Multiuser Detection Method Research Articles

Active Terminal Identification, Channel Estimation, and Signal Detection for Grant-Free NOMA-OTFS in LEO Satellite Internet-of-Things

This paper investigates the massive connectivity of low Earth orbit (LEO) satellite-based Internet-of-Things (IoT) for seamless global coverage. We propose to integrate the grant-free non-orthogonal multiple access (GF-NOMA) paradigm with the emerging orthogonal time frequency space (OTFS) modulation to accommodate the massive IoT access, and mitigate the long round-trip latency and severe Doppler effect of terrestrial–satellite links (TSLs). On this basis, we put forward a two-stage successive active terminal identification (ATI) and channel estimation (CE) scheme as well as a low-complexity multi-user signal detection (SD) method. Specifically, at the first stage, the proposed training sequence aided OTFS (TS-OTFS) data frame structure facilitates the joint ATI and coarse CE, whereby both the traffic sparsity of terrestrial IoT terminals and the sparse channel impulse response are leveraged for enhanced performance. Moreover, based on the single Doppler shift property for each TSL and sparsity of delay-Doppler domain channel, we develop a parametric approach to further refine the CE performance. Finally, a least square based parallel time domain SD method is developed to detect the OTFS signals with relatively low complexity. Simulation results demonstrate the superiority of the proposed methods over the state-of-the-art solutions in terms of ATI, CE, and SD performance confronted with the long round-trip latency and severe Doppler effect.

Iterative NOMA Detection for Multiple Access in Satellite High-Mobility Communications

Non-orthogonal multiple access (NOMA) is a promising technology for next generation multiple access (NGMA). However, traditional NOMA detection methods cannot cope with challenges of NGMA in satellite high-mobility communications. On the one hand, due to the high mobility and heterogeneity of terminals in terms of the velocity and acceleration, time-varying Doppler shifts caused by high-mobility terminals are relatively higher and different for each user, which degrades the demodulation performance seriously and makes multi-user interference cancellation become the bottleneck. On the other hand, owning to wide distribution of high-mobility terminals, the arriving time of users’ signals is different at the receiver, which further incurs more difficulties for NOMA detection. To solve such a problem in satellite high-mobility communications, we propose a novel multi-user detection method based on the new three-dimensional (3D) factor graph for high-mobility environments, named the turbo iterative detection (TID) algorithm. Specially, the proposed algorithm consists of the interference cancellation loop, the Doppler elimination loop and the decoding loop. By means of message passing along edges in the proposed 3D factor graph, these three iterative loops can interact with each other to effectively eliminate time-varying Doppler shifts of heterogeneous high-mobility terminals and interference among multiple users. Simulation results show that the proposed algorithm improves the bit error ratio (BER) performance more than 0.9 dB with less computational complexity compared with traditional algorithms, which demonstrates the superiority of this algorithm in terms of the BER performance and computational complexity.

Joint Active User Detection and Channel Estimation Via Bayesian Learning Approaches in MTC Communications

To support the massive machine-type communications (mMTC) scenario for Internet of Things (IoTs) applications featured by large-scale device connectivity and low device activity, grant-free non-orthogonal multiple access (GF-NOMA) and compressive sensing (CS)-based multi-user detection methods (MUD) are developed. In this paper, we develop two Bayesian CS-based methods, i.e., sparse Bayesian Learning (SBL) and fast inverse-free sparse Bayesian Learning (FI-SBL), for joint MUD and channel estimation (CE) in GF-NOMA with Low-Activity Code Division Multiple Access (LA-CDMA) as the multiple access technology. SBL is investigated for robust MUD and CE by utilizing the parameterized Gaussian prior information. Then to resolve the high computational complexity of SBL, FI-SBL is proposed, which replaces matrix reversion operations with relaxed evidence lower bound. Simulation results show that the two proposed algorithms outperform the traditional methods, and FI-SBL reduces the computational complexity significantly.

Joint User Activity Identification and Channel Estimation for Grant-Free NOMA: A Spatial–Temporal Structure-Enhanced Approach

Exploiting the sparse nature of user activity, compressed sensing (CS) has been a powerful technique to realize efficient user detection in grant-free nonorthogonal multiple access (NOMA). However, most of the existing CS-based multiuser detection schemes merely independently incorporate the temporal correlation in frame-based transmission or spatial correlation induced by multiantenna reception, leading to unsatisfactory user detection performance. Driven by the observation in the CS theory that the signal recovery performance could be enhanced by an increased number of sparse vectors with a common support set, in this article, we propose a novel joint user activity identification and channel estimation (JUICE) framework by integrating the temporal correlation of active user sets with multiantenna reception, which could achieve superior user detection performance. Specifically, we first formulate the JUICE as a Kronecker CS (KCS) problem to model the CS measurement process, by fully extracting the spatial-temporal structure of user activity. Then, based on the mined spatial-temporal structure of user activity, an adaptive subspace pursuit algorithm is developed, i.e., spatial-temporal structure enhanced adaptive subspace pursuit (STS-ASP), which could realize efficient multiuser detection. A distinct advantage of the proposed algorithm is that it does not require any prior knowledge (e.g., the number of active users and the noise level), by adaptively acquiring the number of active users and employing the cross-validation technique to appropriately terminate the iterative procedures. Extensive experimental evaluation is conducted, and the results corroborate the superiority of the proposed framework compared with the existing CS-based multiuser detection methods.

Neural Network Based AMP Method for Multi-User Detection in Massive Machine-Type Communication

In massive machine-type communications (mMTC) scenarios, grant-free non-orthogonal multiple access becomes crucial due to the small transmission latency, limited signaling overhead and the ability to support massive connectivity. In a multi-user detection (MUD) problem, the base station (BS) is unaware of the active users and needs to detect active devices. With sporadic devices transmitting signals at any moment, the MUD problem can be formulated as a multiple measurement vector (MMV) sparse recovery problem. Through the Khatri–Rao product, we prove that the MMV problem is transformed into a single measurement vector (SMV) problem. Based on the basis pursuit de-noising approximate message passing (BPDN-AMP) algorithm, a novel learning AMP network (LAMPnet) algorithm is proposed, which is designed to reduce the false alarm probability when the required detection probability is high. Simulation results show that when the required detection probablity is high, the AMP algorithm based on LAMPnet noticeably outperforms the traditional algorithms with acceptable computational complexity.

Active user detection and channel estimation of uplink grant-free SCMA system based on variational free energy

<p indent=0mm>Joint message passing algorithm (JMPA) that is based on Bayesian theory is a multi-user detection method for the 5G unlicensed SCMA system. This method allows to pass messages in the factor graph until convergence to achieve probability approximation. However, owing to the closed loop of factor graph messaging, there is a possibility of non-convergence for active user detection and channel estimation based on JMPA, which is fatal to the reliability impact of 5G communication systems. This study analyzes the process of active user detection and channel estimation in the uplink grant-free SCMA system that is based on the variational method and derives the fixed point equations that solve the user active probability and channel gain posterior probability. Through the theoretical analysis of the system of equations, sufficient conditions for the convergence of the system of fixed-point equations are obtained. On the basis of the analysis results, the original iterative process is improved. The simulation results show that the improved algorithm is more robust than the original JMPA algorithm and achieves performance without degradation.

A Novel Multiuser Detector for LDPC-Coded DS-UWB Space Formation Flying

Space formation flying has attracted a lot of attention recently. In this paper, we using direct-sequence ultra-wideband (DS-UWB) as the physical layer of inter-spacecraft communications. The traditional multiuser detection method like soft-input soft-output (SISO) cost too much computation. The proposed multiuser detector no longer uses interleaving, and the computational complexity has a linear relationship with the number of users. The bit error ratio (BER) simulation result shows that the proposed method approaches the single-user system with increasing signal-to-noise ratios (SNRs).

Iterative Detection Based on Consensus Alternating Direction Method of Multipliers in Massive Machine-Type Communications

In massive machine-type communication systems, only some of devices usually transmit signals while the others remain silent. The conventional multiuser detection methods have been used with the aid of compressive sensing techniques, but their performance is far from the optimal one. In this paper, we propose an iterative signal detection method that jointly identifies the non-zero support and detects modulated symbols based on consensus alternating direction method of multipliers. Simulation results show that its performance is much better than the conventional detection methods and close to the lower-bound performance of the ideal detector in the case of high SNR.

Multiuser Detection for Nonlinear MIMO Uplink

For the multiple-input multiple-output (MIMO) uplink employing high-order quadrature amplitude modulation (QAM) signaling and with nonlinear high power amplifiers (HPAs) at mobile users’ transmitters, the existing multiuser detection methods can no longer be applied. We propose a novel nonlinear multiuser detection scheme for the nonlinear MIMO uplink. Specifically, we adopt an effective B-spline parameterization of the nonlinear transmit HPAs and derive an efficient and accurate algorithm to identify the nonlinear MIMO uplink channel, including the nonlinear B-spline model of the nonlinear transmit HPAs and the estimate of the linear MIMO channel matrix. Moreover, as the direct result of this nonlinear MIMO channel identification, the B-spline inverse model of nonlinear transmit HPAs can readily be identified. The nonlinear multiuser detection can be effectively implemented by the zero-forcing linear detection based on the estimated linear MIMO channel and followed by compensating the nonlinear distortion of the nonlinear transmit HPAs based on the estimated B-spline inverse model. An extensive simulation investigation is performed to demonstrate the effectiveness of our proposed nonlinear multiuser detection scheme for nonlinear MIMO uplink with high-order QAM signaling.

A robust blind adaptive multiuser detection based on maximum correntropy criterion in satellite CDMA systems

AbstractSatellite code‐division multiple‐access systems use multiuser detection (MUD) methods to deal with multiple‐access interferences. Among the different kinds of MUD, blind adaptive MUD regarding the system as a state‐space model is widely used for its tracking capability and independence of training sequences. The innovation process noise of the state‐space model is usually assumed to follow the Gaussian distribution, and the minimum mean‐square error criterion is the default criterion for most conventional blind adaptive MUD methods. In the past few years, the impulsive noise of the innovation process has attracted attention, declaring that a Gaussian distribution is not suitable for simulating the impulsive noise. Thus, more criteria are proposed to enhance the robustness of the blind adaptive MUD. This paper improves the robustness of MUD methods under impulsive noise by bringing forward a new cost function based on the maximum correntropy criterion and deduces the expression of the blind adaptive detector. Simulation results show that the proposed method achieves superior performance in terms of bit error rate, convergence, and robustness compared with other methods.

Variance Analysis of the New Method of Applying Multiuser Detection in a GPS Receiver in High Dynamic Conditions

Using a global positioning system receiver in high dynamic condition needs to apply some method to help the receiver keep tracking lock on the signal as possible as can. Because of some benefits of the vector tracking method in comparison to the scalar method in GPS tracking loops for keeping lock on the signal, the vector tracking method is considered. To increase the tracking accuracy in high dynamic conditions, using some method of multiuser detection in the vector tracking loop is proposed. The variance analysis showed the improvement in performance of the proposed method.

Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks.

High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity.

A new multiple input multiple output multi-carrier direct sequence code division multiple access system using T × T spreading with link budget analysis

High data rates and High Quality of Service QOS are the main requirements in Next Generation Networks NGNs. The communication channel needs to be shared in an efficient manner. An interesting technique is based on spread spectrum and orthogonal coding sequence called Code Division Multiple Access CDMA. Owing to performance and implementation complexity issues, multi-user detection methods are mainly restricted in high data transmission rate CDMA. In this paper, a low complex multi-user Multi-Carrier CDMA MC-CDMA receiver is proposed and implemented, which employs time T domain spreading at both coding and modulation ends and consequently increases the processing gain. The performance comparison of the proposed technique and the conventional schemes has been performed in terms of bit error rate. The results of the link budget analysis have been provided in terms of reports generated by link budget software of Bonsai Networks.

FPGA Implementation of Multi-User Detection Genetic Algorithm Tool for SDMA-OFDM Systems

Robust multi-user detection (MUD) methods based on space division multiple access (SDMA) techniques are essential to efficiently exploit the electromagnetic spectrum. In this paper, an adaptive Genetic Algorithm-based tool for SDMA-OFDM Systems (GASOS) is developed to improve the performance and computational complexity in cases of fully-loaded and overloaded multi-user scenarios. The data flow in GASOS is appropriate in pipelining and parallelization to reduce operational time. A new GASOS-based MUD hardware design for SDMA-OFDM systems is proposed using FPGA architecture. The design details are presented together with their planned operational modules. Resource utilization is optimized, and the total number of clock cycles required is found to be 15 initially, in addition to one clock cycle per member of algorithm population. A clock frequency of 100 MHz is used and implementation is carried out on Xilinx® Virtex-6 FPGA, built in the development platform ML605 edition with JTAG Hardware Co-simulation. According to the results obtained from the developed algorithm and implementation tools, a high number of users can be physically possible and provided with support. Real-time based implementation of MUD systems has the potential to play a major role in next-generation communication systems.

Power-Controlled Multicarrier and Multiuser Detection Techniques in Wireless CDMA Systems

This paper describes power-controlled multi carrier and multiuser detection techniques for Code Division Multiple Access (CDMA) systems. In conventional CDMA systems, a RAKE receiver is employed to overcome wireless channel effect due to frequency selective characteristics of wireless CDMA systems. Alternatively, multi carrier technique can also be used to overcome the effect of frequency selective channel. Conventional CDMA systems also employ single-user detection scheemes, in that interference between users, called the multiple access interference (MAI), is considered as interference which contributes to the statistics of detection variables affecting the quality of detection. Now, multiuser detection method is proposed to mitigate the inter user interference in CDMA systems. In multiuser detections, the MAI component can be eliminated or cancelled by the use of all user’s spreading code in the system to be available to each user. Another technique that is commonly employed in CDMA system is power control, to mitigate the effects of near-far and fading channel fluctuations. In this study, the basic concept of multi carrier and multiuser detection technique is described in a simple model and the performance for various number of users is simulated and evaluated. The performance of power-controlled multi-carrier and multiuser detection technique is then evaluated and compared with that of the singleuser detection to show a significant improvement.

Low‐complexity iterative interference cancellation multiuser detection based on channel selection and adaptive transmission

In this study, a new iterative interference cancellation (IIC) multiuser detection method is proposed for overloaded multiple-input multiple-output (MIMO) coded orthogonal frequency division multiplexing systems. A channel analyser is used to detect those channels for which the IIC detector will not converge. For these we propose two adaptive methods to enable detection. The first is to use a lower code rate for these channels. The second is to divide the transmitters into several groups which transmit in separate slots. Low-complexity matched filter is applied, and both successive interference cancellation and parallel interference cancellation are considered for interference reconstruction. The simulation results show that the proposed technique can achieve near-optimum bit error rate performance and optimum frame error rate performance, with lower complexity than optimum maximum-likelihood methods.

LMS Blind Adaptive Multiuser Detection for Underwater Acoustic Communication with MMSE and MOE Criteria

In order to solve detection of multi-user detection in underwater acoustic communication networks, blind adaptive multiuser detection method using LMS algorithm was proposed to solve the MAI problem of multi-user detection in underwater acoustic communication channel when users increase. Two type simulations were executed, including synchronous and asynchronous multi-user simulation analysis, to verify the validity of LMS multi-user detection algorithm and inspection machine. The verification of the effectiveness of the MMSE and MOE algorithm for LMS multi-user detection algorithm was done by simulation.

Research and Simulation on the Performance of Multi-User Detection for MC-CDMA System

The paper makes a brief introduction of Multiple Carrier- Code Division Multiple Access (MC-CDMA) scheme based on the principles of Orthogonal Frequency Division Multiplexing (OFDM) and CDMA, and a mathematical model of the uplink is established in MC-CDMA system. The simulation research on different multi-user detection methods in MC-CDMA system is implemented by using MATLAB software, and it also compares the impacts to system performance by several different multi-user detection methods, such as De-Correlation (DEC) multi-user detection, Minimum Mean Square Error (MMSE) multi-user detection and Parallel Interference Cancellation (PIC) multi-user detection, based on understanding and analyzing the experimental results. In addition, the paper also focuses on the research of multi level PIC multi-user detection performance in different primary detection methods and different series detections.

A hybrid multiuser detector based on MMSE and AFSA for TDRS system forward link.

This study mainly focuses on multiuser detection in tracking and data relay satellite (TDRS) system forward link. Minimum mean square error (MMSE) is a low complexity multiuser detection method, but MMSE detector cannot achieve satisfactory bit error ratio and near-far resistance, whereas artificial fish swarm algorithm (AFSA) is expert in optimization and it can realize the global convergence efficiently. Therefore, a hybrid multiuser detector based on MMSE and AFSA (MMSE-AFSA) is proposed in this paper. The result of MMSE and its modified formations are used as the initial values of artificial fishes to accelerate the speed of global convergence and reduce the iteration times for AFSA. The simulation results show that the bit error ratio and near-far resistance performances of the proposed detector are much better, compared with MF, DEC, and MMSE, and are quite close to OMD. Furthermore, the proposed MMSE-AFSA detector also has a large system capacity.

A Low-density Parity-check Codes LDPC based Hybrid Multiuser Detection Method for DS-UWB System

A Low-density Parity-check Codes LDPC based Hybrid Multiuser Detection Method for DS-UWB System