Dr Qu Luo

—In this paper, a novel uncoordinated random access (URA) protocol is presented to address the pressing demand for massive connectivity with low access latency in future massive machine type communication (mMTC) scenarios. The proposed URA scheme integrates the classical slotted ALOHA (S-ALOHA) protocol with sparse code multiple access (SCMA) technique, referred to as SCMA-empowered URA. Specifically, active users randomly choose an SCMA codebook to access the communication network in an arbitrary time slot whenever they want without scheduling. However, due to the lack of central coordination in the proposed URA scheme, SCMA codebook collisions become inevitable, making decoding challenging and leading to increased access failures. To cope with the decoding issue, an interference-canceling (IC) first decoding strategy is proposed at the access point (AP), which can partially tackles collision problems, contributing to a higher system throughput. Taking the proposed IC-first decoding strategy into account, a closed-form theoretical expression of the throughput is derived. Moreover, to alleviate the throughput degradation under the congested user traffic, a user barring mechanism is introduced to manage the traffic load. Firstly, a closed-form expression of idle codebook probability is developed to help indicate the system state, i.e., congested or not. Then, in addition to the estimated real-time load, the AP adaptively adjusts the access probability and redistributes the actual access load. Finally, simulation results demonstrate that the proposed SCMA-empowered URA scheme enjoys higher maximum throughput, compared to the conventional orthogonal multiple access (OMA) based URA scheme. Moreover, the accuracy of the presented theoretical analysis and the effectiveness of the user barring mechanism are verified. Index Terms—Massive machine type communication (mMTC), sparse code multiple access (SCMA), uncoordinated random access (URA), interference cancellation (IC), theoretical analysis, user barring design.

Sparse code multiple access (SCMA) and multiple input multiple output (MIMO) are considered as two efficient techniques to provide both massive connectivity and high spectrum efficiency for future machine-type wireless networks. This paper proposes a single sparse graph (SSG) enhanced expectation propagation algorithm (EPA) receiver, referred to as SSG-EPA, for uplink MIMO-SCMA systems. Firstly, we reformulate the sparse codebook mapping process using a linear encoding model, which transforms the variable nodes (VNs) of SCMA from symbol-level to bit-level VNs. Such transformation facilitates the integration of the VNs of SCMA and low-density parity-check (LDPC), thereby emerging the SCMA and LDPC graphs into a SSG. Subsequently, to further reduce the detection complexity, the message propagation between SCMA VNs and function nodes (FNs) are designed based on EPA principles. Different from the existing iterative detection and decoding (IDD) structure, the proposed EPA-SSG allows a simultaneously detection and decoding at each iteration, and eliminates the use of interleavers, de-interleavers, symbol-to-bit, and bit-to-symbol LLR transformations. Simulation results show that the proposed SSG-EPA achieves better error rate performance compared to the state-of-the-art schemes. Index Terms—Multiple input multiple output (MIMO), Sparse code multiple access (SCMA), factor graph, expectation propagation algorithm (EPA), iterative detection and decoding (IDD), single sparse graph (SSG).

Affine frequency division multiplexing (AFDM) is a promising chirp-assisted multicarrier waveform for future high-mobility communications. This paper is devoted to enhanced receiver design for multiple input and multiple output AFDM (MIMO-AFDM) systems. Firstly, we introduce a unified variational inference (VI) approach to approximate the target posterior distribution, under which the belief propagation (BP) and expectation propagation (EP)-based algorithms are derived. As both VI-based detection and low-density parity-check (LDPC) decoding can be expressed by bipartite graphs in MIMO-AFDM systems, we construct a joint sparse graph (JSG) by merging the graphs of these two for low-complexity receiver design. Then, based on this graph model, we present the detailed message propagation of the proposed JSG. Additionally, we propose an enhanced JSG (E-JSG) receiver based on the linear constellation encoding model. The proposed E-JSG eliminates the need for interleavers, de-interleavers, and log-likelihood ratio transformations, thus leading to concurrent detection and decoding over the integrated sparse graph. To further reduce detection complexity, we introduce a sparse channel method by approaximating multiple graph edges with insignificant channel coefficients into a single edge on the VI graph. Simulation results show the superiority of the proposed receivers in terms of computational complexity, detection and decoding latency, and error rate performance compared to the conventional ones.

—Satellite communications are crucial for the evolution beyond fifth-generation networks. However, the dynamic nature of satellite channels and their inherent impairments present significant challenges. In this paper, a novel post-compensation scheme that combines the complex-valued extreme learning machine with augmented hidden layer (CELMAH) architecture and widely linear processing (WLP) is developed to address these issues by exploiting signal impropriety in satellite communications. Although CELMAH shares structural similarities with WLP, it employs a different core algorithm and does not fully exploit the signal impropriety. By incorporating WLP principles, we derive a tailored formulation suited to the network structure and propose the CELM augmented by widely linear least squares (CELM-WLLS) for post-distortion. The proposed approach offers enhanced communication robustness and is highly effective for satellite communication scenarios characterized by dynamic channel conditions and non-linear impairments. CELM-WLLS is designed to improve signal recovery performance and outperform traditional methods such as least square (LS) and minimum mean square error (MMSE). Compared to CELMAH, CELM-WLLS demonstrates approximately 0.8 dB gain in BER performance, and also achieves a two-thirds reduction in computational complexity , making it a more efficient solution.

In this paper, we propose a novel active reconfig-urable intelligent surface (RIS)-assisted amplitude-domain reflection modulation (ADRM) transmission scheme, termed as ARIS-ADRM. This innovative approach leverages the additional degree of freedom (DoF) provided by the amplitude domain of the active RIS to perform index modulation (IM), thereby enhancing spectral efficiency (SE) without increasing the costs associated with additional radio frequency (RF) chains. Specifically, the ARIS-ADRM scheme transmits information bits through both the modulation symbol and the index of active RIS amplitude allocation patterns (AAPs). To evaluate the performance of the proposed ARIS-ADRM scheme, we provide an achievable rate analysis and derive a closed-form expression for the upper bound on the average bit error probability (ABEP). Furthermore, we formulate an optimization problem to construct the AAP codebook, aiming to minimize the ABEP. Simulation results demonstrate that the proposed scheme significantly improves error performance under the same SE conditions compared to its benchmarks. This improvement is due to its ability to flexibly adapt the transmission rate by fully exploiting the amplitude domain DoF provided by the active RIS. Index Terms—Active reconfigurable intelligent surface, amplitude-domain reflection modulation, average bit error probability , achievable rate.

As satellite communications play an increasingly important role in future wireless networks, the issue of limited link budget in satellite systems has attracted significant attention in current research. Although semantic communications emerge as a promising solution to address these constraints, it introduces the challenge of increased computational resource consumption in wireless communications. To address these challenges, we propose a multi-layer hybrid bit and generative semantic communication framework which can adapt to the dynamic satellite communication networks. Furthermore, to balance the semantic communication efficiency and performance in satellite-to-ground transmissions, we introduce a novel semantic communication efficiency metric (SEM) that evaluates the trade-offs among latency, computational consumption, and semantic reconstruction quality in the proposed framework. Moreover, we utilize a novel deep reinforcement learning (DRL) algorithm group relative policy optimization (GRPO) to optimize the resource allocation in the proposed network. Simulation results demonstrate the flexibility of our proposed transmission framework and the effectiveness of the proposed metric SEM, illustrate the relationships among various semantic communication metrics.

—Sparse code multiple access (SCMA) is a promising technique for future machine type communication systems due to its superior spectral efficiency and capability for supporting massive connectivity. This paper proposes a novel class of sparse codebooks to improve the error rate performance of SCMA in the presence of phase noise (PN). Specifically, we first analyze the error rate performance of SCMA impaired by looking into the pair-wise error probability. Then, a novel codebook design metric, called minimum PN metric (MPNM), is proposed. In addition, to design PN resilient codebooks, we propose a novel pulse-amplitude modulation (PAM)-based low projection mother constellation (LP-MC), called LP-PAM. The codebooks for different users are obtained by rotating and scaling the MC, where the phase rotation angles and scaling factors for different users are optimized by maximizing the proposed MPNM. Numerical results show that the proposed PNCBs have larger MPNM values and achieve improved error rate performance than the-state-of-the-art codebooks. Index Terms—Sparse code multiple access (SCMA), phase noise, codebook design, minimum phase noise metric (MPNM).

—In this letter, a novel class of sparse codebooks is proposed for sparse code multiple access (SCMA) aided non-terrestrial networks (NTN) with randomly distributed users characterized by Rician fading channels. Specifically, we first exploit the upper bound of bit error probability (BEP) of an SCMA-aided NTN with large-scale fading of different users under Rician fading channels. Then, the codebook is designed by employing pulse-amplitude modulation constellation, user-specific rotation and power factors. To further reduce the optimization complexity while maintaining the power diversity of different users, an orthogonal layer-assisted joint layer and power assignment strategy is proposed. Finally, unlike existing SCMA codebook designs that treat all users as one super-user, we propose to minimize the BEP of the worst user to ensure user fairness. The simulation results show that the proposed scheme is capable of providing a substantial performance gain over conventional codebooks.

Non-orthogonal multiple access (NOMA) is a promising candidate radio access technology for future wireless communication systems, which can achieve improved connectivity and spectral efficiency. Without sacrificing error rate performance, link adaptation combining with adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) can provide better spectral efficiency and reliable data transmission by allowing both power and rate to adapt to channel fading and enabling re-transmissions. However, current AMC or HARQ schemes may not be preferable for NOMA systems due to the imperfect channel estimation and error propagation during successive interference cancellation (SIC). To address this problem, a reinforcement learning based link adaptation scheme for downlink NOMA systems is introduced in this paper. Specifically, we first analyze the throughput and spectrum efficiency of NOMA system with AMC combined with HARQ. Then, taking into account the imperfections of channel estimation and error propagation in SIC, we propose SINR and SNR based corrections to correct the modulation and coding scheme selection. Finally, reinforcement learning (RL) is developed to optimize the SNR and SINR correction process. Comparing with a conventional fixed look-up table based scheme, the proposed solutions achieve superior performance in terms of spectral efficiency and packet error performance.

This paper focuses on the low-complexity multiuser detection of coded low-density signature (LDS) systems where the numbers of resources and users are both large. Typically, the detection complexity using the conventional message passing algorithm grows exponentially with the number of users occupied at each resource, making it unaffordable for large-scale LDS systems. To address this problem, we propose to apply orthogonal approximate message passing (OAMP) to detect LDS symbols with polynomial complexity. The numerical results demonstrate the superiority of the proposed method in terms of the error performance over the traditional turbo receiver.

—In this paper, we propose a novel composition aided generalized quadrature spatial modulation (C-GQSM) scheme to improve the spectral efficiency (SE) of the GQSM systems by exploiting the power domain degree of freedom. The C-GQSM scheme constitutes a hybridization of GQSM and composition modulation (CM) principles, allowing the information bits to encompass not only the antenna activation patterns (AAPs) and amplitude/phase modulated (APM) constellation symbols, but also the energy allocation patterns (EAPs). In addition, we present two low-complexity detection techniques for the proposed C-GQSM system. The first one is based on the ordered successive interference cancellation (OSIC) technique, while the other based on the weighted coordinate descent (WCD) algorithm. Moreover, the upper bound of the average bit error probability (ABEP) of the proposed C-GQSM scheme is derived under both uncorre-lated and correlated channel conditions. Simulation results show that the proposed C-GQSM outperforms both the conventional CM and GQSM systems in terms of SE without sacrificing the bit error rate (BER) performance. Index Terms—Generalized quadrature spatial modulation (GQSM), composition modulation (CM), average bit error probability (ABEP), low-complexity detector.

This paper conceives a novel sparse code multiple access (SCMA) codebook design which is motivated by the strong need for providing ultra-low decoding complexity and good error performance in downlink Internet-of-things (IoT) networks, in which a massive number of low-end and low-cost IoT communication devices are served. By focusing on the typical Rician fading channels, we analyze the pair-wise error probability of superimposed SCMA codewords and then deduce the design metrics for multi-dimensional constellation construction and sparse codebook optimization. For significant reduction of the decoding complexity, we advocate the key idea of projecting the multi-dimensional constellation elements to a few overlapped complex numbers in each dimension, called low projection (LP). An emerging modulation scheme, called golden angle modulation (GAM), is considered for multi-stage LP optimization, where the resultant multi-dimensional constellation is called LP-GAM. Our analysis and simulation results show the superiority of the proposed LP codebooks (LPCBs) including one-shot decoding convergence and excellent error rate performance. In particular, the proposed LPCBs lead to decoding complexity reduction by at least 97% compared to that of the conventional codebooks, whilst owning large minimum Euclidean distance. Some examples of the proposed LPCBs are available at https://github.com/ethanlq/SCMA-codebook.

In this paper, we propose a fluid antenna (FA) enabled joint transmit and receive index modulation (FA-JTRIM) transmission mechanism for reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) communication systems. By integrating the methodologies of FA and IM, the proposed scheme achieves enhanced spectral efficiency (SE) while requiring only a single radio frequency (RF) chain at both the transmitter and receiver. The proposed scheme offers a low hardware cost and power consumption transmission mechanism for the RIS-aided mmWave communication systems. Specifically, the encoding of information bits encompasses not only the modulated symbol but also the indices of transmit FA positions and receive antennas. To achieve a reliability-complexity trade-off, two types of detectors are introduced for the proposed FA-JTR-IM scheme, including the optimal maximum likelihood (ML) detector and two-step sequential (TSS) detector. Based on the ML detector, we derive the expression for the conditional pair-wise error probability of the proposed FA-JTR-IM scheme. Additionally, we provide the closed-form expressions for the unconditional PEP under the finite-path and infinite-path channel conditions, respectively. Simulation results demonstrate the superiority of the proposed FA-JTR-IM scheme in terms of error performance over its conventional benchmark schemes under the same SE condition

Sparse code multiple access (SCMA) is a promising non-orthogonal multiple access scheme for enabling massive connectivity in next generation wireless networks. However, current SCMA codebooks are designed with the same size, leading to inflexibility of user grouping and supporting diverse data rates. To address this issue, we propose a variable modulation SCMA (VMSCMA) that allows users to employ codebooks with different modulation orders. To guide the VM-SCMA design, a VM matrix (VMM) that assigns modulation orders based on the SCMA factor graph is first introduced. We formulate the VM-SCMA design using the proposed average inverse product distance and the asymptotic upper bound of sum-rate, and jointly optimize the VMM, VM codebooks, power and codebook allocations. The proposed VM-SCMA not only enables diverse date rates but also supports different modulation order combinations for each rate. Leveraging these distinct advantages, we further propose an adaptive VM-SCMA (AVM-SCMA) scheme which adaptively selects the rate and the corresponding VM codebooks to adapt to the users’ channel conditions by maximizing the proposed effective throughput. Simulation results show that the overall designs are able to simultaneously achieve a high-level system flexibility, enhanced error rate results, and significantly improved throughput performance, when compared to conventional SCMA schemes.

This paper studies the codebook design for sparse code multiple access (SCMA) based visible light communication (VLC) impaired by shot noise. By focusing on the typical Rician fading channels, we first derive a lower bound of the mutual information of VLC with shot noise and present a design metric called minimum normalized Euclidean distance (MNED). We then propose a novel codebook design approach for VLC including novel non-linear compensation (NLC) constellation and power scheduling matrix under the non-negative and real constraint. Simulation results demonstrate that our proposed codebook design leads to a higher MNED and thus significantly improved bit error performance over the existing SCMA codebooks for VLC systems.

This paper studies the affine frequency division multiplexing (AFDM)-empowered sparse code multiple access (SCMA) system, referred to as AFDM-SCMA, for supporting massive connectivity in high-mobility environments. First, by placing the sparse codewords on the AFDM chirp subcarriers, the input-output (I/O) relation of AFDM-SCMA systems is presented. Next, we delve into the generalized receiver design, chirp rate selection, and error rate performance of the proposed AFDM-SCMA The proposed AFDM-SCMA is shown to provide a general framework and subsume the existing OFDM-SCMA as a special case. Third, for efficient transceiver design, we further propose a class of sparse codebooks for simplifying the I/O relation, referred to as I/O relation-inspired codebook design in this paper. Building upon these codebooks, we propose a novel iterative detection and decoding scheme with linear minimum mean square error (LMMSE) estimator for both downlink and uplink channels based on orthogonal approximate message passing principles. Our numerical results demonstrate the superiority of the proposed AFDM-SCMA systems over OFDM-SCMA systems in terms of the error rate performance. We show that the proposed receiver can significantly enhance the error rate performance while reducing the detection complexity.