Hua Yu

Bio: Hua Yu is an academic researcher from Central China Normal University. The author has contributed to research in topics: MIMO & Antenna (radio). The author has an hindex of 3, co-authored 4 publications receiving 42 citations.

The MMSE Channel Estimation Based on DFT for OFDM System

Abstract: The minimum mean-square error (MMSE) channel estimation has well performance but higher complexity than least-square (LS) channel estimation, specially it requires the channel statistical properties including the channel autocorrelation matrix and the noise variance. However, it is difficult to obtain the channel statistical properties in practice. In this paper, through the DFT based estimator, in time domain, the noise variance can be estimated, and the channel autocorrelation matrix is also obtained by using the noise suppressed channel impulse response. Then the MMSE channel estimation for OFDM system is realized. Simulation results demonstrate that the performance is better than the DFT based estimator and closed to the ideal MMSE estimator.

Exact BER Expression for Alamouti Scheme with Joint Transmit and Receive Antenna Selection

Abstract: In this paper, we propose a simple joint transmit and receive antenna selection algorithm based on maximizing the instantaneous signal to noise ratio (SNR) over uncorrelated Rayleigh fading channels in multi-input multi-output (MIMO) systems. For a special case that two transmit antennas and one receive antenna are selected, while Alamouti scheme is employed, the exact bit error rate (BER) expression for binary phase shift keying (BPSK) is derived. The analytical results are exactly verified by the simulations.

Adaptive Power Allocation for Decode-and-Forward MIMO-OFDM Relay System

Abstract: In this paper, a two-hop MIMO-OFDM relay system with a decode-and-forward (DF) relay is considered, in which each terminal is equipped with multiple antennas. With the goal of maximizing the instantaneous capacity, a suboptimal power allocation algorithm under the total transmit power constraint is proposed. Since the independence of fading channel during each hop, subcarrier pairing strategy is given to further improve the system capacity. The simulation results show that the proposed suboptimal power allocation algorithm in this paper achieves a higher capacity than the uniform power allocation, and that subcarrier paring is an effective way to enhance the system capacity.

Capacity Bounds for Joint Transmit and Receive Antenna Selection Systems with Correlated Fading Channels

Abstract: In this paper, we investigate the capacity for antenna selection systems in the spatial correlated Rayleigh fading channels. Antenna selection is performed both at the transmitter and receiver, one transmit antenna is selected from N transmit antennas and m receive antennas are selected from M receive antennas. Upper and lower bounds of the capacity are derived. For a special antenna selection system in which one transmit antenna and two receive antennas are selected, the exact forms of the upper bound and lower bound are given . The simulation results show that both upper bound and lower bound are tight with the ergodic capacity and the exact form of the bounds fits the Monte Carlo results exactly.

Analysis of Levenberg-Marquardt and Scaled Conjugate gradient training algorithms for artificial neural network based LS and MMSE estimated channel equalizers

Abstract: Multilayer perceptron (MLP) based artificial neural network (ANN) equalizers, deploying back propagation (BP) training algorithm, have been profusely used for equalization earlier. However this algorithm suffers from slow convergence rate, depending on the size of network. In this paper, Levenberg-Marquardt and Scaled Conjugate algorithms are proposed to train an MLP based ANN for least square (LS) and minimum mean square (MMSE) estimated channel coefficients using MPSK and MQAM modulation techniques. The key analytical performance measures are comprehended in terms of three parameters i.e regression, validation and training state. Based on the regression parameter, Scaled Conjugate method outpaces Levenberg-Marquardt and on the basis of Mean Squared Error (MSE), it is seen that the Levenberg-Marquardt has better accuracy than Scaled Conjugate.

Resource Allocation and Node Placement in Multi-Hop Heterogeneous Integrated-Access-and-Backhaul Networks

Abstract: We consider a heterogeneous MIMO-OFDMA based dense small cell (SC) system in which each macro cell base station (MBS) serves its coverage area with the help of small cell base stations (SBSs) through multi-hop wireless connections. The SBSs act as integrated access and backhaul (IAB) nodes that handle both access and backhaul traffics with wireless links. We first develop an optimal (sum-rate maximization) resource allocation (RA) algorithm which considers subcarriers/spatial subchannels assignment and the associated power allocations. We also present two low-complexity suboptimal RA schemes which, as verified by simulations, incur only minor performance loss in the high SNR region. Our RA algorithms can be applied to other multi-hop networks with general UE association rule and node location distributions. We study the channel aging effect caused by the time lag between the time channel state information (CSI) is measured and that when data transmission occurs. We show the benefit of channel prediction and the limit of a centralized RA approach. The advantages of frequency (channel) reuse and the multi-hop architecture are demonstrated as well. A related but perhaps more important system design issue for an IAB cellular network is the IAB node placement problem. With the given UE association rule and UE location distribution, we present systematic approaches to find the optimal node locations. For two special propagation models, we derive closed-form expressions for the node locations that maximizes a spectral efficiency lower bound. Numerical results validate the accuracy of our estimates based on either numerical evaluations or closed-form solutions.

Performance Analysis of Joint Transmit and Receive Antenna Selection With Orthogonal Space-Time Coding

Abstract: This paper analyzes the performance of multiple-input-multiple-output (MIMO) systems with transmit and receive antenna selection (T-RAS). The average bit error rate (BER) and the average symbol error rate (SER) are derived by utilizing the characteristic function (CF) of the joint output signal-to-noise ratios (SNRs). Our approach can be used over not only independent but also arbitrary correlated channels. For the sake of brevity, this paper focuses on Nakagami-m fading channels. The simulation results are provided to validate the numerical calculations.

Hardware Impairments-Aware Transceiver Design for Multi-Carrier Full-Duplex MIMO Relaying

Abstract: In this work, we study the linear precoding and decoding design problem for a full-duplex (FD) multi-carrier (MC) decode and forward (DF) relaying system, under multiple sources of impairments. In particular, the impact of non-linear hardware distortions at the transmit and receiver chains, leading to residual self-interference (SI) and inter-carrier leakage (ICL), as well as the imperfect channel state information (CSI) are taken into account. In the first step, the known time-domain characterization of hardware impairments is transformed over a general orthonormal MC basis. As a result, the problem of linear precoding and decoding design is formulated to maximize the MC system sum-rate, however, leading to a non-convex mathematical structure. An alternating quadratic convex program (AQCP) is consequently proposed, with a monotonic improvement at each iteration, leading to a guaranteed convergence. The proposed AQCP framework is then extended, employing the Dinkelbach algorithm, in order to maximize the system energy efficiency in terms of bits-per-Joule. The proposed design strategies are considered both for per-subcarrier as well as the joint-subcarrier coding strategies, wherein the latter case the coding is performed jointly over all subcarriers. Numerical simulations show a significant gain in the performance of the proposed algorithms compared to the half-duplex (HD) counterparts or to the solutions where the impact of impairments are not considered, particularly when the hardware accuracy is not very high.

Transceivers and methods for use in transmitting information in a massive mimo system

Abstract: A method and apparatus is disclosed herein for transmitting information in massive MIMO system. In one embodiment, the apparatus comprises a plurality of antenna elements; a baseband processor; a plurality of radio-frequency (RF) chains coupled to the baseband processor; a plurality of switches coupled to the plurality of RF chains, wherein positions of switches in the plurality of switches being determined by instantaneous channel state information; a radio-frequency (RF) preprocessor coupled between the plurality of switches and the plurality of antenna elements, the RF preprocessor to apply a preprocessing matrix to signals, elements of the preprocessing matrix being adjusted as a function of average channel state information, and wherein the positions of the switches and elements of the preprocessing matrix are jointly chosen, and wherein the preprocessing matrix is chosen based on a metric related to expected performance obtained from at least one channel realization.