Given the significant potential of orthogonal time frequency space (OTFS) signals in advancing integrated sensing and communication (ISAC) systems, this paper investigates the target sensing enhancements in ISAC-OTFS systems. Specifically, a customized inter-range-cell interference (IRCI)-free range reconstruction method is proposed for high-quality target sensing. The resultant mainlobe signal-to-noise ratio (SNR) is derived as a function of OTFS waveform parameters, and the achievable maximum SNR is deduced to provide a benchmark for subsequent simulations. The optimization of OTFS waveforms for maximizing the target sensing SNR is formulated with hardware realization constraints (i.e., peak to average power ratio (PAPR) and energy constraints). The resultant non-convex multi-ratio fractional programming problem is solved using a hybrid algorithm named multi-ratio fractional programming and partial successive convex approximation (MR-FP-PSCA). Finally, the numerical results, including the IRCI-free target sensing method and the proposed optimization algorithm, demonstrate the effectiveness of the developed schemes.

Resistive Random-Access Memory (ReRAM) has garnered significant attention due to its high storage density, rapid read/write speeds, and compatibility with CMOS devices. However, the simple crossbar structure of ReRAM introduces sneak path (SP) interference, which impairs the storage reliability of the ReRAM system. To address this, we propose a novel Zoned Namespace (ZNS)-based ReRAM storage scheme, which is well-suited for scenarios with hybrid storage protection of multi-type data and employs low-density parity-check (LDPC) codes to mitigate the impact of sneak paths. Furthermore, considering the asymmetric nature of the ReRAM channel, we first develop a computer-calculable Asymmetric Discrete Density Evolution method for the belief propagation decoding algorithm (ADDE-BP). Due to the across-array storage structure, sneak path interference and noise vary across sub-arrays, resulting in codewords experiencing a non-uniform “sum channel”. To address this, we further propose criteria based on ADDE-BP for non-uniform error correction, specifically for the design of low-density parity-check (LDPC) codewords. Simulation results show that the proposed codes achieve 1–2 orders of magnitude lower BER than IEEE standard codes and Mackay codes under most channel conditions, thus demonstrating that our proposed LDPC code design for across-array applications enhances data storage reliability compared to conventional methods. Most importantly, the maximum check node degree and node type of the designed code were reduced, thus greatly simplifying the hardware implementation. This work establishes a co-design framework for ReRAM that simultaneously improves the reliability and efficiency of storage systems.

Integrated sensing and communication (ISAC) systems improve unmanned aerial vehicles (UAVs) efficiency and safety for low-altitude economy, but struggle with target identification due to reliance on primary radar. Thus, inspired by secondary surveillance radar (SSR) systems that can recognize target identities, this paper proposes an target identity recognition (TIR)-enabled ISAC technology to further improve UAV identification and tracking capabilities, optimizing airspace management and collision avoidance. Firstly, a novel integrated waveform design for TIR-enabled ISAC systems is proposed, where the waveform carries the interrogation/reply information of TIR through pulse modulation, and maintains a low-level amplitude (LLA) during pulse interval, allowing communication data to be modulated onto the carrier phase. Then, the proposed integrated waveform shows a trade-off between TIR bit error rate (BER) and communication symbol error rate (SER) due to the LLA, with an algorithm developed to optimize LLA for minimizing TIR BER while maintaining low communication SER.

Integrated sensing and communication (ISAC) has emerged as a key enabling technology for 6G networks. This paper addresses the joint beamforming design challenge in ISAC systems to prevent sensing information leakage to legitimate communication users. We propose a novel optimization framework that leverages semidefinite relaxation (SDR) and alternating optimization (AO) techniques to jointly design the base station beamforming vectors and the phase shift matrix of the RIS deployed at the radar target. The proposed approach ensures the satisfaction of communication SINR requirements while effectively suppressing the eavesdropping capability of sensing eavesdroppers. Simulation results demonstrate that our method achieves near-complete eavesdropping elimination compared to RIS-free and random-phase RIS configurations, enabling secure decoupling of sensing and communication functionalities.

In this work, a novel double-covertness framework is developed for integrated sensing and communication (ISAC) systems, where both the radar and communication signals are protected from being maliciously detected by adversaries. Specifically, a new measurement named joint intercept probability (JIP) is proposed for characterizing the double-covertness performance. Next, an optimal power allocation strategy is designed to minimize the JIP, subject to certain quality-of-service (QoS) requirements for communication and sensing. Simulation results verify the effectiveness of our proposed solution and demonstrate the intrinsic relationship among power allocation, JIP and different QoS requirements.

This paper presents a novel autonomous transmissive reconfigurable intelligent surface (ATRIS) framework for weighted sum-rate maximization in millimeter wave (mmWave) high-speed railway (HSR) communications. The proposed system employs ATRIS units mounted on high-speed train (HST) windows to enable efficient signal refraction from trackside base stations (BS) to in-cabin users, creating supplementary virtual line-of-sight (LoS) paths. To address the inherent challenges of HSR communications—including severe Doppler effects, multipath degradation, reduced coherence time, and fast fading—while reducing the computational complexity of conventional optimization approaches, we develop a decentralized feedback-based optimization framework. The system autonomously optimizes ATRIS phase shifts by maximizing the fraction of power transmitted through its' surface from BS, utilizing an on-board RF-Power Detector and genetic algorithm (GA). The optimized phase shift configurations are then transmitted to the BS via backhaul link, where weighted minimum mean square error (WMMSE) algorithms optimize the beamforming vectors to maximize users weighted sum-rates. For performance benchmarking, we implement a comparative centralized optimization approach using conventional passive transmissive reconfigurable intelligent surface (PTRIS) with direct BS control signal. Extensive simulation results demonstrate that our ATRIS-based system achieves competitive weighted sum-rates within 25% of the centralized PTRIS approach while significantly reducing computational complexity from$O\left(P G N K M_{B S}\right)$to O(PGN), where$P$is population size,$G$is number of generations,$N$is number of ATRIS elements,$K$is number of users, and$M_{B S}$is number of BS antennas. These results validate the proposed framework's viability for practical HSR communication implementations operating at speeds of up to 600 km/h.

With the rapid development of rail transit, both the diversity and volume of data transmitted in Train Communication Network (TCN) have significantly increased. Conventional TCN technologies struggle to accommodate this expansion. TimeSensitive Networking (TSN), an enhanced technology built upon traditional Ethernet, not only supports periodic traffic with consistent latency but also maintains compatibility with standard Ethernet services. Its capability to handle high bandwidth, low latency and ensure reliability makes TSN a promising solution for train communications. This paper establishes a network topology and data flow model based on TSN. Building on Time-Aware Shaping (TAS), we propose the Priority-Sorted Multi-Routing No-Wait Scheduling Algorithm (PSMRS). PSMRS distinguishes between priorities and provides better service for high-priority traffic, while also enhancing bandwidth utilization, scheduling success rates, and real-time performance. Furthermore, experimental simulations are conducted using Python and OMNeT++. The results of these experiments demonstrate the feasibility of the proposed algorithm, specifically the findings verify that PSMRS ensures faster response time for high-priority traffic, boosts overall link utilization, increases data flow scheduling success rate, and delivers superior real-time performance in large-scale flow scheduling.

In this paper, a novel artificial noise (AN)-aided secure and covert integrated sensing and communication (ISAC) framework is established for uncrewed aerial vehicle (UAV) systems, to against malicious radar signal detection and communication eavesdropping. Specifically, we consider that besides the communication and sensing signals, the AN signal, which is used to interfere with the eavesdropper and conceal the existence of radar signal, will be transmitted by the UAV-enabled base station (UBS) with uncertainty on its power level. The closed-form expressions of intercept probability (IP) as well as the minimum detection error probability (M-DEP) are derived. Moreover, an efficient communication and sensing performance maximization strategy is designed by optimizing the beamforming vector of communication, covariance matrix of sensing, and UBS receiver filter jointly, to satisfy the IP, power and M-DEP constraints. Simulation results are provided to verify the effectiveness of our joint design by comparing it to benchmark strategy. Moreover, the impact of AN power uncertainty is examined via simulations.

Low Earth orbit (LEO) satellite communications are the key enabler for achieving 6G ubiquitous connectivity. With the rapid progress of small satellite technology and the surging demands on direct-to-satellite services, a global wave of building LEO satellite constellations has been arisen. LEO satellite communications are the typical high mobility scenarios and suffer from severe Doppler effects. To overcome this challenge, orthogonal time frequency space (OTFS)-based LEO satellite communications have recently been studied, which exploit high mobility to obtain delay-Doppler diversity. However, due to limited satellite transmit power and very long propagation distance, the satellite-to-ground (S2G) links are very weak, and also suffer from inter-beam and inter-satellite interference. In this paper, we study coordinated multi-satellite transmission for OTFS-based LEO satellite communications to significantly improve the performance of S2G transmission, through enabling multiple satellites to cooperatively serve ground users. Furthermore, considering different delay and Doppler offsets among cooperative LEO satellites, we propose simultaneous pilots-based aggregate channel estimation (SP-ACE) scheme to improve channel estimation, which aggregately estimates the channels in S2G joint transmission by regarding the channels of all cooperative links as a single channel. Besides integer Doppler, we also consider fractional Doppler and propose three-stage peak-searching correlation (PSC)-based fractional Doppler estimation. Finally, simulations are conducted and the results demonstrate the effectiveness of the proposed coordinated multi-satellite transmission scheme, SP-ACE and three-stage PSC fractional Doppler estimation schemes.

This letter focuses on the optimal sum secure degree of freedom (SDoF) in a two-way wiretap channel (TW-WC), wherein two legitimate full-duplex multiple-antenna nodes cooperate with each other and are wiretapped by a multiple antenna eavesdropper simultaneously. It aims to find the optimal sum SDoF pertaining to secret-key capacity for the TW-WC. First, we analyze the upper bound and lower bounds of the optimal sum SDoF by establishing their equivalence to the expression of the optimal SDoF corresponding to the secrecy rate for the TW-WC. Subsequently, in scenarios where the legitimate nodes are configured with an equal number of transmit and receive antennas, it is elucidated that the upper and lower bounds of the optimal SDoF converge. Furthermore, the findings suggest that a higher SDoF can be achieved than the existing works, thereby heralding an enhancement in secure spectral efficiency.

Integrated sensing and communication (ISAC) holds significant commercial potential in future 6G. The 3GPP technical report indicates that it is crucial to prioritize the sensing services of the ISAC system to ensure the efficient execution of critical services due to resource-constrained environments. Thus, this paper investigates priority-based resource allocation in ISAC systems, where an ISAC base station (BS) simultaneously serves a communication user (CU) and detects both a primary sensing target (PST) and a secondary sensing target (SST). First, A priority criteria for this ISAC system is proposed: 1) Above all, to ensure that the Cramer-Rao bound (CRB) for PST is maintained below a threshold; 2) Following this, the CRB of the SST should be optimized, while ensuring the communication spectral efficiency is preserved. Then, based on this criterion, three cases are derived, and for each case, a distinct resource allocation problem is formulated, yielding closed-form or semi-closed-form expressions of the optimal resource allocation for each problem. Furthermore, An algorithm is also proposed to determine the occurrence of each case and provide the corresponding optimal resource allocation. In addition, system performance under each case is analyzed based on these expressions. Finally, the simulation results demonstrate the impact of the priority strategy on performance, which is consistent with the previous performance analysis.

The advent of reconfigurable intelligent surfaces (RIS) introduces a novel paradigm to address mutual interference issues within radar-communication coexistence (RCC) systems. However, the predominantly discrete reflection coefficients (DRC) of most real-world RISs pose new challenges for the design of interference-mitigating reflection coefficients. This paper investigates a RIS-assisted RCC system with DRC. First, a radar SINR maximization problem under the constraints of communication signal-to-interference plus noise ratio (SINR) requirements is formulated to obtain feasible designs for the DRC and radar beamforming vectors. Then, an alternating optimization approach is applied, decomposing the original problem into two sub-problems. For the DRC optimization sub-problem, a design approach based on semidefinite relaxation (SDR) and Gaussian randomization is proposed. For the radar beamforming sub-problem, the closed-form expressions for the optimal radar beamforming vectors are obtained by the generalized Rayleigh quotient and the Karush-Kuhn-Tucker (KKT) conditions. Finally, it is demonstrated that within a communication-centric scenario, the RIS needs to maintain orthogonality between the interference channel and the radar-target channel in order to achieve the upper bound of the radar SINR. Based on this conclusion, a low-complexity approach is proposed to optimize the radar SINR in a communication-centric scenario.

The advent of sixth-generation (6G) wireless communication systems represents a transformative leap in global connectivity, moving from traditional internet of things (IoT) frameworks to an advanced artificial intelligence of things (AIoT) paradigm. This evolution presents significant challenges, primarily due to exponential growth in data volume, complexity, and latency requirements. To address these challenges, over-the-air (OTA) computation has emerged as a breakthrough approach by integrating computational processes directly into the communication framework, overcoming the inefficiencies of traditional separate designs. In this study, we explore the integration of OTA computation with reconfigurable intelligent surfaces (RISs) within multi-cell multiple-input multiple-output (MIMO) networks. RIS technology enhances signal propagation, mitigates interference, and optimizes wireless coverage, thereby complementing the OTA computation paradigm’s ability to facilitate real-time data aggregation and processing. Specifically, we propose a novel joint optimization framework aimed at minimizing the mean squared error (MSE) in multi-cell environments. This framework addresses the complexity of beamforming design through an innovative power-iteration-based majorization-minimization approach and a successive alignment technique. In addition, we perform asymptotic analysis to elucidate the performance benefits of large-scale MIMO and RIS configurations. We also consider the fairness of MSE computation throughout the multi-cell system. Finally, numerical simulations validate the effectiveness of the proposed methods and provide additional insights based on the asymptotic analysis.

In this paper, aimed to against spoofing attack, we propose a novel physical layer authentication (PLA) framework for unmanned aerial vehicle (UAV) communication networks under Rayleigh and Rician channels. A new PLA metric, called authentication distance (AD), is defined by jointly considering the geographical locations, elevation angles, and channel randomness between a legitimate sensor and a malicious spoofer. For Rayleigh channel in dense urban environment, the closed-form expressions for the false alarm probability (FAP) and miss detection probability (MDP) are obtained by adopting method of convolution and integration by parts. Next, the PLA hypothesis test model with Rician channel is established in suburban environment where both the Rician factor and the path loss exponent are functions of UAV altitude. To proceed, the expressions for the FAP and MDP are derived based on the doubly non-centralFdistribution. In addition, MDP minimization solutions subject to certain FAP requirement are developed in both Rayleigh and Rician channels by optimizing the detection threshold and UAV altitude jointly. Simulation results show that our derived analytical expressions of FAP and MDP match the Monte Carlo simulations well. Moreover, simulation results also imply the effectiveness of the proposed PLA framework for UAV communication networks.

In this paper, we propose a blockchain-based energy trading mechanism for electric vehicle (EV) charging and discharging, which aims to provide a user-friendly, secure, and efficient energy trading platform for EV users. Firstly, EV users are required to calculate an evaluation function through the Road Side Unit (RSU) decision-making mechanism and select the RSU that maximizes their benefits to participate in vehicle-to-vehicle (V2V) energy trading. Secondly, this paper develops a mixed pricing strategy for V2V energy trading based on the Bayesian game. The strategy, combined with the real-time micro-market supply and demand status, promptly adjusts the bids of both parties of the energy transaction. After determining the transaction price, the mechanism further derives the energy trading volume that maximizes social welfare. Finally, the simulation results show that in the V2V energy transaction under the blockchain environment, adopting the RSU decision-making mechanism proposed in this paper can reduce the buyer's cost and improve the seller's revenue. The mixed pricing strategy can effectively improve the price satisfaction of energy transaction users and the success rate of transaction matching. It can protect user privacy and reduce communication loss, demonstrating blockchain's broad application prospects in the future energy transaction market.

Evolving from informatization to intelligence, railway wireless communication system (RWCS) is required to support more high quality service with strained resources. Nevertheless, due to the high mobility of trains, the perfect channel state information (CSI) of RWCS is typically hard to obtain, which may induce severe performance loss. To address these issues, we proposed an active RIS-assisted RSMA RWCS, where the CSI acquired is assumed to be imperfect. In this system, we formulated a weighted sum-rate (WSR) maximization problem to jointly optimize the beamforming, rate allocation vectors and RIS precoding matrix. To overcome the uncertainty of imperfect CSI and non-convexity of this problem, we transform orignial WSR maximization problem into a weighted average sum-rate ones, and we propose a block coordinate descent (BCD) algorithm based on weighted minimum mean square error (WMMSE) , fractional programming (FP) and sample average approximated (SAA) method to solve it. Numerical results show that active RIS-aied rate-splitting architecture has impressive advantages over conventional passive RIS-assisted space division multiple access (SDMA) under imperfect CSI.

The utilization of Specific Emitter Identification (SEI) in war defense has significantly improved the capability to identify and analyze enemy targets through the use of radio frequency fingerprint (RFF) extracted from received signals to identify specific emitters. The application of deep learning (DL) technology, specifically in wireless security authentication, has the potential to further enhance SEI. However, traditional machine learning approaches are centralized-based, which is not optimal for SEI due to the private nature of the emitter dataset, especially when the dataset are distributed among different organizations. Federated learning (FL) offers a solution by allowing multiple clients to cooperate in model training without dataset exchange. This paper introduces FL into SEI and proposes an open-set recognition framework. Unlike closed-set recognition, which only recognizes the emitters in the training set, open-set recognition is capable of identifying emitters that are not in the training set. Therefore the proposed framework is extremely suitable for the unknown emitter identification. The experimental results show that the proposed scheme achieves a high level of accuracy in identifying unknown emitters, even if the model is trained distributedly.

In this paper, we develop a secure multi-layer mobile edge computing (MEC) system where an unmanned aerial vehicle (UAV) equipped with a reconfigurable intelligent surface (RIS) acts as an aerial edge server and assists the offloading from multiple ground users to a base station (BS), in the presence of a full-duplex active eavesdropper (AE). To enhance the computing performance, we consider a partially offloading scheme where the computational task at each user can be executed at itself and offloaded to the UAV edge server and the BS via the UAV-enabled RIS, respectively. To maximize the total number of secure computing tasks among all users, we design a low complexity iterative algorithm by jointly optimizing the RIS phase shift, UAV deployment, power and computing resource allocation subject to certain power constraints. Numerical results show that compared to benchmark offloading schemes, our proposed UAV-RIS aided multi-layer MEC design improves the computing performance by at least 12.91%. Numerical results also demonstrate the impact of the full-duplex AE and validate the robustness of our proposed solution.

This paper investigates reconfigurable intelligent surface (RIS) aided multi-cell non-orthogonal multiple access (NOMA) networks with stochastic geometry methods. Under Rayleigh and Nakagami-m fading channels, we provide two types of approximate channel models to depict RIS channels, i.e., the N-fold convolution model and the curve fitting model. The analysis reveals that the N-fold convolution model is accurate and tractable when ignoring inter-cell interference, while the curve fitting model can evaluate the impact of inter-cell interference with a small error. The N-fold convolution model provides accurate diversity orders compared to other existing approaches such as the central limit model. Based on these channel models, we derive the closed-form analytical and asymptotic expressions of coverage probabilities and ergodic rates for two paired NOMA users. The analytical results demonstrate that: i) When we ignore inter-cell interference, the diversity order of the typical user is equal to the number of Rayleigh fading channels; and ii) For Nakagami-m fading channels with coefficientm, the diversity order is equal tomtimes of the channel number. Numerical results show that: i) RISs are capable of enhancing the coverage performance and ergodic rates of the proposed network; and ii) RISs provide extra flexibility for NOMA decoding orders.

In this paper, we present a novel unmanned aerial vehicle (UAV) aided physical layer authentication (PLA) frame-work to detect the origin of the received signal between a legitimate transmitter and a malicious adversary, based on the physical properties of channel characteristics and geographical locations. First, we model the authentication hypothesis test at the UAV based on the signal-to-noise ratio (SNR) of each transmission and analyze the probability density functions (PDFs) of SNR differences. Then, we derive the explicit expressions of false alarm probability (FAP) and miss detection probability (MDP), both of which depict the occurrence of detection error. Next, with the aim of minimizing the MDP subject to a given FAP constraint, the detection threshold and UAV deployment are jointly optimized. Numerical results verify the accuracy of our derived expressions and demonstrate the impact of distribution rate and adversary’s location on the detection performance. Moreover, numerical results also highlight the superiority of our proposed solution using SNR differences over benchmark strategy in high-rise urban environment.

Mobile-edge computing (MEC) and intelligent reflecting surface (IRS) are envisioned as two promising technologies that enable massive connectivity in the future Internet of Things (IoT) networks. MEC allows IoT devices (IDs) to offload their computation intensive tasks and, thus, can prolong their lifespan. In contrast, the IRS can enhance the channel condition between IDs and the access points (APs), which are co-located with the MEC server. Wireless power transfer technique enabling energy harvesting for IDs helps realizing sustainable IoT network. This article applies IRS in a multi-ID MEC system for better latency performance. We first propose a multiple access scheme with hybrid frequency-division and nonorthogonal access technologies and then design a timing protocol for the IDs. Based on the above design, we study the latency optimization problem with the joint optimization of power allocation, the IRS phase shift matrix, and uplink and downlink beamformer under maximum power constraint for the IDs and AP. To tackle the formulated multivariable nonconvex problem, we split the target problem into several subproblems and provide a near-optimal low-complexity ID clustering scheme. Afterward, we derive optimal solutions to these subproblems, and a low-complexity fast-convergence alternating algorithm is proposed to minimize the overall latency. Presented simulation results verify the convergence of the alternating algorithm, and its superiority over the benchmarks.

In this paper, a batched sparse(BATS) code transmission scheme based on chunked outer code is proposed. At the source node, a source file is first segmented into K number packets, then all the packets are divided into N chunks, each of which contains the same number of packets except for the last one if K cannot be divided by N. The chunks are encoded with the chunked outer code of BATS codes before transmitted to the next node. At the destination node, only the decodable batches need to be decoded to recover the input packets, and undecodable batches are abandoned directly to save the storage resources. In the aspect of the decoding, a simplified decoder is proposed, which is based on Gaussian elimination decoding. The consumed number of batches with a source file successfully transmitted by using the proposed scheme is analyzed under both time-invariant and time-variant channels. The simulation results show that compared with conventional BATS codes, less number of batches are consumed by applying the proposed chunked outer code.

In this paper, a batched sparse(BATS) code transmission scheme based on Low-density Parity-check(LDPC) precoding over GF(2) is studied. At the transmitter, a source file is first segmented into several packets, which are then precoded with LDPC to generate more packets. The precoded packets are encoded with the outer coding of the conventional BATS codes before they are transmitted to the intermediate nodes, which apply inner coding to the received packets and forward them to the next node. At the sink node, only a portion of received packets need to be decoded successfully to recover the source file. Moreover a one-step BP decoder is then proposed which achieves the same performance as the two-step BP decoder. The simulation results show that compared with the conventional BATS codes, less transmission batches are required by using the LDPC precoding. Meanwhile, one step decoder achieves the same transmission performance as the two step decoder, which decodes BATS codes and LDPC codes successively.

Sparse unmixing (SU) has been widely investigated for hyperspectral analysis with the aim to find the optimal subset of spectral signatures in a spectral library (known in advance) that can optimally model each pixel of the given hyperspectral image. Usually, the available spectral library organizes spectral signatures in groups. However, most existing strategies do not take full advantage of the inherent properties in the library. In this article, we design a convex framework for SU that incorporates the group structure of the spectral library. The convex framework includes two kinds of algorithms derived from either the primal or the dual form of the alternating direction method of multipliers (ADMM). Then, the convergence properties of the convex framework are established. Based on the convex framework, a novel nonconvex framework is developed for unmixing, which provides a new manner to enhance the sparsity of solution. The core of the nonconvex framework is to design a nonconvex penalty function for efficient minimization utilizing the generalized shrinkage mapping. The penalty function can be regarded as a closer approximation of the$l_{0}$norm. Experiments conducted on simulated and real hyperspectral data demonstrate the superiority and effectiveness of the proposed nonconvex framework in improving the unmixing performance and enhancing the sparsity of solution with respect to state-of-the-art techniques.

It has been shown that the SK scheme, which was proposed by Schalkwijk and Kailath, is a self-secure capacity-achieving (SSCA) feedback scheme for the Gaussian wiretap channel, i.e., the SK scheme not only achieves the feedback capacity of the Gaussian channel, but also is secure by itself and achieves the feedback secrecy capacity of the Gaussian wiretap channel. For the multi-user wiretap channels, very recently, it has been shown that Ozarow’s capacity-achieving feedback scheme for the two-user Gaussian multiple-access channel (GMAC) is the SSCA feedback scheme for the two-user Gaussian multiple-access wiretap channel (GMAC-WT). In this paper, first, we propose a SSCA feedback scheme for the two-user GMAC-WT with degraded message sets (GMAC-WT-DMS). Next, we extend the above scheme to the two-user GMAC-WT-DMS with noncausal channel state information at the transmitters (NCSIT), and show that the extended scheme is also a SSCA feedback scheme. Finally, we derive outer bounds on the secrecy capacity regions of the two-user GMAC-WT-DMS with or without NCSIT, and numerical results show the rate gains by the feedback.

Benefiting from the powerful cyclic redundancy check aided successive cancellation list (CA-SCL) decoder, the polar codes have achieved competitive performances with respect to LDCP codes. However, its short codeword performance needs to be further improved for supporting reliable short package transmissions typically in massive machine-type communications (mMTC). In this paper, the short polar coding problem is tackled by developing a bit-flipping aided CA-SCL detection method. First, we reveal that error distribution of SCL decoding strongly relates to the row weights of generator matrix. Accordingly, we determine the flipping indices according to both their row weights and their polarized bit-channel reliabilities. The simulation results show that our row weight based successive cancellation list flipping (RWB-SCL-Flipping) decoding achieves around 0.3 dB gain compared with its counterpart in [1] while transmitting short codewords over AWGN channels.

With the remarkable development of spectral unmixing, the sparse-representation-based approaches have emerged as a promising alternative. The sparse-representation-based approaches aim at finding the optimal subset of a spectral library that can optimally model each pixel of a given hyperspectral image in a semisupervised fashion. The classic sparse unmixing models are solved by the prime alternating direction method of multipliers (pADMMs). However, the computation task of pADMM is heavy and time consuming. In this letter, we design a novel dual-alternating direction method of multipliers (dADMMs) for the classic sparse unmixing models. We also present the global convergence analysis of our algorithm in some special cases. As shown in our experiments, the proposed algorithm is more effective than the state-of-the-art algorithms.

A hybrid downlink system that simultaneously uses visible light communication (VLC) and radio frequency (RF) is investigated, assuming that only one of the two considered users is capable of receiving information over the optical band. In order to facilitate information transmissions from the VLC access point to the RF user, mixed VLC/RF relaying and simultaneous lightwave information and power transfer (SLIPT) are utilized. Moreover, a cognitive-based resource allocation policy and tractable bounds for the harvested energy are introduced. Furthermore, by taking into account the random location of the VLC and RF user terminals, the closed-form outage probability for the VLC user is given, while for the RF user, the outage probability is derived in terms of infinite-series, which is also approximated by a tractable closed-form expression. In addition, the outage probability of the RF user is minimized by optimizing the direct current (DC) component. Finally, simulations are provided to verify the accuracy of the theoretical analysis and demonstrate the effectiveness of the proposed optimization framework.

The Schalkwijk-Kailath (SK) feedback scheme is a capacity-achieving coding scheme for the point-to-point white Gaussian channel with feedback. Recently, it has been shown that the SK scheme, which is not designed with consideration of secrecy, already achieves perfect weak secrecy by itself, i.e., the secrecy capacity of the Gaussian wiretap channel with feedback equals the capacity of the same model without secrecy constraint. In this paper, we propose a capacity-achieving SK type feedback scheme for the two-user Gaussian multiple-access channel with degraded message sets (GMAC-DMS). Similarly to the inherent secrecy nature of the classical SK scheme, we show that the proposed scheme is also secure by itself, which indicates that the feedback secrecy capacity of the two-user Gaussian multiple-access wiretap channel with degraded message sets (GMAC-WT-DMS) equals the capacity of the same model without secrecy constraint.

A batched sparse (BATS) code provides a novel two-stage coding structure for the multi-hop network, in which the outer code performed at the source node generates a potentially unlimited number of batches and the inner code at the intermediate network nodes applies network coding on packets belonging to the same batch. Previous works have studied the performance of BATS codes in the erasure channels, in which the packet loss rate ε is always assumed to be a constant on each link. However, in some application scenarios such as the Industrial Internet of Things (IIoTs) where there are a number of mobile nodes in the networks, the channel conditions could be time-variant due to the mobility of nodes, resulting the packet loss rate ε varying over time as well. Therefore this paper studies the rank distribution which is one of the most significant performance metric of BATS codes under time-variant channels by assuming the packet loss between links modeled as a random variable instead of a constant value. Closed-form expressions of rank distribution are obtained with the packet loss rate ε following two typical types of distributions. Both numerical and simulation results are provided to verify our analysis.

In this article, a general framework for enhancing the physical layer security (PLS) in the Internet of Things (IoT) systems via channel feedback is established. To be specific, first, we study the compound wiretap channel (WTC) with feedback, which can be viewed as an ideal model for enhancing the PLS in the downlink transmission of IoT systems via feedback. A novel feedback strategy is proposed and a corresponding lower bound on the secrecy capacity is constructed for this ideal model. Next, we generalize the ideal model (i.e., the compound WTC with feedback) by considering channel states and feedback delay, and this generalized model is called the finite state compound WTC with delayed feedback. The lower bounds on the secrecy capacities of this generalized model with or without delayed channel output feedback are provided, and they are constructed according to variations of the previously proposed feedback scheme for the ideal model. Finally, from a Gaussian fading example, we show that the delayed channel output feedback enhances the achievable secrecy rate of the finite state compound WTC with only delayed state feedback, which implies that feedback helps to enhance the PLS in the downlink transmission of the IoT systems.

As a hybrid MIMO architecture, beamspace multiple input multiple output (MIMO) can significantly reduce the number of required radio frequency (RF) chains in millimeter wave (mmWave) massive MIMO systems without obvious performance loss, in which, however, the number of users supported cannot be larger than that of RF chains. To break this fundamental limit, we introduce the concept of code-domain non-orthogonal multiple access (NOMA) into beamspace MIMO. A beam selection scheme is proposed first to maximize the sum-rate by utilizing the quasi-orthogonality of the beamspace channel. Furthermore, a low-complexity detection algorithm is developed to realize the transceiver design in mmWave communications using lens antennas. Finally, numerical results of the decoding complexity at receiver side are analyzed. Simulation results show that the proposed beamspace MIMO-NOMA in code domain can achieve higher spectrum and energy efficiency compared with the existing beamspace MIMO.

In this paper, we consider a downlink non-orthogonal multiple access (NOMA) enabled heterogeneous small cells network (HSCN), where the macro base station simultaneously communicates with multiple small cell base stations (SBSs) through wireless backhaul. In each small cell, users are grouped by NOMA bases and then served by their respective SBS. The proposed framework considers the realistic imperfect channel state information and quality of service requirements of users. The goal is to investigate an energy-efficient joint power, and bandwidth allocation scheme, which aims to maximize the energy efficiency (EE) of the small cells in downlink NOMA-HSCN constrained by the maximum transmit power and the minimum required data rate simultaneously. The optimization problem is non-convex due to the fractional objective function and non-convex constraint and thus challenging to obtain an exact solution efficiently. To this end, the joint optimization is first decomposed into two subproblems. Then, an iterative algorithm to solve the power optimization subproblem is proposed with guaranteed convergence. Furthermore, we derive a closed-form solution for the bandwidth allocation subproblem. Simulation results reveal that the effectiveness of the proposed schemes in terms of EE compared to the existing NOMA and the orthogonal multiple access schemes.

Wireless content caching in cellular networks is an efficient way to reduce the service delay and alleviate backhaul pressure. For the benefits of sharing spectral and storage resources, clustering in cached networks has recently attracted significant research interests. Meanwhile, since the multimedia content (e.g., video) of caching networks may require a huge transmission rates, millimeter wave (mmWave) communication is considered to be an efficient transmission scheme for cache-enabled networks. We investigate the ergodic rate and average service delay for typical user terminal (UT) in the clustered cache-enabled small cell networks (SCN) and ultra dense networks (UDN) with mmWave channels. In SCN, each cluster consists of cache-enabled UTs, and in the UDN a cluster is formed by cache-enabled UTs and small base stations (SBSs) with non-uniform caching capacity. The clusters are assumed to be discs and content sharing is only possible within clusters through mmWave device-to-device (D2D) tier and SBS tier communications. With stochastic geometry methods, the distributions of content sharing distance and signal-to-interference-noise-ratio (SINR) of typical UT in a cluster are derived for both SCN and UDN scenarios. To minimize the average service delay in high SINR region, we provide an algorithm to jointly optimize caching scheme for SBSs and UTs. By simulations, we validate our theoretical analysis and the performance of proposed caching scheme. The numerical results also show that there exists best radius in the design of cluster for UDNs.

We investigate the state-dependent Gaussian wiretap channel with noncausal channel state information at the transmitter (GWTC-N-CSIT), and explore whether three strategies (i.e., taking action on the state, legitimate receiver's channel output feedback, and combining the former two strategies together) help to enhance the secrecy capacity of the GWTC-N-CSIT. To be specific, we first determine the secrecy capacity of the GWTC-N-CSIT with noiseless feedback. Next, we derive lower and upper bounds on the secrecy capacity of the GWTC-N-CSIT with action-dependent state. Finally, we derive lower and upper bounds on the secrecy capacity of the GWTC-N-CSIT with both action-dependent state and noiseless feedback, and show that these bounds meet for a special case. Numerical results of this paper indicate that all three strategies enhance the secrecy capacity of the GWTC-N-CSIT. The study of this paper offers new options for enhancing the secrecy rates of the state-dependent wiretap channel models.

With the development of healthcare 4.0, there has been an explosion in the amount of data such as image, medical text, physiological signals, lab tests, etc. Among them, medical records provide a complete picture of the associated clinical events. However, the processing of medical texts is difficult because they are structurally free, diverse in style, and have subjective factors. Assigning metadata codes from the International Classification of Diseases (ICD) presents a standardized way of indicating diagnoses and procedures, so it becomes a mandatory process for understanding medical records to make better clinical and financial decisions. Such a manual encoding task is time-consuming, error-prone and expensive. In this paper, we proposed a deep learning approach and a medical topic mining method to automatically predict ICD codes from text-free medical records. The result of the F1 score on Medical Information Mart for Intensive Care (MIMIC-III) dataset increases by 5% over the state of art. It also suitable for multiple ICD versions and languages. For the specific disease, atrial fibrillation, the F1 score is up to 96% and 93.3% using in-house ICD-10 datasets and MIMIC-III datasets, respectively. We developed an Artificial Intelligence based coding system, which can greatly improve the efficiency and accuracy of human coders, and meanwhile accelerate the secondary use for clinical informatics.

We propose an indoor lightwave downlink wireless communication network with the non-orthogonal multiple access (NOMA) technology, that consists of one visible light communication (VLC) access point (AP) and a pair of randomly located users. Although both users can directly receive information from the AP, the performance of the far user is degraded compared to the near one due to the asymmetrical channel gains. Thus, the user cooperation strategy is proposed to improve the performance of the far user by using mixed VLC/RF relaying technique in parallel with the wireless optical direct link. To efficiently exploit the available heterogeneous links, the concept of cross-band selection combining (CBSC) is introduced, according to which the far user is continuously served by either the mixed VLC/RF or the direct VLC link. Meanwhile, the performance of the proposed scheme is thoroughly investigated and compared to appropriate baselines. To this end, we derive closed-form expressions for the outage probability of each user as well as the system sum throughput. Finally, simulation results are provided to verify the effectiveness of the proposed scheme and the accuracy of the corresponding analysis.

In this paper, we propose the full-duplex and cloud radio access network (C-RAN) based multi-cell non-orthogonal multiple access schemes over 5G mobile wireless networks. To cope with the severe intra-cell and inter-cell interferences as well as perform the centralized optimization, we adopt the C-RAN architecture, where the baseband processing and resource management are conducted at a central unit (CU). With the goal of maximizing the weighted sum achievable rate, we formulate the sum rate maximization power allocation problem as a non-convex problem. Thanks to the hidden monotonicity structure of the considered problem, the optimal power allocation algorithm is developed by the monotonic optimization method. Besides, we propose another suboptimal algorithm by employing successive convex approximation method to obtain the close-to-optimal solution with a significantly reduced computational complexity. Extensive simulations are conducted to verify the effectiveness of our proposed power allocation schemes, and confirm the superiority of our proposed C-RAN architecture.

Recently, power allocation has attracted more and more attention in order to optimize the performance of non-orthogonal multiple access (NOMA) systems. Different from existing works, the power allocation problems are investigated for cooperative NOMA systems with dedicated amplify-and-forward half-duplex relay (NOMA-HDR) and full-duplex relay (NOMA-FDR). From the fairness standpoint, the power allocation problems are formulated to maximize the minimum achievable user rate in the considered systems. The problems for both NOMA-HDR and NOMA-FDR systems with two-user and M-user are addressed. The closed-form power allocation policy of two-user NOMA-HDR system is obtained. Also, the optimal numerical power allocation policies for two-user NOMA-FDR and M-user NOMA-HDR systems are obtained. In addition, the problem for M-user NOMA-FDR systems is solved in noise-limited environment. Simulation results show that the proposed NOMA-HDR or NOMA-FDR scheme with power adaption clearly outperforms the NOMA-HDR or NOMA-FDR scheme with fixed power allocation. Besides, when the residual self-interference channel gain is small, the performance of NOMA-FDR system is better than the NOMA-HDR system.

Identifying relation from clinical texts is a complex and challenging task due to the specific biomedical knowledge. Existing methods for this work generally have the misclassification problem caused by sample class imbalance. In this paper, we propose a hierarchical attention-based convolutional long short-term memory (ConvLSTM) network model to solve this problem. We construct a sentence as multi-dimensional hierarchical sequence and directly learn local and global context information by a single-layer ConvLSTM network. Besides, a hierarchical attention-based pooling is built to capture the parts of a sentence that are relevant with the target semantic relation. Experiments on the 2010 i2b2/VA relation dataset show that our model outperforms several previous state-of-the-art models without relying on any external features.

The dirty paper wiretap channel, also referred to as the Gaussian wiretap channel with noncausal state at the transmitter, is revisited. First, we determine the secrecy capacity of the dirty paper wiretap channel with noiseless feedback, where the feedback channel is from the legitimate receiver to the transmitter. Next, we obtain lower and upper bounds on the secrecy capacity of the action-dependent dirty paper wiretap channel with noiseless feedback, and show that these bounds meet for a special case. Unlike the fact that action on the state helps to enhance the capacity of the dirty paper channel with feedback, numerical results of this paper indicate that it may not help to enhance the secrecy capacity of the dirty paper wiretap channel with feedback.

To the best of our knowledge, Belief Propagation List (BPL) decoding achieves the best error-correction performance within the class of BP based polar code decoding algorithms. It regards different permutations of the polar code factor graph as a range of available "decoding lists" for individually executing the BP algorithm. Then, a minimum Euclidean distance criterion is employed to combine these individual decisions. However, we demonstrated that simply increasing the number of lists involved in the BPL algorithm does not always improve its performance. Instead, we exploit the extrinsic information transfer (EXIT) chart technology to verify the efficiency of a decoding list. Based on this analysis, an efficient list selection scheme is proposed. In the same spirit, in order to mitigate the impact of relatively inferior decoding lists on other selected decoding lists, new decision fusion schemes are also designed. Benefiting from these improvements of BPL algorithm, performance gains are evidenced in our simulation results.

The paper studies the multi-cell cooperation scheme under the time and frequency doubly selective channels, in which the multi-cell co-channel interference are jointly eliminated with the inter-symbol interference to enhance the transmission reception. The basic idea of interference alignment is exploited, with which the link-level interference and network-level interference are aligned to the same dimension before canceled. Instead of assuming the perfect channel information is available at the receivers, an embedded pilot framework is also proposed to track and update the channel state information every short time period, making the proposed scheme more feasible for practical application. Additionally, the pilot design is also discussed and an optimal embedded pilot scheme is derived.

Non-orthogonal multiple access (NOMA) has attracted both academic and industrial interest since it has been considered as one of the promising 5G technologies in order to increase connectivity and spectral efficiency. In this paper, we focus on a downlink NOMA network, where a single base station serves a set of users through multiple subchannels. The goal is to jointly optimize energy efficiency (EE) and fairness among users with respect to the subcarrier and power allocation parameters. To achieve this with acceptable complexity, we propose a novel greedy subcarrier assignment scheme. Due to the fractional form of the EE expression and the existence of interference, the power allocation problem is non-convex. To this end, we first transform this into an equivalent subtractive form, which is then solved by using fractional programming with sequential optimization of the power allocation vectors. Simulation results reveal the effectiveness of the proposed scheme in terms of EE and fairness among users compared to baseline schemes. Finally, the proposed algorithms are of fast convergence, low complexity, and insensitive to the initial values.

As one of the key enabling technologies of emerging smart societies and industries (i.e., industry 4.0), the Internet of Things (IoT) has evolved significantly in both the technologies and applications. It is estimated that more than 25 billion devices will be connected by wireless IoT networks by 2020. In addition to ubiquitous connectivity, many envisioned applications of the IoT, such as industrial automation, vehicle-to-everything (V2X) networks, smart grids, and remote surgery, will have stringent transmission latency and reliability requirements, which may not be supported by the existing systems. Thus, there is an urgent need for rethinking the entire communication protocol stack for wireless IoT networks.

As one of the key enabling technologies of emerging smart societies and industries (i.e., industry 4.0), the Internet of Things (IoT) has evolved significantly in both technologies and applications. It is estimated that more than 25 billion devices will be connected by wireless IoT networks by 2020. In addition to ubiquitous connectivity, many envisioned applications of IoT, such as industrial automation, vehicle-to-everything (V2X) networks, smart grids, and remote surgery, will have stringent transmission latency and reliability requirements, which may not be supported by existing systems. Thus, there is an urgent need for rethinking the entire communication protocol stack for wireless IoT networks. In this tutorial paper, we review the various application scenarios, fundamental performance limits, and potential technical solutions for high-reliability and low-latency (HRLL) wireless IoT networks. We discuss physical, MAC (medium access control), and network layers of wireless IoT networks, which all have significant impacts on latency and reliability. For the physical layer, we discuss the fundamental information-theoretic limits for HRLL communications, and then we also introduce a frame structure and preamble design for HRLL communications. Then practical channel codes with finite block length are reviewed. For the MAC layer, we first discuss optimized spectrum and power resource management schemes and then recently proposed grant-free schemes are discussed. For the network layer, we discuss the optimized network structure (traffic dispersion and network densification), the optimal traffic allocation schemes and network coding schemes to minimize latency.

The broadcast channel with mutual secrecy requirement at the receivers (BC-MSR-R) is a basic model characterizing the physical layer security (PLS) in the down-link of the wireless communication systems, where one transmitter sends two independent messages to two receivers via a broadcast channel, and each receiver can successfully decode his/her intended message and wishes to overhear the other one's message. This paper studies how to enhance the already existing secrecy rate region of the BC-MSR-R via receivers' feedback. Specifically, we propose two feedback strategies for the BC-MSR-R, where one uses the feedback to generate pure secret keys protecting the transmitted messages, and the other uses the feedback to generate not only keys but also cooperative messages helping the receivers to improve their decoding performance. Different inner bounds on the secrecy capacity region of the BC-MSR-R with noiseless feedback are constructed according to different feedback strategies, and these bounds are further illustrated by a Dueck-type example.

Non-orthogonal multiple access (NOMA) has attracted both academic and industrial interest since it has been considered as one of the promising 5G technologies in order to increase connectivity and spectral efficiency. In this paper, we focus on a downlink multicarrier (MC) NOMA network, where a single base station serves a set of users through multiple subchannels. The goal is to jointly optimize energy efficiency (EE) and fairness among users with respect to the subcarrier and power allocation parameters. To achieve this with acceptable complexity, a novel greedy subcarrier assignment scheme based on the worst-user first principle is proposed. Due to the fractional form of the EE expression and the existence of interference, the power allocation problem is non-convex and NP-hard. To this end, we first transform this into an equivalent subtractive form, which is then solved by using fractional programming with sequential optimization of the inter/intra-subchannel power allocation vectors. Simulation results reveal the effectiveness of the proposed scheme in terms of EE and fairness among users compared to baseline schemes. Finally, the proposed algorithms are of fast convergence, low complexity, and insensitive to the initial values.

This paper investigates the power allocation problems for non-orthogonal multiple access with coordinated direct and relay transmission (CDRT-NOMA), where a base station (BS) communicates with its nearby user directly, while communicating with its far user only through a dedicated relay node (RN). The RN is assumed to operate in either half-duplex relaying (HDR) mode or full-duplex relaying (FDR) mode. Based on instantaneous channel state information (CSI), the dynamic power allocation problems under HDR and FDR schemes are formulated respectively, with the objective of maximizing the minimum user achievable rate. After demonstrating the quasi-concavity of the considered problems, we derive the optimal closed-form power allocation policies under the HDR scheme and the FDR scheme. Then, a hybrid relaying scheme dynamically switching between HDR and FDR schemes is further designed. Moreover, we also study the fixed power allocation problems for the considered CDRT-NOMA systems based on statistical CSI so as to optimize the long-term system performance. The simulations show that our proposed power allocation policies can significantly enhance the performance of CDRT-NOMA systems.

Airborne radio access networks (A-RANs) is a particularly promising technology due to its ability to offer fast, cost-efficient, and on-demand enhancement of the existing telecommunication infrastructure. The main challenges of ARANs are the energy sustainability of the aerial platforms (APs) and the establishment of reliable links with the ground nodes. To this direction, we propose a novel approach, which is based on mixed free-space optical (FSO)/radio frequency (RF) relaying protocol and simultaneous lightwave information and power transfer (SLIPT). In this context, we also formulate and optimally solve the max-min fairness problem, which regulates the trade-off between the energy and information transfer to the AP and allocates the available resources to multiple endusers. Finally, the impact of the number of users and weather conditions on system's optimal configuration and performance is investigated through simulations. The offered results provide meaningful theoretical and practical insights on the capabilities of the proposed scheme.

Massive connectivity and safety guarantee are two main challenges in 5G vehicular communication networks. In this paper, we proposed a 5G vehicular communication network which provides active road safety application, traffic efficiency application and infotainment application at the same time. For V2V communications, we exploit SCMA(Sparse Code Multiple Access) and full-duplex to provide massive connectivity, which are also promising to reduce the transmission latency and improve the spectrum efficiency. For V2I communications, OFDMA and half- duplex technologies are adopted for traffic efficiency information transmission and entertainment content transmission. Besides, software-defined networking (SDN) and wireless network virtualization (WNV) are also exploited to slice the network into multiple independent slices, which isolates the road safety application from other applications. Then we proposed virtual resource allocation scheme, in which the absolute priority mechanism is applied to ensure the successful transmission of road safety information. The centralized scheduling and virtual resource allocation problem is formulated, and a Lagrangian dual algorithm is developed, which converges to a stable resource allocation scheme after a limited number of iterations. Simulation results show that the proposed mixed SCMA/OFDMA scheme outperforms the traditional orthogonal multiple access scheme in terms of system throughput.

We study a mobility prediction based proactive wireless caching scheme for two-tier cellular networks consisting of a base station (BS) tier and a device-to-device (D2D) tier. Two scenarios are considered: popular contents cached only at BSs, and popular contents cached at both BSs and MTs. We model user mobility as a Markov renewal process to predict user moving paths and residence time. Then we analyse the hit-rate performance to evaluate the presented schemes. By formulating content placement to maximize the hit-rate as optimization problems, we provide the optimal solution for the first scenario and develop a greedy mobility prediction based proactive wireless caching (MPPC) scheme for the second. Through analysis we show that the hit-rate achieved by MPPC is at least exp(1)-1/exp(1) of the optimal hit-rate. The numeric results show that the MPPC can dramatically improve the hit-rate performance, compared with random caching and most popular caching (MPC) schemes. We show that the hit-rate achieved by MPPC outperformances MPC by 26% at most when MTs are not able to cache. Besides we present the impact of the moving speed on the hit-rate performance of MPPC for MTs.

Recently, it has been shown that the time-varying multiple-access channel (MAC) with perfect channel state information (CSI) at the receiver and delayed feedback CSI at the transmitters can be modeled as the finite state MAC (FS-MAC) with delayed state feedback, where the time variation of the channel is characterized by the statistics of the underlying state process. To study the fundamental limit of the secure transmission over multi-user wireless communication systems, we re-visit the FS-MAC with delayed state feedback by considering an external eavesdropper, which we call the finite state multiple-access wiretap channel (FS-MAC-WT) with delayed feedback. The main contribution of this paper is to show that taking full advantage of the delayed channel output feedback helps to increase the secrecy rate region of the FS-MAC-WT with delayed state feedback. Moreover, by a degraded Gaussian fading example, we show the effects of feedback delay and channel memory on the secrecy sum rate of the FS-MAC-WT with delayed feedback.

This paper investigates the constellation/codebook design of a promising uplink multiple access technique, sparse code multiple access (SCMA), proposed for the fifth generation mobile networks. The application of bit-interleaved coded modulation with iterative multiuser detection is considered for uplink SCMA over fading channels. Extrinsic information transfer chart is used to aid the analysis and the design of multidimensional constellations, and the design criteria for multidimensional constellations and labelings optimization are thus established. Furthermore, a new and simple approach of multi-stage optimization for the multidimensional constellation design is proposed for SCMA, to improve the bit-error rate performance and alleviate the complexity of turbo multiuser detection. Numerical and simulation results are also provided to demonstrate the performance and verify the efficiency of the proposed scheme, compared with the state of the art.

Ultra-dense networks (UDNs) are the promising technology for the fifth-generation wireless networks and beyond to significantly boost network capacity and improve network coverage by exploiting spatial spectrum reuse through the deployment of massive base stations (BSs). In this paper, the fundamental tradeoffs of non-orthogonal multicast, multicast, and unicast in the UDN are studied, to understand the impact of network densitification on them and provide some insights on UDN deployment. Non-orthogonal multicast with imperfect channel estimation and successive interference cancellation is also investigated. To evaluate the performance, a tractable model for performance analysis is developed by using stochastic geometry, and then the analytical expressions for downlink signal-to-interference-plus-noise ratio coverage probability, spectrum efficiency, area traffic capacity, and energy efficiency are derived. The numerical results together with the Monte Carlo simulations are also provided. The results demonstrate that non-orthogonal multicast can further improve the performance of multicast and achieve higher spectrum efficiency, area traffic capacity, and energy efficiency than unicast from the low-to-high BS density regions, but suffers from inferior performance to unicast in the very high BS density region. The results also show that the non-orthogonal multicast and multicast exhibit different performance trends from unicast.

Power allocation is an important issue in order to optimize the performance of non-orthogonal multiple access (NOMA) systems. However, the power allocation problem for cooperative NOMA systems has not been well investigated. In this paper, we investigate the power allocation problems for half-duplex cooperative NOMA (HD-CNOMA) and full-duplex cooperative NOMA (FD-CNOMA) systems, respectively. From the fairness standpoint, the optimization problem for each system is formulated to maximize the minimum achievable user rate in a NOMA user pair. Even though both of the formulated problems are neither concave nor quasi-concave, the optimal closed-form solutions of both cases are still obtained with the proposed two-step method. First, we transform the initial problem into a quasi-concave problem by treating the relay transmit power, namely R, as a constant, and then solve the obtained quasiconcave problem. Second, we convert the original problem into a univariate problem of R based on the results of the first step, and eventually obtain the optimal power allocation. In addition, a hybrid half/full-duplex cooperative NOMA scheme, which dynamically switches between the HD-CNOMA and FD-CNOMA mode, is proposed. After that, a relay selection scheme is also investigated to extend the hybrid scheme into general networks with multiple users. Numerical results demonstrate that the proposed hybrid relaying scheme can achieve a significant performance improvement with respect to the conventional NOMA, HD-CNOMA, and FD-CNOMA scheme.

Cooperative non-orthogonal multiple access (NOMA) has attracted more and more attentions recently, in which NOMA-strong users play as relays to help the data transmission of NOMA-weak users. Different from existing works, we study the problem of power allocation for cooperative NOMA systems with half-duplex relaying mode. From a fairness standpoint, our proposed scheme aims at maximizing the minimum achievable user rate in a paired user group. More specifically, we divide the cooperative NOMA systems into two categories, i.e., fixed relaying scheme and adaptive relaying scheme. Fixed relaying scheme means the transmit power at the relay node, namely , is a given fixed constant while adaptive relaying scheme implies that can adapt to channel conditions according to our strategy. It is shown that the formulated power allocation problem for fixed relaying scheme is quasi-concave while the problem for adaptive relaying scheme is not. Hence, we firstly solve the former problem using a bisection algorithm by transforming it into a sequence of convex feasibility problems. Then, relying on the derived results of fixed relaying scheme, we find that the problem for adaptive relaying scheme can be converted into a univariate function about , in which the optimum can be also obtained by a similar bisection procedure. Numerical results reveal that the proposed adaptive relaying scheme always outperforms the proposed fixed relaying scheme. In addition, we also show that the cooperative NOMA systems are especially appropriate for systems under low SNR environments or having significantly different fading coefficients between NOMA users.

The finite state Markov channel (FSMC) has been shown to be a useful model for the time-varying fading channels. In this paper, we study the security issue in the wireless communication systems by considering the FSMC with an eavesdropper, which we call the finite state Markov wiretap channel (FSM-WC). More specifically, the FSM-WC is a channel with one input (the transmitter) and two outputs (the legitimate receiver and the eavesdropper). The transition probability of the FSM-WC is controlled by a channel state which takes values in a finite set, and it undergoes a Markov process. We assume that the state is perfectly known by the legitimate receiver and the eavesdropper, and through a noiseless feedback channel, the legitimate receiver sends the state back to the transmitter after some time delay. Measuring the eavesdropper's uncertainty about the transmitted message by equivocation, we provide inner and outer bounds on the capacity-equivocation region of this novel model, and show that these bounds meet (the capacity-equivocation region is determined) if the channel output for the eavesdropper is a degraded version of that for the legitimate receiver. The capacity results of this paper are further explained via degraded Gaussian and Gaussian fading examples.

This paper investigates the asymptotic performance of bit-interleaved coded modulation (BICM) with iterative multiuser detection and decoding in uplink sparse code multiple access (SCMA) systems. The extrinsic information transfer (EXIT) characteristics analysis of the joint multiuser detector for SCMA is provided, and shows that the average detection reliability for multiple users converges to the single-user case, if ideal feedback from the decoder is available to the detector. We develop a tight analytical bound on the convolutionally encoded bit-error rate (BER) for independent Rayleigh fadings, based on the single-user bound with arbitrary multidimensional constellations. Moreover, we analyze the achievable coding and diversity gains of the SCMA-BICM system with iterative receiver. Simulations are carried out to verify the effectiveness of the analysis.

Power domain non-orthogonal multiple access (NOMA), which multiplexes multiple users in power domain to achieve high spectrum efficiency, is a promising technology for the fifth-generation (5G) wireless networks and beyond. In this work, we study time and power allocation for two-hop NOMA relaying with decode-and-forward (DF) protocol, to satisfy two NOMA users' different quality of service (QoS) requirements. The performance metrics of outage probability and ergodic capacity are used to evaluate two NOMA users, respectively. The closedform expression for outage probability is also derived. Furthermore, to obtain optimal time allocation factor to achieve the minimum outage probability, we formulate it as one optimization problem and develop a golden section search (GSS)-based algorithm to solve it. Also, the tradeoff between time and power allocation is further analysed to improve the system performance. Numerical and simulation results show that the proposed time and power allocation DF-NOMA behaves better than the traditional equal-time slot cooperative NOMA.

Power allocation plays an important role in cooperative non-orthogonal multiple access (NOMA) systems. To guarantee the quality of service (QoS) requirements of users, we present the cross layer power allocation algorithms for half-duplex cooperative NOMA (HD-CNOMA) and full-duplex cooperative NOMA (FD-CNOMA) systems respectively. From fairness standpoint, the optimization problem for each scheme aims at maximizing the minimum user effective capacity in a NOMA user pair under different delay QoS constraints. Due to the quasi-concavity of both problems, we propose a bisection-based cross layer power allocation algorithm for both cases to obtain the optimal solution. Numerical results show that proposed schemes significantly outperforms existing fixed cooperative NOMA schemes. Moreover, we also illustrate that proposed cooperative NOMA schemes are more suitable for low SNR environments compared to the optimized conventional NOMA scheme.

The power allocation for multi-user sparse code multiple access (SCMA) downlink systems with finite- alphabet constraints is investigated. An explicit expression for the achievable rate for downlink SCMA systems with finite-alphabet inputs is derived, which is applicable to arbitrary number of users. Moreover, a novel power allocation scheme that can ensure users' fairness for multi-user SCMA downlink systems is proposed. In an effort to solve the formulated non-convex optimization problem, a low- complexity polynomial algorithm is proposed, which yields an optimal solution. Simulation results demonstrate that the proposed power allocation algorithm is capable of enhancing the performance significantly compared to the equal power allocation scheme.

The convergence of communications, caching and computing (i.e., 3C) has attracted a lot of interests recently. To save communication resources, caching has been introduced into information-centric communication networks. Meanwhile, computing has also been exploited to improve the efficiency of communication networks. However, the combination of both communication, caching and computing is still at its infancy and significant research challenges remain to be addressed. Different from the previous works, we consider a virtualized 3C network, in which multiple service providers (SPs) are able to share the physical resources (i.e., bandwidth, storage and computation resources) from the same infrastructure provider (InP), and the users can dynamically choose the services from different SPs to maximize their utility. The dynamics of resource sharing between multiple SPs and users are modeled via a game theoretical approach. More specifically, the evolution and the dynamic behaviors of users are modeled as an evolutionary game. The competition among the SPs is formulated as a non-cooperative game, and an iterative algorithm is proposed to obtain its Nash equilibrium. Simulation results are presented to show the dynamics and equilibrium of the proposed game model.

The physical layer security in the up‐link of the wireless communication systems is often modelled as the multiple access wiretap channel (MAC‐WT), and recently it has received a lot attention. In this paper, the MAC‐WT has been re‐visited by considering the situation that the legitimate receiver feeds his received channel output back to the transmitters via two noiseless channels, respectively. This model is called the MAC‐WT with noiseless feedback. Inner and outer bounds on the secrecy capacity region of this feedback model are provided. To be specific, we first present a decode‐and‐forward (DF) inner bound on the secrecy capacity region of this feedback model, and this bound is constructed by allowing each transmitter to decode the other one's transmitted message from the feedback, and then each transmitter uses the decoded message to re‐encode his own messages, i.e. this DF inner bound allows the independent transmitters to co‐operate with each other. Then, we provide a hybrid inner bound which is strictly larger than the DF inner bound, and it is constructed by using the feedback as a tool not only to allow the independent transmitters to co‐operate with each other but also to generate two secret keys, respectively, shared between the legitimate receiver and the two transmitters. Finally, we give a sato‐type outer bound on the secrecy capacity region of this feedback model. The results of this paper are further explained via a Gaussian example, and from this example, we see that the noiseless feedback helps to enhance the achievable secrecy rate region of the Gaussian MAC‐WT without feedback.

Multimedia broadcast/multicast service (MBMS) transmission, which distributes the media content to multiple users on the same radio resources by using point-to-multipoint communications, is a highly spectrum efficient mechanism for multimedia communications. In this paper, we study the application of power domain non-orthogonal transmission to MBMS enhancements in a K-tier heterogeneous network, in order to satisfy the ever-increasing demands for emerging applications and performance requirements. Then, we present non-orthogonal multi-rate MBMS transmission (NOMRMT) and non-orthogonal multi-service MBMS transmission schemes and investigate their performance by using stochastic geometry. A tractable mode is developed to analyze the performance of asynchronous and synchronous non-orthogonal MBMS transmission. Based on this model, analytical expressions for the signal-to-interference-plus-noise ratio coverage probability, average number of served users, and sum rate are derived. The results demonstrate that non-orthogonal MBMS transmission can achieve better performance than the orthogonal one, while synchronous non-orthogonal MBMS transmission is superior to the asynchronous one.

Millimeter wave (mmWave) wireless networks can operate in single-cell point-to-multipoint mode to provide local multicast services efficiently. In this paper, the performance of multicast mmWave wireless networks is studied, through stochastic geometry. Then, the use of power domain non-orthogonal multiple access (NOMA) for enhancing mmWave multicasting is also investigated. Furthermore, we study multicasting in two-tier mmWave heterogeneous networks, and propose a novel cooperative NOMA multicast scheme. Analytical expressions for the signal-to-interference-plus-noise ratio coverage probability, the average number of served users, and the sum multicast rate are derived, in order to assess the performance of these schemes. Finally, we discuss the maximum sum multicast rates, by formulating them as optimization problems, and also develop efficient golden section search algorithms to solve them. The offered solutions reveal the impact of data transmission rate and power allocation on the sum multicast rate. Both analytical and numerical results demonstrate that NOMA can significantly improve the mmWave multicasting, while the proposed cooperative NOMA mmWave multicast scheme can further improve the NOMA mmWave multicasting.

We investigate the error performance of multidimensional constellations in the multiple access and broadcast channels. More specifically, we provide closed-form expressions for the pairwise error probability (PEP) of the joint maximum likelihood detection, for multiuser signaling in the presence of additive white Gaussian noise and Rayleigh fading. Arbitrary numbers of users and multidimensional signal sets are assumed, while the provided formula for the PEP is a function of the dimension-wise distances of the multidimensional constellation. Furthermore, a useful upper bound on the average symbol error probability is also obtained through the union bound. The analysis is applied to the sparse code multiple access systems. The analytical results are validated successfully through simulations, and show their importance in the multidimensional constellation design.

For the sake of supporting massive connectivity in the future 5G networks, non-orthogonal multiple access (NOMA) techniques are advocated. As a promising NOMA technique, in recent years sparse code multiple access (SCMA) has attracted substantial attention. However, there is a paucity of studies on the theoretical analysis of its error-freely achievable data rate, especially, in the downlink context. Hence, we derive the cutoff rate of SCMA in downlink broadcast channels, which indicates the lower-bound of a system's error-freely achievable rate. However, we will demonstrate that when considering the conventional categorization of pairwise error events, the accuracy of the cutoff rate rapidly degrades in the low-SNR region owing to the fact that multi-user SCMA systems typically encounter an extremely large constellation size. Alternatively, by invoking Bergmans' concept from 1973 in the categorization of pairwise error events, we obtain a more accurate cutoff rate both in the low- SNR regions and the high-SNR regions. Moreover, we provide insights into the cutoff rate derivation process, which reveals some general guidelines for designing a beneficial codebook, capable of improving SCMA with respect to its original low-density signature-based counterpart.

The finite-state Markov channel (FSMC), where the channel transition probability is controlled by a state undergoing a Markov process, is a useful model for the mobile wireless communication channel. In this paper, we investigate the security issue in the mobile wireless communication systems by considering the FSMC with an eavesdropper, which we call the finite-state Markov wiretap channel (FSM-WC). We assume that the state is perfectly known by the legitimate receiver and the eavesdropper, and through a noiseless feedback channel, the legitimate receiver sends his received channel output and the state back to the transmitter after some time delay. Inner and outer bounds on the capacity-equivocation regions of the FSM-WC with delayed state feedback and with or without delayed channel output feedback are provided in this paper, and we show that these bounds meet if the eavesdropper's received symbol is a degraded version of the legitimate receiver's. The above-mentioned results are further explained via a degraded Gaussian fading example.

The newly proposed sparse-code multiple-access (SCMA) has been shown to approach the single-user performance even the overload reaches 150% when message passing algorithm (MPA) detection is applied. Obviously, combined with multiple-input multiple-output (MIMO) techniques, the spectrum efficiency of SCMA system can be further improved. While maximum likelihood (ML) detection is optimal for MIMO-SCMA, the detection complexity would grow exponentially when the number of both the antennas and users increase. In this paper, we propose a novel low complexity joint MPA detection scheme for downlink MIMO-SCMA to utilize the sparsity of the channel and codeword. The analysis and simulation results show that compared with ML detection, the proposed joint MPA can decrease the complexity significantly while keep the BER performance unchanged.

In this paper, we investigate the application of spherical codes in a sparse code multiple access (SCMA) system. We use spherical codes to build multidimensional mother constellations for SCMA codebooks, to lower peak to average power ratio (PAPR) as well as to improve the overall spectrum efficiency. Furthermore, we introduce four approaches to construct good spherical codes. These codes are easy and have large coding gains. We make extensions to some of these spherical codes such that they are suitable for usage in SCMA systems. The performance of the constructed codebooks are compared to known codebooks through simulations, and the numerical results show that spherical codes based codebooks can effectively improve the system performance.

This paper investigates error performance of sparse code multiple access (SCMA) networks with multiple access channels (MAC) and broadcast channels (BC).We give the closed-form expression for the pairwise error probability (PEP) of joint maximum likelihood (ML) detection for multiuser signals over additive white Gaussian noise (AWGN) and Rayleigh fading channels with an arbitrary number of users and multidimensional codebooks. An upper bound for the average symbol error rate (SER) is calculated. The bound is tight in both AWGN channel and Rayleigh fading channels for high SNR regions. The analytical bounds are compared with simulations, and the results confirm the effectiveness of the analysis for both AWGN and Rayleigh fading channels.

In this paper, a general framework of the multiple- input multiple-output (MIMO) transceiver design for 5G multiple access (5GMA), including both non- orthogonal multiple access (NOMA) and sparsity code multiple access (SCMA), is developed to enhance the system throughput of next generation of communication systems. By applying generalized singular value decomposition (GSVD), MIMO channels can be decomposed into multiple single-input single- output (SISO) channels, to which the concept of NOMA and SCMA can ideally be applied. GSVD based precoding is proposed to both uplink and downlink 5GMA transmissions, and simulation results are provided to demonstrate the performance of the proposed schemes.

In this paper, an optimized codebook design based on rotated angles and extrinsic information transfer (EXIT) chart for a non-orthogonal multiple access scheme, called irregular sparse code multiple access (IrSCMA), is presented. Unlike regular SCMA, in IrSCMA, the defined degree of layer's resource nodes is different, which is beneficial to system performance.It is demonstrated that the new codebook can greatly improve the BER performance especially when the signal-to-noise ratio(SNR) is high, without sacrificing the low detection complexity, compared with the existing codebooks and LDS.

We propose a novel two-timeslot two-way full-duplex (FD) relaying scheme, in which the access link and the backhaul link are divided in the time domain, and we study the average end-to-end rate and the outage performance. According to the user equipment capability and services, we investigate two scenarios: three-node I- and four-node Y-relaying channels. Among various relaying protocols, the well-known amplify-and-forward and decode-and-forward are considered. Closed-form expressions for the average end-to-end rate and the outage probability, under the effect of residual self-interference and inter-user interference, are presented. The results show that the proposed two-timeslot two-way FD relaying scheme can achieve higher rate and better outage performance than the half-duplex one, when residual self-interference is below a certain level. Therefore, this relaying scheme presents a reasonable tradeoff between performance and complexity, and so, it could be efficiently used in the fifth-generation wireless networks.

In this paper, we investigate the effects of a trusted relay node on the secrecy of the broadcast channel by considering the model of relay broadcast channel with confidential messages (RBC-CM). Inner and outer bounds on the capacity-equivocation region of the RBC-CM are provided, and the capacity results are further explained via a degraded Gaussian example, which we call the degraded Gaussian relay broadcast channel with one common and one confidential messages. Numerical results show that this trusted relay node helps to enhance the security of the Gaussian broadcast channel with one common and one confidential messages.

In this paper, we systematically study the average rate and outage probability tradeoffs of full-duplex two-way and one-way relaying under residual self-interference. Among various relaying protocols, two common of them are considered: amplify-and-forward (AF) and decode-and-forward (DF). Furthermore, we consider the application of physical-layer network coding (PNC) and analog network coding (ANC) to full-duplex two-way relaying. Novel closed-form expressions for the average rate and outage probability, are presented. The results show that full-duplex two-way relaying can achieve higher rate than one-way relaying in the medium to high signal-to-noise ratio (SNR) region, at the cost of a certain loss in the outage performance. Moreover, DF protocol can achieve better outage performance than the AF one, but it suffers from a certain loss in the rate in the high SNR region. It is also shown that PNC can further improve the rate and outage performance. In addition, the results clearly reveal the effects of time multiplexing, forward protocol, and network coding on relaying systems, which would shed light on designing practical full-duplex relaying schemes.

In this paper, we investigate the effects of an additional trusted relay node on the secrecy of multiple-access wiretap channel (MAC-WT) by considering the model of multiple-access relay wiretap channel (MARC-WT). More specifically, first, we investigate the discrete memoryless MARC-WT. Three inner bounds [with respect to decode-and-forward (DF), noise-and-forward (NF), and compress-and-forward (CF) strategies] on the secrecy capacity region are provided. Second, we investigate the degraded discrete memoryless MARC-WT, and present an outer bound on the secrecy capacity region of this degraded model. Finally, we investigate the Gaussian MARC-WT, and find that the proposed relay strategies (DF, NF, CF strategies) help to enhance Tekin-Yener's achievable secrecy rate region of the Gaussian MAC-WT.

In this paper, we consider a two-way relaying scenario with one pair of source nodes, one relay and one eavesdropper. All nodes are equipped with multiple antennas, and we study the impact of antenna selection on such a secure communication scenario. Three transmission schemes with different tradeoff between secure performance and complexity are investigated respectively. Particularly, when antenna selection is implemented at the relay and no artificial noise is introduced, the condition to realize secure transmissions is established. Then by allowing the sources to inject artificial noise into the system, the secure performance is evaluated by focusing on different eavesdropping strategies. When both the relay and the sources send artificial noise, a low complexity strategy of antenna selection is proposed to efficiently utilize the antennas at the sources and the relay. The developed asymptotic results demonstrate that, by adding more artificial noise and performing joint antenna selection, a better secure performance, such as a larger secrecy rate and a lower outage probability, can be realized at a price of imposing more complexity on the system. Simulation results are also provided to demonstrate the accuracy of the developed analytical results.

The transmission rate, delivery reliability, and network lifetime are three fundamental but conflicting design objectives in energy-constrained wireless sensor networks (WSNs). In this paper, based on stochastic network utility maximization framework, we address the optimal rate-reliability-lifetime tradeoff with time-varying channel capacity constraint, reliability constraint, and energy constraint. By introducing the weight parameters, we combine the optimization objectives of rate, reliability, and lifetime into a single objective to characterize the tradeoff among them. However, the optimization formulation of the rate-reliability-reliability tradeoff is neither separable nor convex. Through a series of transformations, a separable problem is derived, and an efficient distributed stochastic subgradient algorithm is proposed via dual decomposition and stochastic subgradient techniques. It is proved that the proposed algorithm can converge to the global optimum with probability one. Numerical examples confirm its convergence. In addition, numerical examples investigate the impact of weight parameters on the rate utility, reliability utility, and network lifetime, which provide guidance to properly set the value of weight parameters for a desired performance of WSNs according to the realistic application's requirements.

Existing work has demonstrated that network coding can significantly reduce system delay in multi-source and multi-destination scenarios. However, such a scheme doesn't take consideration in terms of throughput In this paper, we propose to use rateless coding scheme to network-coded multi-source and multi-destination scenarios, which is a practical minimizing system delay and maximizing throughput approach. In particular, the analytical result based on outage probability has been developed. Numerical results have also been provided to show the delay and throughput performance of the proposed protocol.

Existing work has shown that random coding across multi-cast sessions can reduce the system delay significantly, however, such a scheme requires the strong assumption that each source has the priori information of other sources' messages. Actually the broadcasting nature of radio propagation can provide an opportunity to realize collaboration across sessions without causing much system overhead. In this paper, we propose the application of network coding to multi-source multi-destination (MSMD) scenarios and provide formal analysis for the improvement of system delay. In particular, two types of analytical results have been developed, one based on the outage probability and the other based on the use of practical convolutional codes. Monte-Carlo simulation results have also been provided to demonstrate the delay performance of the proposed network coded protocol.

In this paper, based on a belief-propagation decoding strategy, a class of generalized parity-check codes called complex rotary codes is investigated. It is shown that, by using iterative sum-product decoding, the complex rotary codes have a much lower decoding complexity than Turbo codes, but have almost the same performance for the high code rate and short frame case (frame length< 500 bits). It is also shown that the prime block size of complex rotary codes is essential to achieve better performance because of its uniform checking characteristic.

Two simple but effective methods for reducing the average complexity (and power consumption) of the conventional turbo-cyclic-redundancy-check decoding scheme with negligible performance degradation in a wideband direct-sequence code-division multiple-access (W-CDMA) environment are introduced. When applied to a W-CDMA turbo code with frame length 640 b at a bit-error rate (BER) of 10/sup -6/, the resultant modified schemes can save up to 73% of the average decoding complexity, relative to the conventional scheme. In general, the proposed schemes are more attractive for short-frame and low-BER applications.

A simple but effective method for reducing the average complexity (and power consumption) of turbo decoding with negligible performance degradation in a W-CDMA environment is introduced. It modifies the conventional turbo-CRC decoding scheme by performing two CRC tests per iteration to detect at the earliest a correctly converged decoding process. When applied to a W-CDMA turbo code with frame length 640 bits at a BER of 10/sup -6/, it can save about 50% of the average decoding complexity, relative to the conventional scheme. Further complexity reduction can be achieved by integrating the CRC test as an intermediate step in the component SlSO decoder. In general, the proposed scheme is more attractive for short-frame and low-BER applications.