Non-coherent Massive SIMO Systems in ISI Channels: Constellation Design and Performance Analysis

A massive single-input multiple-output (SIMO) system with a single transmit antenna and a large number of receive antennas in intersymbol interference (ISI) channels is considered. Contrast to existing energy detection (ED)-based non-coherent receiver where conventional pulse amplitude modulation (PAM) is employed, we propose a constellation design which minimizes the symbol-error rate (SER) with the knowledge of channel statistics. To make a comparison, we derive the SERs of the ED-based receiver with both the proposed constellation and PAM, namely $P_{e\_opt}$ and $P_{e\_pam}$. Specifically, asymptotic behaviors of the SER in regimes of a large number of receive antennas and high signal-to-noise ratio (SNR) are investigated. Analytical results demonstrate that the logarithms of both $P_{e\_opt}$ and $P_{e\_pam}$ decrease approximately linearly with the number of receive antennas, while $P_{e\_opt}$ degrades faster. It is also shown that the proposed design is of less cost, because compared with PAM, less antennas are required to achieve the same error rate

Semiblind Channel Estimation and Data Detection for OFDM Systems With Optimal Pilot Design

This paper considers semiblind channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) over frequency-selective fading channels. We show that the samples of an OFDM symbol are jointly complex Gaussian distributed, where the mean and covariance are determined by the locations and values of fixed pilot symbols. We exploit this distribution to derive a novel maximum-likelihood (ML) semiblind gradient-descent channel estimator. By exploiting the channel impulse response (CIR) statistics, we also derive a semiblind data detector for both Rayleigh and Ricean fading channels. Furthermore, we develop an enhanced data detector, which uses the estimator error statistics to mitigate the effect of channel estimation errors. Efficient implementation of both the semiblind and the improved data detectors is provided via sphere decoding and nulling-canceling detection. We also derive the Cramér-Rao bound (CRB) and design optimal pilots by minimizing the CRB. Our proposed channel estimator and data detector exhibit high bandwidth efficiency (requiring only a few pilot symbols), achieve the CRB, and also nearly reach the performance of an ideal reference receiver

Joint Design of Multi-Tap Analog Cancellation and Digital Beamforming for Reduced Complexity Full Duplex MIMO Systems

Incorporating full duplex operation in Multiple Input Multiple Output (MIMO) systems provides the potential of boosting throughput performance. However, the hardware complexity of the analog self-interference canceller scales with the number of transmit and receive antennas, thus exploiting the benefits of analog cancellation becomes impractical for full duplex MIMO transceivers. In this paper, we present a novel architecture for the analog canceller comprising of reduced number of taps (tap refers to a line of fixed delay and variable phase shifter and attenuator) and simple multiplexers for efficient signal routing among the transmit and receive radio frequency chains. In contrast to the available analog cancellation architectures, the values for each tap and the configuration of the multiplexers are jointly designed with the digital beamforming filters according to certain performance objectives. Focusing on a narrowband flat fading channel model as an example, we present a general optimization framework for the joint design of analog cancellation and digital beamforming. We also detail a particular optimization objective together with its derived solution for the latter architectural components. Representative computer simulation results demonstrate the superiority of the proposed low complexity full duplex MIMO system over lately available ones.Comment: 8 pages, 4 figures, IEEE ICC 201

Parallel-Interference-Cancellation-Assisted Decision-Directed Channel Estimation for OFDM Systems using Multiple Transmit Antennas

The number of transmit antennas that can be employed in the context of least-squares (LS) channel estimation contrived for orthogonal frequency division multiplexing (OFDM) systems employing multiple transmit antennas is limited by the ratio of the number of subcarriers and the number of significant channel impulse response (CIR)-related taps. In order to allow for more complex scenarios in terms of the number of transmit antennas and users supported, CIR-related tap prediction-filtering-based parallel interference cancellation (PIC)-assisted decision-directed channel estimation (DDCE) is investigated. New explicit expressions are derived for the estimator’s mean-square error (MSE), and a new iterative procedure is devised for the offline optimization of the CIR-related tap predictor coefficients. These new expressions are capable of accounting for the estimator’s novel recursive structure. In the context of our performance results, it is demonstrated, for example, that the estimator is capable of supporting L = 16 transmit antennas, when assuming K = 512 subcarriers and K0 = 64 significant CIR taps, while LS-optimized DDCE would be limited to employing L = 8 transmit antennas. Index Terms—Decision-directed channel estimation (DDCE), multiple transmit antennas, orthogonal frequency division multiplexing (OFDM), parallel interference cancellation (PIC)