Modular extremely large-scale array (mXL-array) represents a novel architecture for the extremely large aperture array (ELAA), offering extended coverage and significantly enhanced spatial resolution in near-field communication scenarios due to its unique modular array structure and flexible deployment capabilities. This paper is the first study to explore the potential of mXL-array in enhancing covert performance in the near-field communication. We design a sub-module-connected hybrid beamforming architecture to maximize the covert transmission rate conditional on only imprecise location information of Willie is available. First, a computationally efficient algorithm incorporating alternating direction method of multipliers and majorization-minimization (ADMM-MM) is developed to derive a closed-form solution for the fully digital beamforming vector. Subsequently, we obtain the baseband digital beamforming vector and the analog beamforming matrix by employing an alternating optimization (AO) algorithm. Simulation results demonstrate the excellent spatial beamforming control capability of the proposed algorithm. Specifically, even when Willie is positioned between Alice and Bob, the proposed algorithm enables the beam to avoid the region occupied by Willie while focusing the main beam toward Bob, thereby significantly improving the covert transmission rate. In addition, the superior performance of the proposed schemes, compared to existing benchmark algorithms, is verified through numerical simulations.

Clock synchronization is a critical technology in wireless sensor networks (WSNs), providing the foundation support for various operations among network nodes. However, traditional timestamp-based synchronization methods suffer from insufficient synchronization accuracy and high communication overhead, making it difficult to meet the requirements of high-precision applications. Meanwhile, frequent information exchange significantly increases network energy consumption and limits the network lifespan. To address these issues, we propose an implicit synchronization estimation method based on pulse correlation detection. This method operates at the physical layer, leveraging the excellent correlation properties of pulse signals to avoid the frequent information exchanges required in traditional timestamp-based synchronization, thereby reducing communication overhead. Based on this, the phase offsets of active nodes are estimated and quantized, and then transmitted to the listening nodes by using pulse position modulation (PPM) technology. Finally, high - precision synchronization between the listening node and the reference node is achieved. The simulation results confirm the validity of our analysis.

Integrated sensing and communication (ISAC), which can exploit the wireless spectrum for concurrent sensing and communication functions, is regarded as a promising technology for the future sixth generation (6G) wireless communication networks. This paper proposes a robust beam tracking method for maneuverable unmanned aerial vehicles (UAVs) with jittering effect within the ISAC framework. By utilizing reflected echoes, the kinematic parameters are measured and the interacting multiple model with extended Kalman filter (IMM-EKF) is designed for robust beam tracking of maneuverable UAVs. Furthermore, due to the jittering effect, the UAV may not point to the optimal alignment direction. To this end, we propose the coordinate descent particle swarm optimization (CDPSO) algorithm to balance the jittering effect by maximizing the received signal-to-noise ratio (SNR) of the UAV. The effectiveness of the proposed scheme is verified via simulation results.

Currently, traditional network passive defense mechanisms like firewalls prove inadequate against the escalating sophistication of cyber threats. There is an urgent need for more advanced proactive defense strategies, such as network security situation prediction (NSSP). NSSP aims to predict the future development of network through historical and current data. Nevertheless, the majority of existing prediction approaches are capable of achieving either short-term or long-term prediction individually, yet there remains a need for enhancing prediction speed to meet the requirements for practical deployment. Therefore, This paper proposes an integrated long and short-term prediction method called RSMHA. This approach draws on Split-Attention Networks (ResNeSt) and Multi-Head Attention (MHA) to maximize feature extraction capabilities and comprehensively enhance both long-term and short-term prediction abilities. The methods chosen in RSMHA are highly efficient, allowing for a streamlined model structure and enhanced running speed. We evaluated RSMHA using both a real-world intrusion detection system (IDS) alert dataset and the UNSW-NB15 dataset. The experimental results demonstrate that, in comparison to other state-of-the-art methods, our RSMHA approach reduces the prediction error to a certain extent while maintaining a comparable prediction accuracy, and realizes a significant enhancement in prediction speed.

Sparse code multiple access (SCMA) and mobile edge computing (MEC) can greatly enhance the capabilities of IoT networks by providing massive connectivity and timely computation. The paper presents a model and analysis of the performance for a large-scale grant-free (GF) SCMA aided MEC network. Firstly, stochastic geometry is used to derive closed-form solutions for offloading probability and SCMA ergodic rate. Then, the impact of SCMA on task completion time and energy cost in MEC networks is studied using queueing theory. Simulation results verify the validity of the theoretical expression and demonstrate that SCMA has advantages over orthogonal multiple access (OMA) in improving the offloading probability and ergodic rate, and reducing task latency and energy cost.

Orthogonal time frequency space (OTFS) has attracted a lot of attention as a feasible waveform applied in joint communication and radar (JCR) systems in contrast to orthogonal frequency division multiplexing (OFDM) waveform. To explore the advantages of OTFS waveform, first, a unified matrix (UM) expression is summarized by utilizing discrete fractional Fourier transform (DFrFT), and then a novel OTFS waveform based on UM expression is investigated in this article. The fractional order parameters of the proposed UM-OTFS waveform is set to the same values during preprocessing and Heisenberg transformation stages, and the UM-OTFS waveform can be converted into other waveform forms by undergoing different fractional order parameters. In addition, a three-stage sensing parameter estimation algorithm is developed for target velocity and range estimation through grid partitioning, coarse and fine estimation. Meanwhile, a low-complexity fractional zero force (ZF) or minimum mean square error (MMSE) equalizer based on lower-upper (LU) decomposition (LU-ZF/MMSE) is presented, which results in a log-linear order of complexity without any performance degradation of bite error ratio (BER) by analyzing sparsity and quasi-banded structure of the equivalent matrix. The simulation results indicate the superiority of the proposed UM-OTFS waveform in terms of sensing parameter estimation and BER performance compared with several advanced waveforms.

Sparse code multiple access (SCMA) and mobile edge computing (MEC) are two promising technologies for future Internet of Things (IoT) networks. SCMA enables large-scale connections, while MEC brings computing resources closer to user devices, resulting in faster response time and improved user experiences through task offloading. In this article, we investigate a large-scale grant-free (GF) SCMA enhanced MEC network. First, we propose the offloading protocol for the GF-SCMA enhanced MEC framework and describe the task offloading process using GF-SCMA in detail. Then, we model and analyze the performance of this network, deriving closed-form solutions for the offloading probability and SCMA ergodic rate using stochastic geometry. Additionally, we apply queueing theory to examine the impact of GF-SCMA on task latency and energy consumption in the MEC network. The accuracy of the theoretical expressions is confirmed by simulation results, demonstrating that SCMA outperforms orthogonal multiple access (OMA) in terms of increasing offloading probability and ergodic rate, as well as reducing task delay and energy consumption. Furthermore, this advantage becomes more pronounced with higher user density and task generation rate. Through parameter comparison, it is seen that increasing the pilot and codebook number of GF-SCMA can improve the performance of the proposed scheme in practical implementations.

This work presents a novel K-Repetition based Hybrid Automatic Repeat reQuest (HARQ) scheme for uplink sparse code multiple access (SCMA) systems. Our core idea is to apply network coding (NC) principle to re-encode different packets (after channel coding and interleaving) or their fragments, where K-Repetition is an emerging HARQ technique (recommended in 3GPP Release 15) for enhanced reception in future massive machine-type communications. Such a proposed scheme is referred to as the NC aided K-repetition SCMA (NCK-SCMA) in this paper. We aim to understand the optimal NCK-SCMA design criteria for maximizing the channel diversity as well as the efficient receiver processing for superior error rate performances. It is found that NC can enable a larger diversity order for NCK-SCMA with fewer resources (i.e., higher spectrum efficiency). Toward this objective, some novel design criteria are developed for the efficient configuration of NCK-SCMA. Moreover, we propose an iterative network decoding and SCMA detection (INDSD) algorithm for robust and low-complexity recovery of the transmit data from a low-density parity-check (LDPC) coded uplink NCK-SCMA system. Simulation results demonstrate that the proposed NCK-SCMA lead to higher throughput and improved reliability over the conventional K-SCMA.

Integrating sparse code multiple access (SCMA) and mobile edge computing (MEC) into the Internet of Things (IoT) networks can enable efficient connectivity and timely computation for resource-limited IoT users. This paper studies the computation rate maximization problem under task deadline constraints in dynamic SCMA-MEC networks. Specifically, we propose a predictive deep Q-network for SCMA resource allocation and computation offloading (PQ-RACO) algorithm for single-cell scenarios, where IoT devices use long short-term memory (LSTM) networks to predict the states and actions of other agents. However, the PQ-RACO algorithm is not scalable for increasing numbers of IoT devices. To address this issue, an improved multi-agent deep Q-network for SCMA resource allocation and computation offloading algorithm (MQ-RACO) is proposed for multi-cell scenarios. The algorithm is a centralized training and decentralized execution (CTDE) multi-agent reinforcement learning (MARL) algorithm with explicit rewards, which is tailored to the special structure of joint rewards. Simulation results demonstrate that the proposed algorithm outperforms several state-of-the-art MARL algorithms and other benchmark schemes in terms of convergence speed and computation rate.

Abstract In this paper, a joint detection strategy of Willie based on two phases observation is proposed and an energy‐efficient covert communication scheme with an adaptive assist nodes group (AANG) based on uniform jamming power (UJP) strategy is proposed to against the joint‐phase detection of Willie, which achieves covert communication with lower energy cost and higher average covert rate (ACR). The probability of detection error (PDE) at Willie with joint‐phase detection and ACR are derived. Furthermore, the optimal power allocation of legitimate transmitters is resolved to maximize ACR. Numerical results demonstrate the benefit of the proposed scheme over the covert rate and consumed jamming power.

To defend against eavesdropping and spoofing attacks, the physical layer authentication (PLA) techniques utilize the unique attributes of channel or device for identifying attackers. Among these techniques, the PLA schemes based on channel phase responses use the secret key driven channel phase to authenticate the legitimate user, which have a better performance than the channel amplitude based schemes. However, the prior phase-based schemes only consider the perfect channel correlation coefficient between the two successive timeslots, which differs from the real scenarios. Meanwhile, the closed-form expressions of the theoretical analysis results are not comprehensive in the prior schemes, which are also not tight especially at low signal-to-noise ratio (SNR) regions. In this paper, we propose a PLA scheme based on the channel phase response, aiming to offset the performance loss introduced by the channel correlation coefficient. Moreover, we derive the closed-form expressions of the theoretical analysis results, such as the mean value, the variance and the probability density functions (PDFs), which can be utilized to provide the closed-form threshold for making decision instead of a great ideal of testing. Then, the security analysis is provided to verify the resistance of the proposed scheme under the attacks. Simulation results show that the proposed scheme outperforms the benchmarks and the proposed theoretical results match well with the simulated results even under low SNR regions.

The application of sparse code multiple access (SCMA) to multi-access edge computing (MEC) networks can provide massive connections as well as timely and efficient computation services for resource-constrained Internet of Things (IoT) devices. This paper investigates the maximization of computation rate in SCMA-MEC networks under a dynamic environment. We first formulate an initial optimization problem to maximize the long-term computation rate of IoT devices under task delay constraints. Then, a joint computation offloading and SCMA resource allocation algorithm based on long short-term memory (LSTM) network and dueling deep Q network (DQN) is proposed. Specifically, each IoT device acts as an agent in the algorithm. Since each device can only observe part of the environment state, the LSTM network is used to predict the states of other devices. The computation rate of devices is taken as a reward to conduct action exploration in dueling DQN, and then the near-optimal computation offloading decision, SCMA codebook allocation, and power distribution of IoT users are obtained after training. Numerical simulation results demonstrate that the proposed algorithm can achieve higher computation rate compared with other baseline schemes.

With the considerable success achieved by modern fuzzing infrastructures, more crashes are produced than ever before. To dig out the root cause, rapid and faithful crash triage for large numbers of crashes has always been attractive. However, hindered by the practical difficulty of reducing analysis imprecision without compromising efficiency, this goal has not been accomplished.

Abstract In order to counter the double attack with wardens and eavesdroppers in the practical scenario, a distributed transmission scheme with security and covertness is proposed, which combines coding techniques and transmission protocol. The covert message is encoded by rateless codes and transmitted embedded in normal frames. The security is based on the random essence of rateless coding, and the covertness is achieved by ignoring the error frames and maintaining the signal waveform. The inter‐collusion between multiple wardens and eavesdroppers greatly increases the potential security hazards, which is first discussed in this paper. The authors can counter the inter‐collusion attack by adjusting the ratio of covert frame transmission in the distributed transmission scheme with security and covertness. Compared with the related work, this paper has many advantages, such as good robustness, lower extra complexity, and the insurance of the performance for both normal message and covert message. The analysis and simulation results show that our distributed transmission scheme with security and covertness can achieve both covertness and security based on the effective design under the existing communication system.

Abstract With the rapid development of wireless communication, the use of the inherent features of wireless channels to enhance and supplement existing security mechanisms has attracted widespread attention. In this work, a key generation scheme based on power allocation optimisation is proposed. The subchannel state information obtained from channel probing is employed to allocate signal power. Furthermore, an improved channel probing process is designed to implement the optimisation scheme of power allocation. Theoretical analysis and simulation results show that this optimisation scheme can obtain higher key capacity, and the superiority is more prominent when the signal‐to‐noise ratio is low. Besides, the key bits mismatch rate of the proposed optimisation scheme is decreased and the corresponding key generation rate is higher compared with the benchmark.

Grant-free sparse code multiple access (GF-SCMA) is considered to be a promising multiple access candidate for future wireless networks. In this article, we focus on characterizing the performance of uplink GF-SCMA schemes in a network with ubiquitous connections, such as the Internet-of-Things (IoT) networks. To provide a tractable approach to evaluate the performance of GF-SCMA, we first develop a theoretical model taking into account the property of multiuser detection (MUD) in the SCMA system. Then, the error rate performance of GF-SCMA in the case of codebook collision is analyzed to investigate the reliability of GF-SCMA when reusing codebook in massive IoT networks. For performance evaluation, accurate approximations for both success probability and average symbol error probability (ASEP) are derived. To elaborate further, the analytical results are utilized to discuss the impact of codeword sparse degree in GF-SCMA. After that, we conduct a comparative study between SCMA and its variant, dense code multiple access (DCMA), with GF transmission to offer insights into the effectiveness of these two schemes. This facilitates the GF-SCMA system design in practical implementation. Simulation results show that denser codebooks can help to support more user equipments (UEs) and increase the reliability of data transmission in a GF-SCMA network. Moreover, a higher success probability can be achieved by GF-SCMA with denser UE deployment at low detection thresholds since SCMA can achieve overloading gain.

Sparse code multiple access (SCMA) is a kind of code-domain nonorthogonal multiple access (NOMA) scheme, which can support the increasing requirements for high spectral efficiency and massive connections. Meanwhile, multiaccess edge computing (MEC) is a promising technology for providing resource-constrained users with computing resources. In this article, we propose a novel optimization scheme in the SCMA-based MEC network from the perspective of energy and latency for the Internet of Things (IoT) devices. Specifically, a system utility is first used to calculate the weighted energy consumption and task execution latency. The initial utility minimization problem is nonconvex and then can be subdivided into two tractable subproblems by fixing task offloading decisions, namely, optimal local computing via CPU frequency scheduling and optimal edge computing via the SCMA codebook assignment, subcarrier power allocation, and MEC server computing resources distribution. Primarily, a joint SCMA codebook assignment based on the bidirectional matching principle and optimal power allocation algorithm is proposed. Moreover, we come up with CPU frequency scheduling strategies utilizing convex optimization to optimize the computing resources allocation (CRA) of local devices and the MEC server. Finally, a low-complexity task offloading policy based on simulated annealing is presented. Numerical results show that our proposed joint optimization algorithm for resource allocation and task offloading can achieve a good compromise between time delay and energy consumption for IoT devices. It is demonstrated that the proposed strategy has a remarkable advantage compared to the previous SCMA-MEC schemes.

Sparse code multiple access (SCMA) is a kind of code-domain non-orthogonal multiple access (NOMA) scheme, which can support the increasing requirements for high spectral efficiency and massive connections. Meanwhile, multi-access edge computing (MEC) is a promising technology for providing resource-constrained users with computing resources. The integration of these two technologies can efficiently improve the computation service. In this paper, we propose a novel optimization scheme in the SCMA-based MEC network from the perspective of energy and latency for the Internet of Things (IoT) devices. To minimize the total overhead of devices, the communication and computation resources allocation, as well as computation offloading are jointly considered. Primarily, a joint SCMA codebook assignment based on the bidirectional matching principle and optimal power allocation algorithm is proposed to maximize the uplink transmit rate. Moreover, we put forward CPU frequency scheduling strategies utilizing convex optimization to optimize the computing resources allocation of local devices and the MEC server. Finally, a low-complexity task offloading policy based on simulated annealing is presented. Numerical results show that our proposed joint optimization algorithm for resource allocation and computation offloading can achieve a good compromise between time delay and energy consumption for IoT devices.

Abstract Multiple‐input multiple‐output‐sparse code multiple access, a non‐trivial integration of sparse code multiple access and multiple‐input multiple‐output techniques, is able to achieve high spectrum efficiency and massive user connections. However, this integration also increases the complexity of signal detection. Here, the signal detection problem of multiple‐input multiple‐output sparse code multiple access is transformed into a tree search problem and use sphere decoding to detect the signal. By setting the initial radius to positive infinity, sphere decoding can achieve optimal maximum likelihood performance while the complexity is high. In order to further reduce the complexity of sphere decoding, a block‐wise sorted QR decomposition algorithm is proposed. Based on block‐wise sorted QR decomposition, the improved sphere decoding, namely block‐wise sorted QR decomposition‐sphere decoding, is able to make the tree search more efficient. Since only the detection order of each user's signal has been changed, block‐wise sorted QR decomposition‐sphere decoding can maintain the optimal maximum likelihood performance. Simulation results and complexity analysis show that block‐wise sorted QR decomposition‐sphere decoding can achieve optimal performance and both hard‐output and soft‐output block‐wise sorted QR decomposition‐sphere decoding have much lower complexity than joint message passing algorithm. Furthermore, given the same signal‐to‐noise ratio, the complexity of block‐wise sorted QR decomposition‐sphere decoding decreases with the increase of receiving antennas, while the complexity of joint message passing algorithm increases linearly.

In secret key generation of physical layer security technology, it is challenging to achieve high key capacity and low bit inconsistency rate. This paper investigates intelligent reflecting surface (IRS)-assisted secret key generation, which aims to maximize the secret key capacity by adjusting the placement of the IRS units. Specifically, we first analyze and deduce the key capacity expression of the IRS-assisted system from the perspective of information theory. Then we investigate how to use the channel state information (CSI) to place the IRS units effectively so as to maximize the secret key capacity. Simulation results show that our scheme could improve the quality of secret key generation significantly.

The code length and rate of length-compatible polar codes can be adaptively adjusted and changed because of the special coding structure. In this paper, we propose a method to construct length-compatible polar codes by employing physical layer encryption technology. The deletion way of frozen bits and generator matrix are random, which makes polar codes more flexible and safe. Simulation analysis shows that the proposed algorithm can not only effectively improve the performance of length-compatible polar codes but also realize the physical layer security encryption of the system.

In order to resist eavesdropper collusion attack in wireless multi‐user network, the authors propose a distributed physical layer encryption (DPLE) scheme with energy‐efficient design. The encryption is embedded into rateless coding at both user nodes and relay node. Meanwhile, data frame permutation is added at the relay for increasing randomness. It is noteworthy that the secret key is used as the seed of random number generator, which controls the encoding process and permutation. At receiver, the decryption is united with decoding process without any extra cost, which makes DPLE special in the field of lightweight security. There are two cases considered in security analysis for resisting collusion attack: without error and with error. Typical results are time complexity and attack success probability, respectively. Furthermore, the evaluation for algorithm implementation is investigated. The theoretic result and simulation show that the proposed scheme can combat colluding eavesdroppers by high complexity and very low attack success probability. Moreover, lower computation cost is achieved.

In recent years, orthogonal frequency division multiplexing with index modulation (OFDM‐IM) has been proposed due to its extra diversity gain. Specially, OFDM with all index modulation (OFDM‐AIM) was proposed, which removed symbol bits and enhanced the diversity order compared to typical OFDM. However, the security issue of OFDM‐AIM has not been given full attention. This paper proposes an encrypted subblock design aided OFDM with all index modulation (ESD‐OFDMAIM) scheme to enhance physical layer security. Firstly, an encryption process of subblock design was put forward, which creates a random look‐up table and thus the mapping rule of ESD‐OFDM‐AIM between information bits and subblock realisations becomes random and time varying. Moreover, the scrambling and rotation encryption based on chaotic sequences from channel state information is utilised to prevent the eavesdropper from stealing the information via wireless channel. For eavesdroppers, parameters of ESD‐OFDM‐AIM such as spectral efficiency (SE), constellation points and the length of look‐up table are concealed by the encryption. Finally, analyses of attack models and the information entropy of constellations are also provided to measure the security of ESD‐OFDM‐AIM. Simulation results show that ESD‐OFDM‐AIM can effectively improve the system security without the affecting bit error rate performance.

Sparse code multiple access (SCMA) is one of the non‐orthogonal multiple access schemes to meet the demands of massive connection and high spectral efficiency in the 5G communications. Since the sparsity of the codebook, the message passing algorithm (MPA) can be utilised for multi‐user detection. However, the high computational complexity of MPA hinders the practical application of SCMA. The extended Max‐Log MPA (EML‐MPA) and the channel‐adaptive extended Max‐Log MPA (CAD‐EML‐MPA) help to reduce the complexity of conventional Log‐MPA with trellis representation. On this basis, the authors propose a dynamic trellis based MPA (DT‐MPA) in this study. DT‐MPA selects symbols dynamically according to a specific threshold in each iteration of MPA. The impact of the threshold on the complexity and convergence behaviour is analysed. Simulation results show that the DT‐MPA with variable which is related to bit signal‐to‐noise can achieve better bit error rate performance and lower complexity than EML‐MPA and CAD‐EML‐MPA.

In this study, a multiple access scheme called low density signature isotropic orthogonal transfer algorithm (LDS‐IOTA) is proposed for overloading transmissions, and an analytical model for the performance limitations of this system is developed. LDS‐IOTA utilises a low density signature structure for spreading the symbols in frequency domain, and applies such technique to IOTA‐based filter bank multicarrier system. The input–output mutual information of LDS‐IOTA is analysed for the case of finite size modulation, and LDS‐IOTA is compared with OFDM as well as LDS‐OFDM over multipath fadding channels.

In order to solve the security problem for fading channel, a pragmatic physical layer encryption (PLE) scheme is proposed, which utilises diversity technique elaborately. Different from the conventional PLE schemes based on phase rotation for the modulated symbol, the proposed scheme changed phase and amplitude together for a block of symbols each time, which can be defined as multi‐dimensional PLE (MPLE). Unconventional constellation obfuscates eavesdropper, which can be seen as the first level security in the physical layer. The correct probability based on chosen plaintext attacks and known plaintext attacks is deduced. It can be seen from the simulation results that the MPLE scheme can achieve lower attack success probability because of multi‐level security and better performance based on diversity under fading channel.

A novel concatenated physical‐layer encryption (CPLE) scheme is proposed in this study, where better security can be achieved as well as reliability advantage. In CPLE scheme, the encryption is embedded in rateless encoding. The secret key, which is generated from wireless channel, controls the random degree and random linear combination. The rateless codes are also concatenated with other conventional channel codes, which can achieve better reliability. Different from security codes, both the security and reliability in the proposed scheme can be improved. Furthermore, there is no extra computation requirement on decoding process. Security analysis is presented including time complexity comparison and attacks resistance in practical application. Compared to other PLE schemes, the proposed scheme achieves lower complexity, and higher channel adaptation and performance advantage. On the basis of National Institute of Standards and Technology statistical test suite, CPLE scheme can achieve randomness as the traditional cipher system such as advanced encryption standard. Furthermore, simulation results show that the CPLE scheme outperforms the conventional concatenated codes at the same coderate.

Sparse code multiple access (SCMA) is a promising candidate air interface of the next generation mobile networks. However, the decoding complexity of current message passing algorithm for SCMA is very high. In this study, the authors map SCMA constellation to q ‐order Galois field ( ) and introduce a trellis representation to SCMA. Based on the trellis representation, they propose low‐complexity decoding algorithms for SCMA by using truncated messages, which is referred as extended max‐log (EML) algorithm. As the truncated length of EML is unitary for each user, they further propose a channel‐adaptive EMLalgorithm to truncate the messages with a rule that can be adaptive to the channel state. Simulation results show that the proposed schemes obtain a low computational complexity with only a slight performance degradation when the truncated length is selected appropriately.

A new decoding strategy of belief propagation (BP) for low‐density parity‐check codes is presented by serially concatenating the traditional simultaneous decoding (also known as flooding) and the informed dynamic decoding (IDD) (e.g. node‐wise residual belief propagation (NW RBP) or informed variable‐to‐check (IVC) RBP). The frame error rates (FER) and bit error rates (BER) of the concatenated BP decoder outperform that of the non‐concatenated single decoder. In addition, as the signal‐to‐noise ratio (SNR) increases, the average number of decoding iterations required for the concatenated BP decoder decreases, and tends to merge with that of the first sub‐decoder in the high SNR region. Moreover, since the IDD strategies concerned in this paper require extra effort for the residual computation, and the sequential updating of IDD is much more time consuming than the simultaneous updating of flooding. Therefore, compared with using a single IDD, serially concatenating flooding and IDD reduces both the approximate decoding complexity and the decoding latency because the concatenated decoder is still dominated by the sub‐decoder flooding.

For relay‐assisted system, better relay channel and instable direct transmission (DT) channel exist. The recent coding schemes always focus on how to improve the system performance when channels are in medium signal‐to‐noise ratios. For the instability of DT channel, a novel coding scheme with multi‐dimensional constellations at relay is proposed, which make use of the robust relay channel. The design rule based on best approximate performance is given in the form of an optimisation problem, and its general solution is also shown. In addition, the optimal relay‐coding matrix design for 8PSK and 16QAM has been discussed in detail. Simulation results show that the authors’ proposed coding scheme outperforms the conventional scheme with repetition and is more robust than other well designed schemes in confronting the instability of DT channel.

Radar‐embedded communication (REC) provides a reliable and low probability of intercept (LPI) communication link to the intended receivers while masking its presence from intercept receivers. This study summarises all the waveform design schemes as well as receiver processing strategies for intra‐pulse REC, which forms the communication symbol waveform during one pulse interval and utilises de‐correlation processing on the receiver side. Based on the set of eigenvectors after eigen‐decomposition of sampled radar waveform, three design approaches are considered: eigenvectors‐as‐waveforms, weighted‐combining and dominant‐projection (DP). Specifically, DP performs better than the other two approaches even in multipath environment by using one projection matrix masked random vector to represent a communication symbol. Aimed by the drawbacks of DP, the authors propose a novel waveform generation approach called modified DP (MDP) in this study. MDP uses a common digitally‐modulated communication symbol spread by a pseudorandom sequence, so that it can enlarge the Euclidean distances between different data symbols and generate soft information for soft decision decoding, thus improving symbol error ratio and bit error ratio. Simulation results show that MDP significantly improves the reliability performance especially when channel coding is used, while also maintaining a relatively equal anti‐intercept performance.

Joint sparse graph for code division multiple access systems (JSG‐CDMA) combines multiple accessing (low‐density signature) and forward error correction (low‐density parity check code) techniques, and it achieves satisfactory performance under overloaded conditions. In this study, the authors carry on the research on the joint detection and decoding for JSG‐CDMA, and analyse the syndrome effect of message passing on the JSG by the extrinsic information transfer (EXIT) chart. An improved algorithm for joint detection and decoding on the JSG‐CDMA receiver is proposed, and the convergence behaviour of the algorithm is analysed by EXIT chart. Simulation results show that improved algorithm enhance the system performance significantly with a marginal increase of the computational complexity.

In this study, the authors consider a two‐hop network, where multiple source nodes (SNs) transmit to a destination node (DN) with the aid of a relay node (RN). The RN is equipped with a buffer, which is capable of storing multiple frames received from the SNs. During each time slot, the proposed protocol activates either the SN–RN hop or the RN–DN hop, depending on the channel quality of each hop and the buffer state at the RN. To optimise the hop activation for the network, they design a hop quality metric and propose a multi‐user buffer‐aided‐relaying uplink (MU‐BR‐UL) protocol, with the aid of the minimum signal‐to‐noise power ratio approximation. The benefits of the proposed protocol are analysed in terms of the end‐to‐end (e2e) outage probability and the e2e transmission delay. Then, the optimal power allocation is proposed for minimising the e2e outage probability under the total power constraint. The results indicate that the outage performance is significantly improved when the proposed power allocation is utilised in the MU‐BR‐UL protocol.

Abstract Low density signature for orthogonal frequency division multiplexing (LDS‐OFDM) is a promising technique for multiple accesses in wireless communications, but its performance is not optimal. In this paper, we study a non‐binary joint sparse graph which combines LDS‐OFDM and non‐binary low density parity check (LDPC) codes, namely non‐binary joint sparse graph for OFDM (NJSG–OFDM). Considering the fact that syndrome computing can be utilized to improve the convergence rate of the joint detection and decoding, syndrome nodes are added to the non‐binary joint sparse graph; consequently, an optimized receiver for the NJSG–OFDM is proposed and analyzed by extrinsic information transfer (EXIT) chart. Simulation results show that the optimized receiver has several advantages such as accelerating the convergence rate of the message passing, improving system performance and alleviating near‐far effect. Copyright © 2017 John Wiley & Sons, Ltd.

In this paper, a novel extending algorithm is proposed for the construction of rate compatible (RC) irregular repeat accumulate like (IRA-like) codes. Based on the structure characters of IRA-like codes, we propose an extending algorithm with uniform check node degree distribution and strong dependency in parity check matrix. Lower rate codes constructed through this method are efficiently encodable and well performed. Starting from initial code rate 8/16, the designed extending algorithm combining with existing puncturing algorithm realizes a series of RC IRA-like codes with rate R = 8/24, 8/23... 8/9. Simulation results show that the constructed RC IRA-like codes outperform those of similar algorithms from 0.04dB to 0.4 dB.

It is generally thought that space‐time block codes (STBCs) can obtain no more than full space diversity. In this study, the authors propose a new construction method of joint orthogonal STBCs based on M ‐dimensional lattice constellations for obtaining space and time diversities simultaneously. By deriving the Chernoff bound of error probability, they prove the exact diversity gain of the proposed code is M times of that in traditional STBCs. This is a valuable scheme as diversity gain is usually the primary factor to determine the ability of anti‐fading. Moreover, the maximum‐likelihood decoder for the proposed code just requires joint decoding of M real symbols, whose complexity is acceptable as M , usually, needs not to be too big. Numerical results show that the proposed code has remarkable improvement of performance compared with some typical STBCs under the comparable low decoding complexity.

In this paper, we propose a class of full diversity rate one space-time block codes (STBC) satisfying the generalized orthogonal constraint (GOC). First an explicit construction of completely decoupled STBC is proposed to obtain a rate one STBC with linear decoding complexity for any number of transmit antennas. Then we propose an adaptation strategy for the codes to achieve full diversity by utilizing partial phase information of the channel obtained via a feedback link. With a few feedback bits, the proposed rate one code has full diversity while reserving the same decoding complexity as Orthogonal STBCs. Moreover, the full diversity can be still achieved even if the simple zero-forced decoding is used at the receiver.