Low-complexity soft-output signal detector based on adaptive pre-conditioned gradient descent method for uplink multiuser massive MIMO systems

In multiuser massive Multiple Input Multiple Output(MIMO)systems,a large amount of antennas are deployed at the Base Station(BS).In this case,the Minimum Mean Square Error(MMSE)detector with soft-output can achieve the near-optimal performance at the cost of a large-scale matrix inversion operation.The optimization algorithms such as Gradient Descent(GD)method have received a lot of attention to realize the MMSE detection efficiently without a large scale matrix inversion operation.However,they converge slowly when the condition number of the MMSE filtering matrix(the coefficient matrix)increases,which can compromise the efficiency of their implementation.Moreover,their soft information computation also involves a large-scale matrix-matrix multiplication operation.In this paper,a low-complexity soft-output signal detector based on Adaptive Pre-conditioned Gradient Descent(APGD-SOD)method is proposed to realize the MMSE detection with soft-output for uplink multiuser massive MIMO systems.In the proposed detector,an Adaptive Pre-conditioner(AP)matrix obtained through the Quasi-Newton Symmetric Rank One(QN-SR1)update in each iteration is used to accelerate the convergence of the GD method.The QN-SR1 update supports the intuitive notion that for the quadractic problem one should strive to make the pre-conditioner matrix close to the inverse of the coefficient matrix,since then the condition number would be close to unity and the convergence would be rapid.By expanding the signal model of the massive MIMO system and exploiting the channel hardening property of massive MIMO systems,the computational complexity of the soft information is simplified.The proposed AP matrix is applied to the GD method as a showcase.However,it also can be used by Conjugate Gradient(CG)method due to its generality.It is demonstrated that the proposed detector is robust and its convergence rate is superlinear.Simulation results show that the proposed detector converges at most four iterations.Simulation results also show that the proposed approach achieves a better trade-off between the complexity and the performance than several existing detectors and achieves a near-optimal performance of the MMSE detector with soft-output at four iterations without a complicated large scale matrix inversion operation,which entails a big challenge for the efficient implementation.

Comparison of Two Neural Networks in MC-CDMA Multiuser Detection

MC CDMA is a thriving topic in recent years. Multiuser interference is also very severe as in DS CDMA. ML method is the best multiuser detection, but it has a computational complexity exponentially increased with the number of users. Mean field annealing and chaotic neural network are two promising optimum techniques. This paper applies them into the ML detection, comparison of the two methods is made.

NOVEL ADAPTIVE MULTIUSER DETECTIONALGORITHM BASED ON WAVELET TRANSFORM

The wavelet transform-based adaptive multiuser detection algorithm is presented. The novel adaptive multiuser detection algorithm uses the wavelet transform for the preprocessing, and wavelet-transformed signal uses LMS algorithm to implement the adaptive multiuser detection. The algorithm makes use of wavelet transform to divide the wavelet space, which shows that the wavelet transform has a better decorrelation ability and leads to better convergence. White noise can be wiped off under the wavelet transform according to different characteristics of signal and white noise under the wavelet transform. Theoretical analyses and simulations demonstrate that the algorithm converges faster than the conventional adaptive multiuser detection algorithm, and has the better performance. Simulation results reveal that the algorithm convergence relates to the wavelet base, and show that the algorithm convergence gets better with the increasing of regularity for the same series of the wavelet base. Finally the algorithm shows that it can be easily implemented.

Strong noise attenuation method based on the multiuser kurtosis criterion

The strong noise produced by the leakage of electricity from marine seismic streamers is often received with seismic signals during marine seismic exploration. Traditional denoising methods show unsatisfactory effects when eliminating strong noise of this kind. Assuming that the strong noise signals have the same statistical properties, a blind source separation （BSS） algorithm is proposed in this paper that results in a new denoising algorithm based on the constrained multi-user kurtosis （MUK） optimization criterion. This method can separate strong noise that shares the same statistical properties as the seismic data records and then eliminate them. Theoretical and field data processing all show that the denoising algorithm, based on multi-user kurtosis optimization criterion, is valid for eliminating the strong noise which is produced by the leakage of electricity from the marine seismic streamer so as to preserve more effective signals and increase the signal-noise ratio. This method is feasible and widely applicable.

Joint Dirty Paper Coding and Linear Receiver Design for Multiuser MIMO Broadcast Channels

A multiuser multiple input multiple output (MIMO) broadcast scheme was proposed through applying dirty paper coding (DPC) at the transmitter and linear equalization at the receiver. Assuming single data stream communication for each user, joint transmitter and linear receiver design were done to enhance the system performance. Furthermore, a multiuser scheduling algorithm was presented to exploit multiuser diversity when the number of the users is larger than that of transmit antennas. The proposed system achieves the sum rate close to the Sato bound and is superior to some of the existing schemes.

Iterative Multiuser Receiver Based on Factor Graph for Asynchronous Coded CDMA Systems

Factor graph, so named because it graphically represents function factorization, with which and its sum-product algorithm the iterative algorithm can be derived clearly. An iterative multiuser receiver based on factor graph for asynchronous coded CDMA system is proposed. In this paper, the a posteriori probability of users information bits conditioned on the noise-whitening filters output is represented by factor graphs, after numbers of iterations with the sum-product algorithm the information bits are estimated. The authors also propose a reduced complexity algorithm. Simulation results show that with this proposed receiver, near-single-user performance can be achieved, and small performance degradation for the reduced complexity algorithm with significant complexity reduction.

Cross-Layer Framework for Capacity Analysis in Multiuser Ultra-Dense Networks with Cell DTx

Cell discontinuous transmission(Cell DTx)is a key technology to mitigate inter-cell interference(ICI)in ultra-dense networks(UDNs).The aim of this work is to understand the impact of Cell DTx on physical-layer sum rates of SBSs and link-layer quality-of-service(QoS)performance in multiuser UDNs.In this work,we develop a cross-layer framework for capacity analysis in multiuser UDNs with Cell DTx.In particular,we first extend the traditional one-dimensional effective capacity model to a new multidimensional effective capacity model to derive the sum rate and the effective capacity.Moreover,we propose a new iterative bisection search algorithm that is capable of approximating QoS performance.The convergence of this new algorithm to a unique QoS exponent vector is later proved.Finally,we apply this framework to the round-robin and the max-C/I scheduling policies.Simulation results show that our framework is accurate in approximating 1)queue length distribution,2)delay distribution and 3)sum rates under the above two scheduling policies,and further show that with the Cell DTx,systems have approximately 30% higher sum rate and 35% smaller average delay than those in full-buffer scenarios.

Fair subcarrier-power allocation scheme for multiuser multicarrier systems

The main objective of multiuser orthogonal frequency division multiple access(MU-OFDM) is to maximize the total system capacity in wireless communication systems. Thus, the problem in MU-OFDM system is the adaptive allocation of the resources(subcarriers, bits and power) to different users subject to several restrictions to maximize the total system capacity. In this work, a proposed subcarrier allocation algorithm was presented to assign the subcarriers with highest channel gain to the users. After the subcarrier allocation, subcarrier gain-based power allocation(SGPA) was employed for power and bit loading. The simulation results show that the proposed subcarrier-power allocation scheme can achieve high total system capacity and good fairness in allocating the resources to the users with slightly high computational complexity compared to the existing subcarrier allocation algorithms.

JOINT SPACE-FREQUENCY MULTIUSER SYMBOL DETECTOR FOR MC-CDMA SYSTEM WITH UNIFORM LINEAR ARRAY

The MultiCarrier Code Division Multiple Access (MC-CDMA) scheme is promising for relieving capacity limit problems of Direct Sequence (DS-) CDMA systems due to serious InterChip Interference (ICI) and MultiUser Interference (MUI) in high-data-rate wireless communication systems. In this paper, the Uniform Linear Array (ULA) is applied to the base station of macrocellular MC-CDMA systems in a frequency-selective fading channel environment. A joint space-frequency multiuser symbol sequence detector is developed for all active users within one macrocell without space-frequency channel estimation. Simultaneously, Directions-Of-Arrivals (DOAs) of all active users can also be estimated. By dividing the ULA into two identical overlapping subarrays, a specific auxiliary matrix is constructed, which includes both symbol sequence and DOA information of all active users. Then, based on the subspace method, performing the eigen decomposition on such auxiliary matrix, the closed-form solution of symbol sequences and DOAs for all active users can be obtained. In comparison with schemes based on channel estimation, our algorithm need not explicitly estimate the space-frequency channel for each active user,so it has lower computation complexity. Extensive computer simulations demonstrate the overall performance of this novel scheme.

Compressive sensing based multiuser detector for massive MBM MIMO uplink

Media based modulation(MBM)is expected to be a prominent modulation scheme,which has access to the high data rate by using radio frequency(RF)mirrors and fewer transmit antennas.Associated with multiuser multiple input multiple output(MIMO),the MBM scheme achieves better performance than other conventional multiuser MIMO schemes.In this paper,the massive MIMO uplink is considered and a conjunctive MBM transmission scheme for each user is employed.This conjunctive MBM transmission scheme gathers aggregate MBM signals in multiple continuous time slots,which exploits the structured sparsity of these aggregate MBM signals.Under this kind of scenario,a multiuser detector with low complexity based on the compressive sensing(CS)theory to gain better detection performance is proposed.This detector is developed from the greedy sparse recovery technique compressive sampling matching pursuit(CoSaMP)and exploits not only the inherently distributed sparsity of MBM signals but also the structured sparsity of multiple aggregate MBM signals.By exploiting these sparsity,the proposed CoSaMP based multiuser detector achieves reliable detection with low complexity.Simulation results demonstrate that the proposed CoSaMP based multiuser detector achieves better detection performance compared with the conventional methods.

Secure Transmissions in Wireless Multiuser Networks Using Message Correlation

Due to the openness of wireless multiuser networks,the private information transmitted in uplink or downlink is vulnerable to eavesdropping.Especially,when the downlink transmissions use nonorthogonal multiple access(NOMA)techniques,the system further encounters interior eavesdropping.In order to address these security problems,we study the secret communication in multiuser networks with both uplink and downlink transmissions.Specifically,in uplink transmissions,the private messages transmitted in each slot are correlated,so any loss of the private information at the eavesdropper will prevent the eavesdropper from decoding the private information in later time slots.In downlink transmissions,the messages are correlated to the uplink information.In this way,any unexpected users who lose the expected user’s uplink information cannot decode its downlink information.The intercept probability is used to measure security performance and we analyze it in theory.Finally,simulation results are provided to corroborate our theoretical analysis.

Optimal dynamic spectrum allocation-assisted latency minimization for multiuser mobile edge computing

Mobile Edge Computing(MEC)has been envisioned as an efficient solution to provide computation-intensive yet latency-sensitive services for wireless devices.In this paper,we investigate the optimal dynamic spectrum allocation-assisted multiuser computation offloading in MEC for overall latency minimization.Specifically,we first focus on a static multiuser computation offloading scenario and jointly optimize users'offloading decisions,transmission durations,and Edge Servers'(ESs)resource allocations.Owing to the nonconvexity of our joint optimization problem,we identify its layered structure and decompose it into two problems:a subproblem and a top problem.For the subproblem,we propose a bisection search-based algorithm to efficiently find the optimal users'offloading decisions and ESs’resource allocations under a given transmission duration.Second,we use a linear search-based algorithm for solving the top problem to obtain the optimal transmission duration based on the result of the subproblem.Further,after solving the static scenario,we consider a dynamic scenario of multiuser computation offloading with time-varying channels and workload.To efficiently address this dynamic scenario,we propose a deep reinforcement learning-based online algorithm to determine the near-optimal transmission duration in a real-time manner.Numerical results are provided to validate our proposed algorithms for minimizing the overall latency in both static and dynamic offloading scenarios.We also demonstrate the advantages of our proposed algorithms compared to the conventional multiuser computation offloading schemes.

BLIND ADAPTIVE MULTIUSER DETECTOR FOR NONLINEARLY MODULATED SATELLITE MOBILE CDMA SYSTEMS

This paper presents a novel blind adaptive noncoherent decorrelative multiuser detector for nonlinearly modulated satellite mobile Code Division Multiple Access (CDMA) systems. By using the known signature waveforms of the counterpart earth station in the blind adaptive multiuser detector, the system performance has been improved obviously. The computation results about the convergence properties of the new detector and the previous detectors demonstrate that the proposed multiuser detector has better performance than previous multiuser detectors for nonlinearly modulated CDMA systems.

Efficient multiuser detector based on box-constrained dichotomous coordinate descent and regularization

The presented iterative multiuser detection technique was based on joint deregularized and box-constrained solution to quadratic optimization with iterations similar to that used in the nonstationary Tikhonov iterated algorithm.The deregularization maximized the energy of the solution,which was opposite to the Tikhonov regularization where the energy was minimized.However,combined with box-constraints,the deregularization forced the solution to be close to the binary set.It further exploited the box-constrained dichotomous coordinate descent algorithm and adapted it to the nonstationary iterative Tikhonov regularization to present an efficient detector.As a result,the worst-case and average complexity are reduced down as K2.8 and K2.5 floating point operation per second,respectively.The development improves the "efficient frontier" in multiuser detection,which is illustrated by simulation results.In addition,most operations in the detector are additions and bit-shifts.This makes the proposed technique attractive for fixed-point hardware implementation.

Resource allocation with CCI suppression for multiuser MIMO-OFDM downlink in correlated channels

To minimize the overall transmit power while maintaining a constant data rate and target BER, a downlink adaptive resource allocation algorithm with jointing the exclusive manner and the shared manner is proposed for multiuser MIMO-OFDM system in correlated channels. The algorithm allocates all the subcarriers to different users according to their spatial correlations. The users with high spatial correlation are allocated in the same group and the exclusive manner is applied. The shared manner with an improved null broadening method, which improves the performance of co-channel interference （CCI） suppression and decreases the number of transmit antennas required, is applied between the different group users. As the user＇s direction of departure （DOD） changes very slowly, a looking up table method is used to reduce the computational complexity. The simulation results show that despite the angle spread of DOD, when compared with the exclusive manner, the proposed algorithm improves the spectral efficiency, and when compared with the TDMA-ZF （zero forcing） shared manner, the proposed algorithm decreases the total transmit power by at least 1 dB.

Performance Enhancement of Multiuser Passive Time Reversal Communication Based on Space-Time Block Coding

Reliable, with high data rate, acoustic communication in time-valTing, multipath shallow water environment is a hot research topic recently. Passive time reversal communication has shown promising results in improvement of the system performance. In multiuser environment, the system performance is significantly degraded due to the interference among different users. Passive time reversal can reduce such interference by minimizing the cross-correlated version of channel impulse response among users, which can be realized by the well-separated users in depth. But this method also has its shortcomings, even with the absence of relative motion, the minimization sometimes may be impossible because of the time-varying environment. Therefore in order to avoid the limitation of minimizing the cross-correlated channel function, an approach of passive time reversal based on space-time block coding （STBC） is presented in this paper. In addition, a single channel equalizer is used as a pest processing technique to reduce the residual symbol interference. Experimental results at 13 kHz with 2 kHz bandwidth demonstrate that this method has better performance to decrease bit error rate and improve signal to noise ratio, compared with passive time reversal alone or passive time reversal combined with equalization.

ANALYSIS OF GROUP MULTIUSER DETECTION BASED ON COALITION GAME THEORY

Coalition game theory is introduced to investigate the performance,fairness and stability of decorrelating group multiuser detection receiver,not only from the perspective of individual nodes,but also various coalitions and the whole system as well. Firstly,to derive how the system scale with coalition size,a stochastic model with transferable payoffs (stochastic TU-model) is provided. Secondly,to find the most preferred coalition structures from the view point of individual nodes,a model with Non-Transferable payoffs (NTU-model) is presented. Theoretical analysis and simulation results suggest that stochasticaly the grand coalition is payoff maximizing for the system as a whole,while individual nodes with good-conditioned channels may prefer local "win-win coalitions".

Low Complexity Multiuser Detection with Recursively Successive Zero-Forcing and SIC Based on Nullspace for Multiuser MIMO-OFDM System

To improve the spectrum efficiency, this paper considers the multiuser detection with the MU-MIMO technology for multiuser MIMO-OFDM system uplink with the same subcarrier shared by multiple users. A low complexity multiuser detection algorithm with recursively successive zero-forcing and successive interference cancellation(RSZF-SIC) based on nullspace is proposed. The RSZF process based on the block diagonalization(BD) technique eliminates the co-channel interference(CCI) by a recursive method based on the nullspace orthogonal theorem. The SIC process detects the user signals respectively with the reasonable user detection sequence based on the results of the RSZF process. The computational complexity of the proposed algorithm is effectively reduced by reducing the total number of singular value decomposition(SVD) operations and the dimension of the SVD matrix in the recursive procedure. The performance of the proposed algorithm is improved in terms of bit error rate and sum capacity of the system, especially in the highSNR regime.

Polar Coded Iterative Multiuser Detection for Sparse Code Multiple Access System

Polar coded sparse code multiple access(SCMA) system is conceived in this paper. A simple but new iterative multiuser detection framework is proposed, which consists of a message passing algorithm(MPA) based multiuser detector and a soft-input soft-output(SISO) successive cancellation(SC) polar decoder. In particular, the SISO polar decoding process is realized by a specifically designed soft re-encoder, which is concatenated to the original SC decoder. This soft re-encoder is capable of reconstructing the soft information of the entire polar codeword based on previously detected log-likelihood ratios(LLRs) of information bits. Benefiting from the soft re-encoding algorithm, the resultant iterative detection strategy is able to obtain a salient coding gain. Our simulation results demonstrate that significant improvement in error performance is achieved by the proposed polar-coded SCMA in additive white Gaussian noise(AWGN) channels, where the performance of the conventional SISO belief propagation(BP) polar decoder aided SCMA, the turbo coded SCMA and the low-density parity-check(LDPC) coded SCMA are employed as benchmarks.

Performance of Block Diagonalization Broadcasting Scheme for Multiuser MIMO System Operating in Presence of Spatial Correlation and Mutual Coupling

In this paper, the capacity of a multiuser Multiple Input Multiple Output (MIMO) system employing the block diagonalization broadcasting scheme in presence of spatial correlation and mutual coupling is investigated. It is shown by computer simulations that, in general, the presence of spatial correlation decreases the capacity of a multiuser MIMO system. However, for some particular antenna element spacing mutual coupling decreases the spatial correlation rendering an increased capacity. The optimized diagonalization broadcasting technique with a two-stage power allocation scheme is proposed and verified. The presented simulations results confirm the advantage of the proposed broadcasting scheme.