Virtual reality (VR) streaming demands both high data rates and low latency, requiring advanced transmission strategies to enhance system performance in wireless networks. This paper proposes a hierarchical rate-splitting multiple access-based cell-free (HRS-CF) VR transmission strategy, which integrates field of view (FoV)-based user grouping, scalable video coding (SVC)-based message design, and message-centric base station selection. Moreover, to characterize the statistical data rate of VR services under a given delay constraint, we investigate the effective capacity (EC) of the VR video streaming under HRS-CF strategy. Furthermore, we jointly optimize the precoding matrix, rate splitting coefficients, and BS selection using the proximal policy optimization (PPO) algorithm, where a power threshold-based BS selection is introduced to reduce computational complexity. Simulation results show that the proposed HRS-CF strategy outperforms the conventional rate splitting and CF transmission schemes, achieving at least a 16% performance improvement.

Drawing upon a data-driven methodology, deep learning has emerged as an innovative approach for dynamic resource allocation in large-scale cellular networks. This paper proposes an optimization strategy relying on domain adversarial networks to reduce the number of poorly performing base stations (BSs). The approach dynamically allocates radio resources to address real-time mobile traffic needs. We calculate the interference coefficients among BSs and design a performance classifier that evaluates BS performance with respect to provided traffic-resource pairs as either poor or good. Most importantly, we use well-performing BSs as source domain data to reallocate the resources of poorly performing ones through the domain adversarial neural network. Experimental results demonstrate that the proposed domain adversarial resource allocation strategy effectively decreases the number of poorly performing BSs in the cellular network, which in turn outperforms other benchmark algorithms in terms of both the ratio of poor BSs and radio resource consumption.

Federated learning (FL), as a privacy-enhancing distributed learning paradigm, has recently attracted much attention in wireless systems. By providing communication and computation services, the base station (BS) helps participants collaboratively train a shared model without transmitting raw data. Concurrently, with the advent of integrated sensing and communication (ISAC) and the growing demand for sensing services, it is envisioned that BS will simultaneously serve sensing services, as well as communication and computation services, e.g., FL, in future 6G wireless networks. To this end, we provide a novel integrated sensing, communication and computation (ISCC) system, called Fed-ISCC, where BS conducts sensing and FL in the same time-frequency resource, and the over-the-air computation (AirComp) is adopted to enable fast model aggregation. To mitigate the interference between sensing and FL during uplink transmission, we propose a receive beamforming approach. Subsequently, we analyze the convergence of FL in the Fed-ISCC system, which reveals that the convergence of FL is hindered by device selection error and transmission error caused by sensing interference, channel fading and receiver noise. Based on this analysis, we formulate an optimization problem that considers the optimization of transceiver beamforming vectors and device selection strategy, with the goal of minimizing transmission and device selection errors while ensuring the sensing requirement. To address this problem, we propose a joint optimization algorithm that decouples it into two main problems and then solves them iteratively. Simulation results demonstrate that our proposed algorithm is superior to other comparison schemes and nearly attains the performance of ideal FL.

Given the popularity of flawless telepresence and the resultants explosive growth of wireless video applications, besides handling the traffic surge, satisfying the demanding user requirements for video qualities has become another important goal of network operators. Inspired by this, cooperative edge caching intrinsically amalgamated with scalable video coding is investigated. Explicitly, the concept of a Pareto-optimal semi-distributed multiagent multipolicy deep reinforcement learning (SD-MAMP-DRL) algorithm is conceived for managing the cooperation of heterogeneous network nodes. To elaborate, a multipolicy reinforcement learning algorithm is proposed for finding the Pareto-optimal policies during the training phase, which balances the teletraffic versus the user experience tradeoff. Then the optimal policy/solution can be activated during the execution phase by appropriately selecting the associated weighting coefficient according to the dynamically fluctuating network traffic load. Our experimental results show that the proposed SD-MAMP- acrshort DRL algorithm: 1) achieves better performance than the benchmark algorithms and 2) obtains a near-complete Pareto front in various scenarios and selects the optimal solution by adaptively adjusting the above-mentioned pair of objectives.

Super-Resolution (SR) algorithms aim to enhance the resolutions of images. Massive deep-learning-based SR techniques have emerged in recent years. In such case, a visually appealing output may contain additional details compared with its reference image. Accordingly, fully referenced Image Quality Assessment (IQA) cannot work well; however, reference information remains essential for evaluating the qualities of SR images. This poses a challenge to SR-IQA: How to balance the referenced and no-reference scores for user perception? In this paper, we propose a Perception-driven Similarity-Clarity Tradeoff (PSCT) model for SR-IQA. Specifically, we investigate this problem from both referenced and no-reference perspectives, and design two deep-learning-based modules to obtain referenced and no-reference scores. We present a theoretical analysis based on Human Visual System (HVS) properties on their tradeoff and also calculate adaptive weights for them. Experimental results indicate that our PSCT model is superior to the state-of-the-arts on SR-IQA. In addition, the proposed PSCT model is also capable of evaluating quality scores in other image enhancement scenarios, such as deraining, dehazing and underwater image enhancement. The source code is available at https://github.com/kekezhang112/PSCT.

Relying on a data-driven methodology, deep learning has emerged as a new approach for dynamic resource allocation in large-scale cellular networks. This paper proposes a knowledge-assisted domain adversarial network to reduce the number of poorly performing base stations (BSs) by dynamically allocating radio resources to meet real-time mobile traffic needs. Firstly, we calculate theoretical inter-cell interference and BS capacity using Voronoi tessellation and stochastic geometry, which are then incorporated into a neural network as key parameters. Secondly, following the practical assessment, a performance classifier evaluates BS performance based on given traffic-resource pairs as either poor or good. Most importantly, we use well-performing BSs as source domain data to reallocate the resources of poorly performing ones through the domain adversarial neural network. Our experimental results demonstrate that the proposed knowledge-assisted domain adversarial resource allocation (KDARA) strategy effectively decreases the number of poorly performing BSs in the cellular network, and in turn, outperforms other benchmark algorithms in terms of both the ratio of poor BSs and radio resource consumption.

This work proposes a covert communication scheme in a cognitive radio network where a secondary transmitter (ST) transmits confidential information to a secondary receiver under the cover of jammers with homogeneous Poisson point process. Specifically, we first analyze the detection performance of the primary transmitter (PT) and Willie under collaboration and non-collaboration modes. We then derive the covert transmission outage probability under ST’s correct and incorrect decisions for whether PT transmits or not and obtain the expression for the effective covert rate (ECR). In order to maximize the ECR, we derive the optimal value of the time allocation ratio, based on which, we also derive the optimal value of ST’s transmit power subject to the covertness constraint and some power constraints. Our examination shows the non-collaboration mode outperforms the collaboration mode in terms of achieving a higher ECR, because the uncertainty of the PT’s transmission in the former one will cause confusion at Willie and lead to an increased detection error rate. In addition, the proposed scheme effectively increases the ECR when compared with the scheme without the jammer.

Mobile edge computing (MEC) and field-of-view (FoV) prediction are two key techniques to enable the wireless virtual reality (VR) service. On this basis, we investigate a practical issue, that is, how to efficiently achieve the user's pre-set quality-of-experience (QoE) requirement on both video quality and delay tolerance. A constrained reward-steering algorithm based on reinforcement learning is proposed in this work to solve this multi-objective optimization problem, which finds the optimal policy approaching the user's targeted QoE. Meanwhile, both an instantaneous service delay constraint and a long-term energy constraint are satisfied by the Lagrangian-based method. Simulation results demonstrate that the proposed algorithm outperforms conventional reinforcement learning relying on weights, i.e. achieving an average reward vector much closer to the user's targeted QoE, and meeting both constraints.

Multi-hop transmissions are desirable in realizing large-scale long-distance covert wireless communications, since a single-hop transmission cannot fully satisfy the covertness requirement even with high transmit power. Against this background, this work compares amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies by examining their achievable effective throughput taking into the covertness quality-of-service. To this end, we first present a framework of maximizing the effective throughput with the assumption that each relay adopts equal transmit power to seek mathematical tractability. With the number of relays and each relay’s transmit power optimized, our results reveal that DF relaying outperforms AF relaying in the considered multi-hop covert communications, in terms of achieving a higher effective throughput with a smaller optimal number of relays. This is mainly due to that regardless of the same detection performance at the warden Willie for AF and DF relaying under the same condition, AF relays amplify both information and noise signals, while DF relays only forward the information signals. In addition, our examinations show that DF relaying with independent codewords achieves a higher effective throughput with a fewer number of relays relative to the DF relaying with a single-codeword. Furthermore, we find that the optimal number of relays increases as the desired covert communication distance increases or the covertness constraint becomes stringent.

Random frequency diverse array (RFDA) based directional modulation (DM) was proposed as a promising technology in secure communications to achieve a precise transmission of confidential messages, and artificial noise (AN) was considered as an important helper in RFDA-DM. Compared with previous works that only focus on the spot of the desired receiver, in this work, we investigate a secrecy region around the desired receiver, that is, a specific range and angle resolution around the desired receiver. Firstly, the minimum number of antennas and the bandwidth needed to achieve a secrecy region are derived. Moreover, based on the lower bound of the secrecy capacity in RFDA-DM-AN scheme, we investigate the performance impact of AN on the secrecy capacity. From this work, we conclude that: 1) AN is not always beneficial to the secure transmission. Specifically, when the number of antennas is sufficiently large and the transmit power is smaller than a specified value, AN will reduce secrecy capacity due to the consumption of limited transmit power. 2) Increasing bandwidth will enlarge the set for randomly allocating frequencies and thus lead to a higher secrecy capacity. 3) The minimum number of antennas increases as the predefined secrecy transmission rate increases.

Covert communications can hide the very existence of wireless transmissions and thus are able to address privacy issues in numerous applications of the emerging Internet of Things (IoT). In this article, we adopt channel inversion power control (CIPC) to achieve covert communications in Rayleigh fading wireless networks, where a transmitter can possibly hide itself from a warden while transmitting information to a receiver. The CIPC can guarantee a constant signal power at the receiver, which removes the requirement that the receiver has to know the channel state information in order to coherently decode the transmitter's signal. Specifically, we examine the performance of the achieved covert communications in terms of the effective covert rate (ECR), which quantifies the amount of information that the transmitter can reliably convey to the receiver subject to the warden's total error probability being no less than some specific value. The noise uncertainty at the warden serves as the enabler of covert communications. For fairness, we also consider noise uncertainty at the legitimate receiver. Our examination shows that increasing the noise uncertainty at the warden and the receiver simultaneously may not continuously improve the ECR achieved in the considered system model.

This work, for the first time, tackles channel estimation design with pilots in the context of covert wireless communication. We consider Rayleigh fading for the communication channel from a transmitter to a receiver, both additive white Gaussian noise (AWGN) and Rayleigh fading for the detection channel from the transmitter to a warden. Before transmitting information signals, the transmitter has to send pilots to enable channel estimation at the receiver. For the case with AWGN detection channel, we first analytically prove that transmitting pilot and information signals with equal power minimizes the warden's detection performance. This motivates us to consider the equal transmit power and then optimize channel use allocation between pilot and information signals under this case. Our analysis shows that the optimal number of the channel uses allocated to pilots increases as the covertness constraint becomes tighter. For the case with Rayleigh fading detection channel, we present a general framework to optimally allocate transmit power and channel uses between pilot and information signals. Our examination shows that the covert communication performance gain achieved by this general framework is not remarkable relative to the scheme with equal transmit power and this gain diminishes as the covertness constraint becomes stricter.

This paper examines the possibility, performance limits, and associated costs for a self-sustained relay to transmit its own covert information to a destination on top of forwarding the source's information. Since the source provides energy to the relay for forwarding its information, the source does not allow the relay's covert transmission and to detect it. Considering the time switching (TS) and power splitting (PS) schemes for energy harvesting, where all the harvested energy is used for transmission at the self-sustained relay, we derive the minimum detection error probability ξ* at the source based on which we determine the maximum effective covert rate ψ* subject to a given covertness constraint on ξ*. Our analysis shows that ξ* is the same for the TS and PS schemes, which leads to the fact that the cost of achieving ψ* in both the two schemes in terms of the required increase in the energy conversion efficiency at the relay is the same, although the values of ψ* in these two schemes can be different in specific scenarios. For example, the TS scheme outperforms the PS scheme in terms of achieving a higher ψ* when the transmit power at the source is relatively low. If the covertness constraint is tighter than a specific value, it is the covertness constraint that limits ψ*, and otherwise, it is upper bound on the energy conversion efficiency that limits ψ*.

In this work, we propose a covert communication scheme where the transmitter attempts to hide its transmission to a full-duplex receiver, from a warden that is to detect this covert transmission using a radiometer. Specifically, we first derive the detection error rate at the warden, based on which the optimal detection threshold for its radiometer is analytically determined and its expected detection error rate over wireless fading channels is achieved in a closed-form expression. Our analysis indicates that the artificial noise deliberately produced by the receiver with a random transmit power, although causes self-interference, offers the capability of achieving a positive effective covert rate for any transmit power (can be infinity) subject to any given covertness requirement on the expected detection error rate. This work is the first study on the use of the full- duplex receiver with controlled artificial noise for achieving covert communications and invites further investigation in this regard.

In this paper, a practical wireless transmission scheme is proposed to transmit confidential messages to the desired user securely and precisely by the joint use of multiple techniques, including artificial noise (AN) projection, phase alignment/beamforming, and random subcarrier selection (RSCS) based on orthogonal frequency division multiplexing (OFDM), and directional modulation (DM), namely RSCS-OFDM-DM. This RSCS-OFDM-DM scheme provides an extremely low-complexity structure for the desired receiver and makes the secure and precise wireless transmission realizable in practice. For illegal eavesdroppers, the receive power of confidential messages is so weak that their receivers cannot intercept these confidential messages successfully once it is corrupted by AN. In such a scheme, the design of phase alignment/beamforming vector and AN projection matrix depends intimately on the desired direction angle and distance. It is particularly noted that the use of RSCS leads to a significant outcome that the receive power of confidential messages mainly concentrates on the small neighboring region around the desired receiver and only small fraction of its power leaks out to the remaining large broad regions. This concept is called secure precise transmission. The probability density function of real-time receive signal-to-interference-and-noise ratio (SINR) is derived. Also, the average SINR and its tight upper bound are attained. The approximate closed-form expression for average secrecy rate is derived by analyzing the first-null positions of the SINR and clarifying the wiretap region. Simulation and analysis show that the proposed scheme actually can achieve a secure and precise wireless transmission of confidential messages in line-of-propagation channel, and the derived theoretical formula of average secrecy rate is verified to coincide with the exact results well for medium and large scale transmit antenna array or in the low and medium SNR regions.

Covert wireless communication aims to hide the very existence of wireless transmissions in order to guarantee a strong security in wireless networks. In this paper, we examine the possibility and achievable performance of covert communication in amplify-and-forward one-way relay networks. Specifically, the relay is greedy and opportunistically transmits its own information to the destination covertly on top of forwarding the source's message, while the source tries to detect this covert transmission to discover the illegitimate usage of the resource (e.g., power and spectrum) allocated only for the purpose of forwarding the source's information. We propose two strategies for the relay to transmit its covert information, namely rate-control and power-control transmission schemes, for which the source's detection limits are analyzed in terms of detection error probability and the achievable effective covert rates from the relay to destination are derived. Our examination determines the conditions under which the rate-control transmission scheme outperforms the power-control transmission scheme, and vice versa, which enables the relay to achieve the maximum effective covert rate. Our analysis indicates that the relay has to forward the source's message to shield its covert transmission and the effective covert rate increases with its forwarding ability (e.g., its maximum transmits power).

Covert communications hide the transmission of a message from a watchful adversary while ensuring a certain decoding performance at the receiver. In this paper, a wireless communication system under fading channels is considered where covertness is achieved by using a full-duplex receiver. More precisely, the receiver of covert information generates artificial noise with a varying power causing uncertainty at the adversary, Willie, regarding the statistics of the received signals. Given that Willie's optimal detector is a threshold test on the received power, we derive a closed-form expression for the optimal detection performance of Willie averaged over the fading channel realizations. Furthermore, we provide guidelines for the optimal choice of artificial noise power range, and the optimal transmission probability of covert information to maximize the detection errors at Willie. Our analysis shows that the transmission of artificial noise, although causing self-interference, provides the opportunity of achieving covertness but its transmit power levels need to be managed carefully. We also demonstrate that the prior transmission probability of 0.5 is not always the best choice for achieving the maximum possible covertness when the covert transmission probability and artificial noise power can be jointly optimized.

Covert communication aims to shield the very existence of wireless transmissions in order to guarantee a strong security in wireless networks. In this work, for the first time we examine the possibility and achievable performance of covert communication in one- way relay networks. Specifically, the relay opportunistically transmits its own information to the destination covertly on top of forwarding the source's message, while the source tries to detect this covert transmission to discover the illegitimate usage of the recourse (e.g., power, spectrum) allocated only for the purpose of forwarding source's information. The necessary condition that the relay can transmit covertly without being detected is identified and the source's detection limit is derived in terms of the false alarm and miss detection rates. Our analysis indicates that boosting the forwarding ability of the relay (e.g., increasing its maximum transmit power) also increases its capacity to perform the covert communication in terms of achieving a higher effective covert rate subject to some specific requirement on the source's detection performance.

In this paper, spatial channel pairing (SCP) is introduced to coherent combining at the relay in relay networks. Closed-form solution to optimal coherent combining is derived. Given coherent combining, the approximate SCP solution is presented. Finally, an alternating iterative structure is developed. Simulation results and analysis show that, given the symbol error rate and data rate, the proposed alternating iterative structure achieves signal-to-noise ratio gains over existing schemes in maximum ratio combining (MRC) plus matched filter, MRC plus antenna selection, and distributed space-time block coding due to the use of SCP and iterative structure.