Multiuser Detection Research Articles

Realtime parallel software implementation of a DS-CDMA Multiuser Detector

In this article the complexity and runtime performance of two Multiuser Detectors for Direct Sequence-Code Division Multiple Access were evaluated in two different hardware platforms. The innovation and aim is to take advantage of present parallel hardware to bring Multiuser technology to present and future Base Stations in order to increase the capacity of the overall system, to reduce the transmission power by the mobile stations and to reduce base station hardware requirements, in Universal Mobile Telecommunications System. The detectors are based on the Frequency Shift Canceller concatenated with a Parallel Interference Canceller. This detector implies the inversion of multiple identical size small matrices and because of that it is very scalable contrary to other solutions/detectors that only permit a sequential implementation despite their lower complexity. Implementations for the Time Division–Code Division Multiple Access, in two software platforms one in OpenMP and the other in CUDA were done taking into account the carrier and doppler frequency offsets (offset different for each user). The result shows that this deployment aware real-time implementation of the Multiuser Detectors is possible with a Graphics Processor Unit being three times faster than required.

Multiuser Detection Schemes Based on Families of OMP and MUSIC Algorithms for Uplink Grant Free NOMA Wireless Communications Systems

Background and Objective: The Non-Orthogonal Multiple Access (NOMA) technology is a multi-access scheme that overcomes most of the disadvantages of its predecessor, the OMA technology. Specifically, NOMA technology supports massive connectivity of multiple users by employing the same non-orthogonal spectrum resource. In an uplink NOMA system with grant-free transmission mode, the Base Station (BS) is unaware of which users are active in the networks at a given time. Consequently, there is a need for mechanism to ensure successful recovery of users’ transmitted signals. This paper presents some new Multiuser Detector (MUD) schemes for uplink grant-free NOMA wireless communication networks with system’s model involving Multiple Measurement Vectors (MMV) rather than the Single Measurement Vector (SMV) that many previous works have considered. These MUDs include those that are based on differential Orthogonal Matching Pursuit (OMP), adaptive Simultaneous OMP (SOMP), compressive- multiple signal classification (MUSIC), and sequential compressive-MUSIC algorithms. Methods: The MUDs are employed in the detection of users’ signals in the uplink NOMA systems. Results and Discussion: Comparative performances of these MUDs with another one that is also based on the MMV system model, the SOMP-based MUD are presented for the scenarios when the system is under-loaded, fully loaded and over-loaded. Conclusion: The results suggest that the sequential compressive-MUSIC-based MUD, though shows weak performance at lower range of SNR, outperforms all the other MUDs including the SOMP-based MUD at higher SNR. Its performance is quite outstanding during the over-loaded scenarios, especially at higher SNR. However, its computational complexity is higher that the closely performing compressive-MUSIC-based MUD and SOMP-based MUD.

An Uplink Secure CB-NOMA with SIC Receiver for Wireless Applications

The nonorthogonal multiple access (NOMA) techniques are considered one of the main methods to realize the goals of 5G mobile and wireless systems such as link communication reliability and high user connectivity. Yet, when the amount of simultaneously connected users increases, many concerns will arise regarding the users’ data security. Various chaotic systems in the communication field have been presented to mitigate the data security concerns offering a cost-efficient technique to provide physical layer security. This work presents an uplink secure chaos-based NOMA (SCB-NOMA) system by exploiting the power domain. For signal modulation at the transmitters’ node, chaos shift keying is used, with controlled transmit power to satisfy the receiver conditions. For multiuser detection, the receiver side employs successive interference cancellation with chaotic demodulation. The efficiency of designed SCB-NOMA is demonstrated by considering different power control factors, system scenarios, and chaotic sequence length compared with different reference systems. It is shown that the efficient selection of the power allocation parameter has a direct effect on the bit error rate (BER) performance. Meanwhile, when the amount of power difference for the successive interference cancellation process is not adequate, the chaotic codes maintain the desired data security and enable robust BER performance for connected users. Besides, the correlation between the utilized chaotic codes has more impact on BER regardless of the considered sequence length.

An Efficient Matching Pursuit Based Compressive Sensing Detector For Uplink Grant-Free NOMA

In this paper, an efficient compressive sensing detector is proposed for uplink grant-free non-orthogonal multiple access (NOMA), where the indices and symbols of the active users are detected separately by using efficient matching pursuit (MP) based algorithms. Specifically, a low-complexity subspace MP (SMP) algorithm is designed for detecting the active user's indices, which is helpful for obtaining an initial estimated symbol vector. Then an efficient MP based symbol correcting mechanism (SCM) is designed for finding and correcting the erroneous results encountered in the initial result. Simulation results indicate that our proposed SMP based SCM (SMP-SCM) algorithm is capable of exhibiting better bit error rate (BER) performance over the oracle least squares (OLS) counterpart in the high SNR regime, which is always taken as a benchmark in conventional multi-user detection of grant-free NOMA system.

Deep Learning Empowered Semi-Blind Joint Detection in Cooperative NOMA

In this paper, we propose a multi-user symbol detection in cooperative-non-orthogonal multiple access (C-NOMA) schemes via deep learning (DL). We use a DL-based detection (DLDet) in both users instead of conventional detectors. Therefore, an iterative detector (i.e., successive interference canceler (SIC)) at the near user (UE1) and a combining plus optimum detector (i.e., maximum ratio combining (MRC) and maximum-likelihood (ML) detector) at the far user (UE2) are not required anymore. The proposed DLDet can detect symbols at the both users simultaneously. Besides, the DLDet does not require an additional channel estimation algorithm to acquire the channel state information (CSI) at the receivers. The multi-user symbol detection is performed based on the received pilot responses simultaneously, thus calling semi-blind. We train the proposed DLDet offline over Rayleigh fading channel and then, we use the offline-trained DLDet as an online detection algorithm. We compare the error performance of the DLDet with two benchmarks: conventional C-NOMA and threshold-based selective C-NOMA (TBS-C-NOMA). With the extensive simulations over Rayleigh fading channels, we reveal that the DLDet outperforms both C-NOMA and TBS-C-NOMA and achieves the full diversity order (i.e., 2). Besides, this performance gain is up to ~10 dB and ~3-7 dB in C-NOMA and TBS-C-NOMA, respectively, which is very promising for the energy-limited networks. Moreover, in order to improve the error performance of the C-NOMA, the TBS-C-NOMA introduces two disadvantages, which are a signaling overhead to obtain the optimum threshold value and a capacity performance decay due the silence of the relay when the threshold is not satisfied. To this end, without using a threshold, outperforming TBS-C-NOMA is essential to revoke these disadvantages. The DLDet accomplish this; hence, the power of the DLDet is unveiled in coping with the error propagation. Then, to reveal the robustness of the DLDet against different fading conditions, we use the offline-trained DLDet as an online detector over different fading channels (i.e., Nakagami- $m$ and Rician). We show that the DLDet outperforms conventional detectors over those fading channels and again outperforms the conventional C-NOMA and TBS-C-NOMA performances, although it is trained over Rayleigh fading channel. Indeed, the DLDet has better performance than the C-NOMA and TBS-C-NOMA even though they are assumed to have perfect CSI whereas the DLDet uses only a single pilot signal. The DLDet again provides the full diversity order (i.e., $2m$ for Nakagami- $m$ and 2 for Rician). This proves the robustness of the DLDet and shows that the DLDet performs well regardless of the fading conditions once it is trained for any fading channel.

A Survey: Nonorthogonal Multiple Access with Compressed Sensing Multiuser Detection for mMTC

One objective of the 5G communication system and beyond is to support massive machine type of communication (mMTC) to propel the fast growth of diverse Internet of Things use cases. The mMTC is aimed at providing connectivity to tens of billions of sensor nodes. The dramatic increase of sensor devices and massive connectivity impose critical challenges for the network to handle the enormous control signaling overhead with limited radio resources. Nonorthogonal multiple access (NOMA) is a new paradigm shift in the design of multiple user detection and multiple access. NOMA with compressive sensing‐based multiuser detection is one of the promising candidates to address the challenges of mMTC. The survey article is aimed at providing an overview of the current state‐of‐art research work in various compressive sensing‐based techniques that enable NOMA. We present characteristics of different algorithms and compare their pros and cons, thereby providing useful insights for researchers to make further contributions in NOMA using compressive sensing techniques. Nonorthogonal CDMA massive connectivity grant free medium access compressive sensing multiuser detection

Deep-Unfolded Sparse CDMA: Multiuser Detector and Sparse Signature Design

Sparse code division multiple access (SCDMA) is a promising non-orthogonal multiple access technique for future wireless communications. In SCDMA, transmitted symbols from multiple users are coded by their own sparse signature sequences, and a base station attempts to detect those symbols using the signature sequences. In this paper, we present a new deep-unfolded multiuser detector called a complex sparse trainable projected gradient (C-STPG) detector for SCDMA systems. Deep unfolding is a deep learning method that tunes trainable parameters in iterative algorithms using supervised data and deep learning techniques. The proposed detector provides a much superior detection performance over that of the LMMSE detector. Other advantages of the proposed detector include a low computational complexity in execution and a low training cost owing to the small number of trainable parameters. In addition, we propose a novel joint learning strategy called gradual sparsification for designing sparse signature sequences based on deep unfolding. This method is computationally efficient in optimizing a set of sparse signature sequences. Numerical results show that the gradual sparsification successfully yields sparse signature sequences with a smaller symbol error rate than those of randomly designed sparse signature sequences.

Limited-Search Chase Decoding Algorithm for LDPC Coded Underwater Acoustic Multiuser Channels

In this paper, we propose a low-complexity soft-input/soft-output (SISO) Chase multiuser detector that has a polynomial computational complexity in terms of the number of the least reliable bit positions for low-density parity-check (LDPC) coded code-division multiple-access (CDMA) systems, which is a potentially competitive technology for underwater acoustic networks (UWAN). Simulation results over highly correlated channels show that the proposed detector can afford searching over a larger number of the least reliable bit positions and achieve better bit-error-rate (BER) performance as compared with the Chase-II detector at much lower complexity.

An Adaptive FH/MC-CDMA to Improve Channel Quality for Multiuser Using Variable Code-Based Carriers

The adaptive variable code-based carriers for multiusers in a common channel of communication is a technique of Multi-Carrier Code Division Multiple Access (MC-CDMA). It is an advanced mode of communication, where multiple users are communicating with different code and a different carrier. The proposed adaptive frequency hopping technique in MC-CDMA will give high signal to noise ratio value mitigating multiple access interference. Proposed adaptive technique detects multi-users with the help of matched filters. The simulation of the above system is done with correlated sub-carriers in the presence of realistic fading channels and even imperfect channel state information for recovering at the transmitter. The performance of an improved allocation algorithm for MC-CDMA system with adaptive frequency hopping is investigated. Imperfect channel state information at the base station does not affect the performance of the proposed technique due to the combined allocation algorithm and multi-user detector employment. The above combination mitigates multiple access interference efficiently, and increases the system capacity in a significant way compared to non-adaptive variable code-based carrier system. The results of the simulation confirm the above said performance factors with realistic correlated sub carriers that are faded with practical communication system parameters.

MUSA Grant-Free Access Framework and Blind Detection Receiver

Recently, a non-orthogonal multiple access scheme called multi-user shared access (MUSA) was proposed to provide massive connection capability of low-complexity devices in the 5G networks. MUSA achieves higher spectral efficiency allowing independent devices to transmit data on the same physical layer time-frequency resources. Furthermore, MUSA introduces a grant-free transmission and a blind multi-user detection at the receiver, reducing the complexity on the transmit side. This approach is interesting for Internet of Things applications over mobile communication networks, where the devices have limited power and processing capacity. The references available in the literature about this multiple access scheme do not bring sufficient details about the MUSA multi-user detector. This limitation makes it difficult to evaluate the MUSA performance and to propose improvements for this new technique. The main goal of this paper is to provide a framework describing the entire communication chain using MUSA as multiple access. This paper also brings a proposal for a blind multi-user detection, where the information about the MUSA parameters and the channel state information are unknown at the receiver side. The performance of the MUSA multi-user detector is improved by a deep learning based processing that improves the quality of the channel estimation provided by a initial minimum mean square error estimator. The proposed deep neural network architecture employed to improve the channel estimation allows more users to share the same time-frequency resources for a given target block error rate, increasing the overall spectrum efficiency of the system.

An Error Rate Comparison of Power Domain Non-Orthogonal Multiple Access and Sparse Code Multiple Access

Non-orthogonal Multiple Access (NOMA) has been envisioned as one of the key enabling techniques to fulfill the requirements of future wireless networks. The primary benefit of NOMA is higher spectrum efficiency compared to Orthogonal Multiple Access (OMA). This paper presents an error rate comparison of two distinct NOMA schemes, i.e., power domain NOMA (PD-NOMA) and Sparse Code Multiple Access (SCMA). In a typical PD-NOMA system, successive interference cancellation (SIC) is utilized at the receiver, which however may lead to error propagation. In comparison, message passing decoding is employed in SCMA. To attain the best error rate performance of PD-NOMA, we optimize the power allocation with the aid of pairwise error probability and then carry out the decoding using generalized sphere decoder (GSD). Our extensive simulation results show that SCMA system with “ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5\times 10$ </tex-math></inline-formula> ” setting (i.e., ten users communicate over five subcarriers, each active over two subcarriers) achieves better uncoded BER and coded BER performance than both typical “ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1\times 2$ </tex-math></inline-formula> ” and “ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times 4$ </tex-math></inline-formula> ” PD-NOMA systems in uplink Rayleigh fading channel. Finally, the impacts of channel estimation error on SCMA, SIC and GSD based PD-NOMA and the complexity of multiuser detection schemes are also discussed.

Control Efficient Power Allocation of Uplink NOMA in UAV-Aided Vehicular Platooning

Power allocation in non-orthogonal multiple access (NOMA) systems is essential to avoid multi-user detection failure. However, controlling the uplink transmission power brings extra signaling overhead, especially in dynamic environments. In this paper, we investigate the uplink transmission power allocation problem in an unmanned aerial vehicle (UAV)-aided platooning NOMA system, where the UAV acts as a relay to assist inter-vehicle communications. Platoon vehicles are admitted to the same vehicle-to-UAV (V2U) channel via our proposed sequence-based power allocation (SPA) strategy. Instead of achieving the optimal energy efficiency, our goal is to design a simple yet effective power control scheme. Specially, in SPA strategy, vehicles determine their transmission power according to their positions in the platoon. Considering platoon dynamics due to vehicle mobility, a power-reserved mechanism is further incorporated in the proposed strategy to pre-allocate power resources for newly joined vehicles. In addition, a power-moving mechanism is further employed to guarantee the uplink signal-to-interference-plus-noise ratio (SINR) of vehicles by changing vehicle transmission power into higher levels during vehicle leaving a platoon. As the system only needs to update vehicle positions for the SPA strategy, only a small amount of signaling is required in our power allocation strategy. Extensive simulation results are provided to demonstrate that the proposed SPA strategy ensures the required SINR of platoon communication in different dynamic scenarios.

Robust RF Mixture Signal Recognition Using Discriminative Dictionary Learning

RF signal recognition is an important element toward RF situational awareness and dynamic spectrum management. In this work, machine learning-based signal recognition algorithms are proposed. Our key contribution is to engineer feature learning such that the classifiers can perform robustly even when a mixture of heterogeneous signal classes is observed, although the training is still done using non-mixture single-label samples. To achieve this, discriminative dictionary learning algorithms are developed with various feature-shaping constraints. The signal detection can then be done in a way reminiscent of the multi-user detection in wireless communication, employing linear equalizers. The algorithms are tested using real wideband RF measurement data. It is verified that the proposed algorithms can robustly classify the component signals even when their powers are widely different and their number is not known a priori.

Low Complexity Decoding Algorithm for Uplink SCMA Based on Aerial Spherical Decoding

As a new non-orthogonal multiple access technology for 5G massive machine type communication scenario, the sparse code multiple access (SCMA) has greatly improved the spectrum efficiency due to the high connection density. SCMA combines QAM (Quadrature Amplitude Modulation) modulation and sparse spreading into a codebook set to obtain forming gain. The user binary bit data is directly mapped into multi-dimensional codewords in the transmitter. The receiver uses the message passing algorithm (MPA) for multi-user detection to achieve efficient decoding. However, MPA is a good solution for SCMA, though its high complexity limits the application in practical systems. In order to reduce the complexity of MPA, this paper proposed a low-complexity decoding algorithm based on the serial spherical decoding message passing algorithm (SSD-MPA), which greatly enhanced the practicability of the SCMA system. The SSD-MPA took into account the distribution characteristics of the Gaussian noise and the reliability of the constellation points, and only updates the trusted constellation point messages of nodes within the spherical radius. At the same time, it used a serial strategy to speed up the convergence rate. The simulation results have shown that when the radius sets properly, the algorithm reduces the complexity by about 2/3 compared with the original MPA, and the performance was almost lossless.

SCMA Codebook Design Based on Divided Extended Mother Codebook

Sparse code multiple access (SCMA) is one of the competitive non-orthogonal multiple access (NOMA) techniques for the next generation communication systems. In this paper, we put forward a simple and efficient design method named divided extended mother codebook (DEMC) to construct SCMA codebooks based on golden angle modulation (GAM) constellation points. First, we generate a vector defined by the GAM. Second, we design the extended mother codebook ( $\mathbf {EMC}$ ) by introducing the power and phase dependent constraints of symbols in multi-dimension codewords. The power constraints can ensure the power of each codeword is the same which leads to the optimal peak to average power ratio (PAPR) especially for the uplink channel. Third, we divide the $\mathbf {EMC}$ into several mother codebooks ( $\mathbf {MC}\text{s}$ ) to generate the constant bit rate (CBR) or variable bit rate (VBR) SCMA codebooks. The structure of the VBR SCMA codebooks is compatible with that of CBR. The VBR codebooks and CBR codebooks use the same factor graph, therefore, the users employed the VBR codebooks can also utilize the efficient message passing algorithm (MPA) for multi-user detection. Simulations reveal that the bit error rate (BER) performance of the proposed CBR DEMC-SCMA codebooks is outstanding with low complexity. The VBR DEMC-SCMA codebooks can flexibly satisfy the different service requirements, and the BER performance of the VBR DEMC-SCMA codebooks is close to each other though their modulation orders are various. This feature shows that the users can apply for a high order codebook to get a faster information transfer rate without increasing transmission power and bandwidth.

Uplink SCMA Codebook Reuse Transmission and Reception Scheme

Sparse code multiple access (SCMA) is a new non-orthogonal multiple access scheme suitable for 5G communication, which can effectively improve spectrum efficiency and support massive connections. Multiple users in the SCMA system realize the sharing of the same time-frequency resources by mapping data into codewords of a special code book (Code Book, CB). A typical SCMA system increases the spectrum utilization to 150%. In order to further improve the system spectrum utilization and increase the number of user connections, this paper proposes an uplink SCMA codebook reuse transmission and reception scheme (CB-Reuse-SCMA), which reuse a codebook to multiple users. The base station allocates <i>β</i> users to each codebook at the same time, so that <i>β</i> users use the same codebook to transmit uplink information. On the receiver of the base station, an improved Logarithmic Message Passing Algorithm (Log-MPA) is designed for multi-user detection, so that the base station can correctly detect the data of <i>β</i> users who reuse the same codebook. Simulation results show that at the time <i>β</i> = 2, the proposed scheme increased the spectrum utilization to 300%; at the time <i>β</i> = 3, the proposed scheme increased the spectrum utilization to 450%. Compared with the traditional SCMA scheme where the user has an exclusive codebook, the proposed scheme improves the spectrum utilization to <i>β</i> × 150% through codebook reuse at the expense of a small amount of SNR gain, which improves the throughput and user connection by <i>β</i> times number.

Binary Golay Spreading Sequences and Reed-Muller Codes for Uplink Grant-Free NOMA

Non-orthogonal multiple access (NOMA) is an emerging technology for massive connectivity in machine-type communications (MTC). In code-domain NOMA, non-orthogonal spreading sequences are uniquely assigned to all devices, where active ones attempt a grant-free access to a system. In this paper, we study a set of user-specific, non-orthogonal, binary spreading sequences for uplink grant-free NOMA. Based on binary Golay complementary sequences, each spreading sequence provides the peak-to-average power ratio (PAPR) of at most 3 dB for multicarrier transmission. Exploiting the theoretical connection to Reed-Muller codes, we conduct a probabilistic analysis to search for a permutation set for Golay sequences, which presents theoretically bounded low coherence for the spreading matrix. Simulation results confirm that the maximum PAPR of transmitted multicarrier signals via the spreading sequences is significantly lower than those for random bipolar, Gaussian, and pseudo-random sequences. Thanks to the low coherence, the performance of compressed sensing (CS) based joint channel estimation and multiuser detection using the spreading sequences turns out to be superior or similar to those for random bipolar, Gaussian, pseudo-random, and Zadoff-Chu sequences. The binary Golay spreading sequences have only two phases regardless of the sequence length, which can make them suitable for low cost MTC devices.

Performance Analysis of Sliding Window Multiuser Detectors Used in Asynchronous Ds-cdma Systems (Dept.E)

In this paper, the sliding-window method is applied on both decorrelating and linear minimum mean-squared error (LMMSE) multiuser detectors. The analytical expressions for the error probability of those multiuser detectors (MUDs) are derived. The analysis is presented for asynchronous direct sequence code-division multiple access (DS-CDMA) in additive white Gaussian noise (AWGN) and multipath fading environment. The adopted detectors divide the received signal stream into processing windows and process them window by window. The effects of expanding the processing-window length on the error probabilities are investigated. The analysis shows that the error performance of the decorrelating detector is much better than that of the LMMSE detector when the power of the interfering users is larger than the desired user power. It is also shown that the performance of the presented detectors will be significantly improved with processing-window length up to four symbols.

Low-Complexity Address Generation for Multiuser Detectors in IDMA Systems

This paper presents a low-complexity address generation unit (AGU) for multiuser detectors in interleave division multiple access (IDMA) systems. To this end, for the first time, all possible options for designing AGUs are first analyzed in detail. Subsequently, a complexity reduction technique is applied to each of those architectures. More specifically, some components in AGUs are relocated to make them shareable and removable without affecting the functionality. The complete transparency of such renovation makes it applicable to any existing multiuser detector without tailoring the interfacing components therein. Measuring the hardware complexity, all the resulting AGUs are compared with each other, and a new architecture simpler than the state-of-the-art one is developed. Implementation results in a 65 nm CMOS process, demonstrating that the proposed AGU can alleviate the equivalent gate count and the power consumption of the prior process by 13% and 31%, respectively.

An efficient and robust multi-user detection in IDMA system

Multi-user detection (MUD) is a popular method in wireless communication systems to enhance efficiency by together processing the signals received from all users. The complexity of MUD has been a great problem in practical scenario. Wiener (optimum) filter yields best estimate of the input signal from noisy observations. In this paper, using Wiener filtering, a less complex and robust MUD strategy is introduced in a new multiple access scheme called interleave-division multiple-access (IDMA) which supports MUD in a simple way. The proposed IDMA system helps in achieving lower bit error rate and manages multiple number of users easily when compared to other multiple access schemes.