitter and receiver. Based on this new approach, the effects of the channel and I/Q imbalances can be jointly estimated, and the influence of channel estimation error due to I/Q imbalances can be greatly reduced. An optimal minimal mean square error (MMSE) estimator and a low-complexity least square (LS) estimator are employed to estimate the joint coefficients of the virtual channel, which are then used to equalize the distorted signals. System performance is theoretically analyzed and verified by simulation experiments under different system configurations. The results show that the proposed method can significantly improve system performance that is close to the ideal case in which I/Q are balanced and the channel state information is known at the receiver.

Influence of Channel Estimation Error on MIMO Multiplexing Using Precoding in Downlink OFDM Radio Access

This paper investigates the influence of channel estimation error on the precoding matrix selection and signal detection for MIMO multiplexing using precoding in the downlink OFDM radio access. In a simulation, we assume codebook-based unitary precoding and signal detection that employs a minimum mean squared error (MMSE) based interference suppression filter. The simulation results clarify the effect of the channel estimation error with respect to the precoding matrix selection and signal detection from the viewpoints of the number of streams, i.e., rank order, the number of transmit antennas, the modulation scheme and channel coding rate, and codebook size, i.e., quantization for precoding matrix feedback information.

Influence of channel estimation error on layered space-time receivers

The performance limitation due to imperfect channel estimation in a layered space-time (BLAST) receiver is addressed. For the performance evaluation, the effective signal-to-interference ratio and average bit error rate expressions of zero forcing VBLAST systems with unordered successive cancellation are derived taking into account the effect of imperfect channel information.