Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems

This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.

Low-complexity signal detection for massive MIMO systems via trace iterative method

Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.

A Survey on Channel Measurements and Models for Underground MIMO Communication Systems

The high reliability of the communication system is critical in metro and mining applications for personal safety,channel optimization,and improving operational performance.This paper surveys the progress of wireless communication systems in underground environments such as tunnels and mines from 1920 to 2022,including the evolution of primitive technology,advancements in channel modelling,and realization of various wireless propagation channels.In addition,the existing and advanced channel modeling strategies,which include the evolution of different technologies and their applications;mathematical,analytical,and experimental techniques for radio propagation;and significance of the radiation characteristics,antenna placement,and physical environment of multiple-input multiple-output(MIMO)communication systems,are analyzed.The given study introduces leaky coaxial cable(LCX)and distributed antenna system(DAS)designs for improving narrowband and wideband channel capacity.The paper concludes by figuring out open research areas for the future technologies.

A Low-Complexity Signal Detection Utilizing AOR Iterative Method for Massive MIMO Systems

Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error(MMSE) signal detection using the accelerated overrelaxation(AOR) iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.

Evaluation of Preamble Based Channel Estimation for MIMO-FBMC Systems

Filter-bank multicarrier （FBMC） with offset quadrature amplitude modulation （OQAM） is a candidate waveform for future wireless communications due to its advantages over orthogonal frequency division multiplexing （OFDM） systems. However, because of or-thogonality in real field and the presence of imaginary intrinsic interference, channel estimation in FBMC is not as straightforward as OFDM systems especially in multiple antenna scenarios. In this paper, we propose a channel estimation method which employs intrinsic interference cancellation at the transmitter side. The simulation results show that this method has less pilot overhead, less peak to average power ratio （PAPR）, better bit error rate （BER）, and better mean square error （MSE） performance compared to the well-known intrinsic approximation methods （IAM）.

Shannon information capacity of time reversal wideband multiple-input multiple-output system based on correlated statistical channels

Utilizing channel reciprocity, time reversal（TR） technique increases the signal-to-noise ratio（SNR） at the receiver with very low transmitter complexity in complex multipath environment. Present research works about TR multiple-input multiple-output（MIMO） communication all focus on the system implementation and network building. The aim of this work is to analyze the influence of antenna coupling on the capacity of wideband TR MIMO system, which is a realistic question in designing a practical communication system. It turns out that antenna coupling stabilizes the capacity in a small variation range with statistical wideband channel response. Meanwhile, antenna coupling only causes a slight detriment to the channel capacity in a wideband TR MIMO system. Comparatively, uncorrelated stochastic channels without coupling exhibit a wider range of random capacity distribution which greatly depends on the statistical channel. The conclusions drawn from information difference entropy theory provide a guideline for designing better high-performance wideband TR MIMO communication systems.

Throughput-based mode switching for MIMO ARQ systems in presence of transmit correlation

The mode switching between spatial multiplexing （SM） and space-time block code （STBC） diversity is investigated for the multiple-input multiple-output （MIMO） automatic repeat request （ARQ） system. Five important practical factors are considered in the proposed switching scheme： transmit correlation, ARQ technique, packet loss probability （PLP） constraint, discrete rate transmission （DRT） and channel coding. Under the spatially correlated channel, the distributions of the post signal-to-interference-plus- noise ratio （SiNR） for the SM mode and the STBC mode are obtained by using Gamma approximations. Then this paper derives the closed-form expressions of the PLP and the throughput for different modes when the ARQ technique is employed, based on which the mode switching algorithm is proposed to improve the spectral efficency. In the simulation, the correction of the expressions is first verified. Then, the significant gain observed by the proposed algorithm is presented. Since the switching point is the key parameter to implement the mode switching, this paper also shows how the switching point is affected by the practical factors considered.

Joint resource allocation scheme for target tracking in distributed MIMO radar systems

A joint resource allocation scheme concerned with the sensor subset,power and bandwidth for range-only target tracking in multiple-input multiple-output(MIMO)radar systems is proposed.By selecting an optimal subset of sensors with the predetermined size and implementing the power allocation and bandwidth strategies among them,this algorithm can help achieving a better performance within the same resource constraints.Firstly,the Bayesian Cramer-Rao bound(BCRB)is derived from it.Secondly,a criterion for minimizing the BCRB at the target location among all targets tracking in a certain range is derived.Thirdly,the optimization problem involved with three variable vectors is formulated,which can be simplified by deriving the relationship between the optimal power allocation vector and the bandwidth allocation vector.Then,the simplified optimization problem is solved by the cyclic minimization algorithm incorporated with the sequential parametric convex approximation(SPCA)algorithm.Finally,the validity of the proposed method is demonstrated with simulation results.

Energy-efficient resource management for CCFD massive MIMO systems in 6G networks

This paper presents a co-time co-frequency fullduplex(CCFD)massive multiple-input multiple-output(MIMO)system to meet high spectrum efficiency requirements for beyond the fifth-generation(5G)and the forthcoming the sixth-generation(6G)networks.To achieve equilibrium of energy consumption,system resource utilization,and overall transmission capacity,an energy-efficient resource management strategy concerning power allocation and antenna selection is designed.A continuous quantum-inspired termite colony optimization(CQTCO)algorithm is proposed as a solution to the resource management considering the communication reliability while promoting energy conservation for the CCFD massive MIMO system.The effectiveness of CQTCO compared with other algorithms is evaluated through simulations.The results reveal that the proposed resource management scheme under CQTCO can obtain a superior performance in different communication scenarios,which can be considered as an eco-friendly solution for promoting reliable and efficient communication in future wireless networks.

Pilot Contamination Elimination in Massive MIMO Systems with an Improved Time-Shifted Scheme

Pilot contamination can bring up a grave impairment in the performance of massive multiple-input multiple-output(MIMO)systems.In this paper,an improved time-shifted pilot scheme is proposed to reduce the pilot contamination,where orthogonal pilots are employed in the same group to eliminate the residual intragroup interference existing in the original time-shifted pilot scheme.Meanwhile,the rigorous closed-form expressions of both downlink and uplink transmission rates with a finite number of antennas are derived,and it is shown that the intra-group interference can be completely eliminated by the proposed scheme.Simulation results demonstrate that both downlink and uplink transmission rates are significantly improved by employing the proposed scheme.

Switching between multiplexing and diversity in MIMO systems with QoS provisioning

Multiple-input multiple-output (MIMO) wireless communication systems can significantly improve the spectrum efficiency or transmission reliability through spatial multiplexing or diversity respectively.Most of previous works mainly have focused on the multiplexing-diversity tradeoff or switching between multiplexing and diversity without considering the property of heterogeneous QoS provisioning.In this paper,switching between multiplexing and diversity in MIMO system with the heterogeneous QoS provisioning is studied.Firstly the QoS provisioning for users are classified into two classes:users with real time service requirement and users with non-real time service requirement respectively.Then based on the heterogeneous QoS Provisioning for users,two different switching criterions are proposed,switching based on the Euclidean distance for users with real time service to minimize the probability of symbol error and capacity-based switching criterion for users with non-real time service to maximize the transmission capacity respectively.Finally,numerical simulation results are illustrated to demonstrate the performance of proposed scheme.

Space-Time Multiuser Detection for DS-CDMA Communication in MIMO Systems

Space-time signal processing based on multiple-input multiple-output（MIMO） systems is an active research field in which interfering signals are cancelled and multiuser detection is achieved using space diversity. In a Rayleigh fading channel, space-time block cedes using multiple transmitting antennas can improve system performance and reduce bit-error-rate for multiuser detection. In this paper, several antenna configurations are designed for DS-CDMA communication in MIMO systems. Space-time linear multinser detection and space-time serial interference cancellation multiuser detection are simulated. Bit-error-rate and computation complexities of the two methods are compared. Conclusions are given in the end.

Iterative Detection and Decoding Algorithm in Dual Polarized Land Mobile Satellite MIMO Systems

An iterative detection and decoding algorithm with outer code decision feedback is proposed for the dual polarized( DP) land mobile satellite( LMS) MIMO systems using concatenated codes. A feedback structure is added after the outer decoder in the proposed algorithm. The feedback information is exploited to control the detecting list in the MIMO detector and reduce the number of symbols which have to be processed at each iteration. As a result,the computational complexity is reduced. Meanwhile,the successfully decoded outer code words are used to calculate the more reliable initial information for the inner decoder and the system performance can be improved by this step. The simulation results show that the proposed algorithm can reduce the computational complexity compared to the traditional iterative detection and decoding algorithm and achieve better performance.

Particle filter for joint frequency offset and channel estimation in MIMO-OFDM systems

A particle filter is proposed to perform joint estimation of the carrier frequency offset （CFO） and the channel in multiple-input multiple-output orthogonal frequency division multiplexing （MIMO-OFDM） wireless communication systems. It marginalizes out the channel parameters from the sampling space in sequential importance sampling （SIS）, and propagates them with the Kalman filter. Then the importance weights of the CFO particles are evaluated according to the imaginary part of the error between measurement and estimation. The varieties of particles are maintained by sequential importance resampling （SIR）. Simulation results demonstrate this algorithm can estimate the CFO and the channel parameters with high accuracy. At the same time, some robustness is kept when the channel model has small variations.

A LOWER COMPLEXITY ANTENNA SELECTION FOR DF RELAY MIMO SYSTEMS

Based on the existing incremental selection algorithm for Decode-and-Forward (DF) Multiple Input Multiple Output (MIMO) systems, a faster one which combines the incremental selection with the decremental exclussion is proposed. Firstly, the algorithm selects one antenna which makes the increment of the capacity greatest in every step. Then, excludes the antennas whose contribution to the capacity is less than μ% of that of the best antenna. Simulations show that the proposed algorithm achieves comparable performance to the existing one and has obviously decreased complexity under the appropriate threshold μ% .

Optimal Multipoint-to-Multipoint Transceiver Design with Massive MIMO Relay Station in OFDM Systems

Based on massive MIMO(multiple-input multiple-output)multipoint-to-multipoint(M2M) systems,in order to avoid pilot contamination and improve the performance of capacity,a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal subcarriers of OFDM(orthogonal frequency division multiplexing) during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase.The massive M2 M system included a single relay station,multiple paired source nodes and destination nodes.Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems.After some mathematical manipulation to sum-rate,the cost function of sum-rate was expressed as quadratic optimizing expressions which could be solved by regular convex optimization softwares.Different from existing algorithms,the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement.Simulations indicate the effectiveness of the proposed optimal precoding system.The proposed scheme not only can reduce pilot contamination,but also can improve performance of bit-error-rate(BER) as well as sumrate contrast to existing algorithms.In addition,it shows that the proposed M2 M massive MIMO system works steadily when the number of users increases in large scale.

A SIMPLIFIED QRD-M SIGNAL DETECTION ALGORITHM FOR MIMO-OFDM SYSTEMS

QR Decompositon with an M-algorithm(QRD-M) has good performance with low complexity,which is considered as a promising technique in Multiple-Input Multiple-Output(MIMO) detections.This paper presented a simplified QRD-M algorithm for MIMO Orthogonal Frequency Division Multiplexing(MIMO-OFDM) systems.In the proposed scheme,each surviving path is expanded only to partial branches in order to carry out a limited tree search.The nodes are expanded on demand and sorted in a distributed manner,based on the novel expansion scheme which can pre-determine the children's ascending order by their local distances.Consequently,the proposed scheme can significantly decrease the complexity compared with conventional QRD-M algorithm.Hence,it is especially attractive to VLSI implementation of the high-throughput MIMO-OFDM systems.Simulation results prove that the proposed scheme can achieve a performance very close to the conventional QRD-M algorithm.

DESIGN OF LOW-DENSITY PARITY CHECK CODES FOR MIMO SYSTEMS WITH DOUBLY-ITERATIVE RECEIVERS

In this paper, the Multiple Input Multiple Output (MIMO) doubly-iterative receiver which consists of the Probabilistic Data Association detector (PDA) and Low-Density Parity-Check Code (LDPC) decoder is developed. The receiver performs two iterative decoding loops. In the outer loop, the soft information is exchanged between the PDA detector and the LDPC decoder. In the inner loop, it is exchanged between variable node and check node decoders inside the LDPC decoder. On the light of the Extrinsic Information Transfer (EXIT) chart technique, an LDPC code degree profile optimization algorithm is developed for the doubly-iterative receiver. Simulation results show the doubly-receiver with optimized irregular LDPC code can have a better performance than the one with the regular one.

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.

Inter-carrier Interference Analysis for MIMO-OFDM Systems in High-Speed Train Environment

The orthogonality between the subcarriers of multipleinput multiple-output orthogonal frequency division multiplexing( MIMO-OFDM) systems is destroyed due to the Doppler frequency offset,particularly in the high-speed train( HST) environment,which leads to severe inter-carrier interference( ICI). Therefore,it is necessary to analyze the mechanism and influence factor of ICI in HST environment. In this paper, by using a non-stationary geometry-based stochastic model( GBSM) for MIMO HST channels, ICI is analyzed through investigating the channel coefficients and the carrier-to-interference power ratio( CIR). It is a fact that most of signal energy spreads on itself and its several neighborhood subcarriers. By investigating the amplitude of subcarriers, CIR is used to evaluate the ICI power level. The simulation results show that the biggest impact factor for the CIR is the multipath number L and the minimum impact factor K; when the train speed υR> 400 km / h,the normalized Doppler frequency offset ε > 0. 35,the CIR tends to zero,and the communication quality will be very poor at this condition. Finally,bit error rate( BER) is investigated by simulating a specific channel environment.