Adaptive Pilot Pattern for Massive MIMO Systems

Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can significantly improve the downlink bit error rate (BER) performance of DS-CDMA in a frequency-selective fading channel. However, the uplink BER performance degrades due to a strong multi-user interference (MUI). We have proposed frequency-interleaved single-carrier spread spectrum multi-access (SC-SSMA) with MMSE-FDE, in which the subcarrier components of each user's signal are interleaved onto a wider bandwidth. Since frequency-interleaving patterns assigned to different users are orthogonal to each other, frequency-interleaved SC-SSMA can avoid the MUI completely while achieving frequency diversity gain with MMSE-FDE. In this paper, transmit/receive antenna diversity is applied to frequency-interleaved SC-SSMA with MMSE-FDE to further improve the BER performance. Its conditional BER is derived for the given set of channel gains. The average BER performance is numerically evaluated using the derived conditional BER and is confirmed by computer simulation.

Recently, multi-carrier code division multiple access (MC-CDMA) has been attracting much attention as a broadband wireless access technique for the next generation mobile communications systems. Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can take advantage of the channel frequency-selectivity and improve the average bit error rate (BER) performance due to frequency-diversity gain. However, conventional MC-CDMA requires the insertion of guard interval (GI) and this reduces the transmission efficiency. Overlap FDE technique has been proposed that requires no GI insertion. Recently, we showed that MC-CDMA using overlap FDE can provide almost the same BER performance as the conventional MC-CDMA downlink using the GI insertion. However, our previous work assumed the ideal channel estimation. In this paper, we propose a pilot assisted channel estimation technique suitable for MC-CDMA downlink using overlap FDE and evaluate the BER performance by computer simulation.

In this paper, we propose a joint channel estimation and symbol detection (JCESD) algorithm relying on message-passing algorithms (MPA) for orthogonal frequency division multiple access (OFDMA) systems. The channel estimation and symbol detection leverage the framework of expectation propagation (EP) and belief propagation (BP) with the aid of Gaussian approximation, respectively. Furthermore, to reduce the computation complexity involved in channel estimation, the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula. Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%, compared with the traditional linear minimum mean square error (LMMSE) algorithm, and can approach to the bit error rate (BER) performance bound of perfectly known channel state information within 0.1 dB.

The initial solution of a massive multiple-input multiple-output (M-MIMO) detector for uplink (UL) is greatly influence the balance between the bit error rate (BER) performance and the computational complexity. Although the maximum likelihood (ML) detector obtains the best BER performance, it has an extremely high computational complexity. Iterative linear minimum mean square error (MMSE) detector based on the Gauss–Seidel (GS), the successive over-relaxation (SOR), and the Jacobi (JA), obtains a good performance-complexity profile when the base station (BS)-to-user-antenna-ratio (BUAR) is large. However, when the BUAR is small, the system suffers from a considerable performance loss. In this paper, a hybrid detector based on the joint GS and SOR methods is proposed where the initial solution is determined by the first iteration of GS method. Numerical results show a considerable complexity reduction and performance enhancement using the proposed GS-SOR method over all methods when the BUAR is small.

This paper presents a bit error rate (BER) performance analysis of vehicular communication systems (VCS) based on the IEEE 802.11p standard assuming velocity variations of the mobile stations (MSs). To that end, we propose a novel Monte Carlo vehicle-to-vehicle (V2V) fading channel simulator that takes into account the accelerated motion and trajectory variations of the MSs. On the grounds of the proposed channel simulator, we assess the impact of the MSs' velocity variations on the system's BER performance. We assume that the channel state information is obtained following the least-squares (LS) channel estimation techniques that are commonly implemented in commercial off-the-shelf WiFi devices. The results show that the velocity variations have in general a slight impact on the system's BER performance. However, the performance is aggravated as the data frame length or the relative speed increases. The simulation framework presented in this paper can be used as a benchmark to evaluate the performance of the emerging VCS in safety critical scenarios.

This paper presents a novel precoder design for an orthogonal frequency division multiplexing (OFDM) system using a channel estimator. First, an asymptotically tight approximation of the pairwise error probability (PEP) error with channel estimation error is presented and is shown to improve the existing upper bound of the PEP. Using the proposed approximation, a near-optimal power allocation scheme is derived and investigated and a new precoding scheme is introduced to improve the bit error rate (BER) performance of the receiver assisted by a minimum mean square error (MMSE) channel estimator. Both experimental and theoretical results included in this paper show improvement in the BER performance of a receiver with channel estimators utilizing the introduced precoder and power allocation scheme.

A turbo receiver combined with CFO compensation in frequency-domain for OFDMA uplink

In a companion paper, we have studied the zero-forcing (ZF) transceiver with decision feedback equalizer (DFE) over slowly time-varying narrowband multiinput multioutput (MIMO) channels. The space-time generalized triangular decomposition (ST-GTD) was used for the design of ZF-DFE transceivers. The space-time geometric mean decomposition (ST-GMD) ZF transceiver minimizes both the arithmetic mean square error (MSE) at the feedback detector and the average uncoded bit error rate (BER) in moderate high signal-to-noise ratio (SNR). This paper addresses the design problem of DFE transceiver without zero-forcing constraint. In the first part, a channel independent temporal precoder is superimposed on the conventional block-wise GMD-based minimum mean square error (MMSE) DFE transceiver to take advantage of the temporal diversity. In the second part, ST-GTD is applied for the design of MMSE DFE transceivers. With accurate channel prediction and space-time powerloading, the proposed ST-GMD MMSE transceiver minimizes the arithmetic MSE at the feedack detector, and maximizes Gaussian mutual information. For practical applications, the ST-GTD MMSE transceiver which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD MMSE system is also developed. In the convex region, our analysis shows that the proposed MMSE transceivers has better BER performance than the conventional GMD-based MMSE transceiver; the average BERs of the proposed systems are nonincreasing functions of the ST-block size. The superior performance of ST-GMD MMSE transceiver over the ST-GMD ZF transceiver is also verified analytically.

In this paper, a new signal detection scheme for overloaded multiple-input multiple output (MIMO) systems is proposed. In MIMO signal detection with belief propagation (BP), a factor graph consists of many loops that arise high complexity and cause performance degradation due to outliers. Various schemes have been proposed to overcome these issues. In BP with maximal ratio combining (MRC) and minimum mean square error (MMSE) pre-cancellation, a conventional scheme applies MRC on received signals in advance to obtain diversity gain to improve bit error rate (BER) performance as compared with BP using only MMSE pre-cancellation. To achieve further performance improvement, BP using a combined channel matrix is proposed in this paper. In the proposed scheme, the number of observation nodes is increased by combining a part of an original channel matrix to the channel matrix with MRC and MMSE pre-cancellation to enhance diversity gain. Numerical results obtained through computer simulation show that the BER performance of the proposed scheme is superior to that of BP or BP with MRC and MMSE pre-cancellation. The proposed scheme improves BER performance by about 3.1 dB at a BER of 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> as compared with the BP withMRC and MMSE pre-cancellation. The computational complexity of the proposed scheme increases as the number of rows of the additional channel submatrix. It is in the same order of magnitude as that of the original BP based MIMO detection scheme.

This paper presents some experimental results on both the channel estimation based minimum mean square error Turbo equalizer (CE MMSE-TEQ) and the direct-adaptation turbo equalizer (DA-TEQ) in single-input single-output (SISO) underwater acoustic (UWA) channels. For CE MMSE-TEQ, we compare the soft-decision feedback Turbo equalizer (SDFE), the bidirectional soft-decision feedback Turbo equalizer (Bi-SDFE) and the classic linear Minimum Mean Square Error (MMSE) Turbo equalizer in terms of bit error rate (BER) performance. For DA-TEQ, the recently proposed soft-decision direct-adaptation TEQ (Soft DA-TEQ) is evaluated with the same set of experimental data. Both QPSK and multilevel modulations (8PSK and 16QAM) have been tested with the symbol rate of 9.77 ksymbols/s. Experimental results show that the CE-TEQs are more robust in SISO underwater acoustic transmission under harsh channel conditions. Especially, with low pilot overheads, the recently proposed Bi-SDFE achieved low BER performance in all cases.

Massive multiple‐input multiple‐output (M‐MIMO) is one of the cutting edge technologies that provides significant improvement in throughput, coverage and spectral efficiency. The challenge with M‐MIMO systems is to extract individual signals from the composite signal, thus making optimal detectors prohibitively complex. Recently, approximate message passing (AMP) and its variant detectors have gained substantial importance due to their decreased complexity and improved performance. However, AMP algorithm does not always converge. Non‐linear detectors like vertical Bell‐Labs layered space‐iime improve the bit error rate (BER) but with high complexity, whereas, linear minimum mean square error (MMSE) detector offers low complexity while compromising on BER performance. Neumann series based MMSE detectors further reduce MMSE computational complexity, however, the BER performance remains the same. In this work, the authors propose a hybrid Neumann series based MMSE detector which decomposes the detected signal into its constituent components and apply a neighbourhood selection algorithm on the obtained components thus improving the overall performance. Another contribution of this work is derivation of an off‐set value for optimised neighbourhood set selection that enables more accurate detection while further reducing computational complexity. Simulation results confirm that the proposed scheme outperforms aforementioned algorithms in terms of BER performance and computational complexity in a continuously changing Rayleigh channel.

Minimum mean square error (MMSE) linear detector has been considered as one of the potential detection algorithm for uplink multi-user massive MIMO systems, because it can achieve the near-optimal bit error rate (BER) performance. However, it involves matrix inversion with high complexity. Thus, the conventional Gauss-Seidel (GS) method has been applied for obtain a low-complexity MMSE detector without employing the computationally intensive matrix inversion. In this paper, we propose a refinement for the conventional GS method based on band matrix concept in order to accelerate the convergence rate, that means reduce the number of iterations and consequently the complexity, guaranteeing the near-optimal BER performance. Analytical and numerical results show the efficiency of the proposed method in comparison to the conventional GS method.

In this paper, linear precoding (LP) algorithm has been studied to improve the bit error rate (BER) performance of large scale multiple input multiple output (MIMO) system. A new technique of enhancing the BER performance of linear precoding algorithm without complexity in hardware and mathematical calculations is proposed and it is used on a traditional LP algorithms like a Maximum Ratio Transmission (MRT), a Zero-Forcing (ZF), a Regularized Zero-Forcing (RZF), and a Minimum Mean Square Error (MMSE) for Millimeter wave MU-MIMO communication system. A new technique is also used to mitigate the BER gab problem between (ZF, MMSE) and (RZF, MMSE) linear precoding algorithms. The result shows that with using the new technique, the BER performance of modified LP significantly outperform their traditional LP by 10−5 when using 4 element of BS antenna, 10−6 when using 16 element of BS antenna and mitigate the BER gab problem at different signal to noise ratio (SNR).

One of the most important problems in helicopter satellite communications is that the periodic blockage of the received signal due to rotor blades significantly degrades the bit error rate (BER) performance. Time diversity is attractive in order to solve this problem. In a previous study, we proposed a time diversity combining scheme performing maximal ratio combining (MRC) on the basis of the channel blockage information estimated with a pseudo BER. However, in the low carrier-to-noise power ratio region, the BER performance of this conventional scheme is inferior to that of the ideal MRC because the channel estimation error is increased. In this paper, an accurate time diversity combining with a novel channel estimation scheme is proposed. The proposed scheme extracts the line spectrum of the periodic blockage from the envelope of the received signal by using the fast Fourier transform (FFT). The channel blockage information is estimated from the inverse FFT of the extracted line spectrum. The results of computer simulation show that the proposed scheme achieves the excellent BER performance very close to that of the ideal MRC.

End-to-end learning of a communications system using the deep learning-based autoencoder concept has drawn interest in recent research due to its simplicity, flexibility and its potential of adapting to complex channel models and practical system imperfections. In this paper, we have compared the bit error rate (BER) performance of autoencoder based systems and conventional channel coded systems with convolutional coding (CC), in order to understand the potential of deep learning-based systems as alternatives to conventional systems. From the simulations, autoencoder implementation was observed to have a better BER in 0-5 dB E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> range than its equivalent half-rate convolutional coded BPSK with hard decision decoding, and to have only less than 1 dB gap at a BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> . Furthermore, we have also proposed a novel low complexity autoencoder architecture to implement end-to-end learning of coded systems in which we have shown better BER performance than the baseline implementation. The newly proposed low complexity autoencoder was capable of achieving a better BER performance than half-rate 16-QAM with hard decision decoding over the full 0-10 dB E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> range and a better BER performance than the soft decision decoding in 0-4 dB E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b</sub> /N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> range.