Covert communication is an important approach to ensure information security by hiding the transmission behavior. Space-domain-coding intelligent reflecting surface (SDC-IRS) can adjust the phase of the reflection signal for passive beamforming in angle domains, which is widely employed in covert communications. However, the gains by SDC-IRS vanish when the warder is proximal to the receiver in angle domains. To overcome this limitation, in this paper, the space-time-coding IRS (STC-IRS) is considered, which can adjust both the phase and the frequency of the reflection signal for passive beamforming in angle-distance domains. Specifically, system performance under STC-IRS and SDC-IRS is compared, revealing the essence that angle and distance discrimination for the receiver is achieved with STC-IRS. Further, to fully exploit STC-IRS, optimization problems are formulated to maximize the covert rate in both line-of-sight scenarios and Rician fading scenarios. To solve the above problems, penalty-based algorithms are proposed where the transmit power, the phase shift and the frequency shift at STC-IRS are optimized jointly with majorization-minimization and block successive upper bound minimization techniques. Considering more general and adverse cases, the proposed algorithms are also extended to the scenario with multiple warders. Simulation results demonstrate the superiority of the proposed scheme compared with other benchmarks. Especially, when the warder and the receiver overlap in angle domains, covert rates with STC-IRS exceed 3 bps by distance domain discrimination, whereas covert rates with SDC-IRS are less than 0.01 bps.

Short-packet communications are applied to various scenarios where transmission covertness and reliability are crucial due to the open wireless medium and finite blocklength. Nonetheless, transmission covertness and reliability present a dilemma and significantly limit the throughput for short-packet communications. Intelligent reflection surface (IRS) is utilized in this paper to address this issue by enabling channel reconstruction, thereby releasing the fundamental limit between transmission covertness, reliability, latency (blocklength), and throughput. Specifically, to reveal the benefits brought by IRS, the achievable throughput without IRS is derived first in terms of the transmission covertness requirement, reliability requirement, and blocklength. Subsequently, the achievable throughput with IRS is derived, which releases the fundamental limit among the above-mentioned performance metrics. Besides, considering the phase uncertainty at IRS and limited channel estimation overhead, the cases where the warder/IRS knows instantaneous/statistical channel state information (CSI) of warder-related/legitimate links are all discussed, elucidating the impacts of CSI availability on the throughput. Furthermore, numerical results verify the accuracy of analytical results and demonstrate the benefits provided by IRS. Especially, the achievable covertness and reliability performance can be enhanced while the minimum required blocklength can be reduced by introducing IRS, which is crucial for short-packet communications.

Wireless short-packet communications pose challenges to the reliability and security of the transmission. Besides, the proactive warder compounds these challenges, who detects and interferes with the potential transmission. Thus, the tradeoff among reliability, covertness, latency (blocklength) and transmission rate is crucial, and efficient system design schemes are required for short-packet communications against the proactive warder. To address these issues, we investigate the reliable and covert performance of above systems. Specifically, detection error probabilities and their approximations are derived for cases where the warder knows the instantaneous/statistical channel state information. Besides, the decoding error probability is derived. The asymptotic relationship among the detection/decoding error probability, blocklength and transmission rate is established, revealing the non-trivial tradeoff between reliability and covertness performance. Furthermore, to maximize the effective throughput, an optimization framework is proposed under reliability and covertness constraints. Numerical results verify the tightness of the approximations and the feasibility of the optimization framework. Furthermore, it is shown that the proactive warder severely degrades the throughput compared to the passive one. And longer blocklength is always beneficial to improve the throughput for systems with optimized transmission rates, whereas the optimal blocklength is not necessarily the maximum one when transmission rates are fixed.

In this paper, the covert communication is considered with a full-duplex (FD) receiver under covertness and reliability constraints in the finite blocklength regime. Conventional covert communication systems are restricted by the square root law. To break through this limitation, an FD receiver is introduced, generating artificial noise (AN) to confuse the warder’s detection and achieving positive covert rates. To investigate the tradeoff among covertness, reliability, blocklength and throughput, the expressions of the warder’s detection error probability and the receiver’s decoding error probability in the finite blocklength regime are derived. Moreover, the asymptotic throughput is analyzed when the maximum transmit power of the FD receiver approaches infinity. Through the asymptotic analysis, we find that the blocklength’s impact on the covertness performance vanishes, which is a reason for achieving positive covert rates. However, the AN will also cause harmful residual self-interference to the receiver for which the FD receiver should be carefully designed by making a tradeoff between the covertness and the effective throughput. Hence, an optimization problem is formulated and solved to maximize the covert throughput. Numerical results show that the proposed scheme is effective in the finite blocklength regime where positive covert rates can be obtained.

Intelligent reflecting surface (IRS) is widely utilized in covert communications to enhance the system performance by passive beamforming. However, transmission covertness is seriously threatened when the warder is located on the line between IRS and the legitimate receiver. To overcome this limitation, the space-time-modulation IRS (STM-IRS) is considered in this paper, which can adjust both the phase and the frequency of the reflection signal to realize three-dimensional (3D) beam focusing. To maximize the signal-to-noise ratio at the receiver, an optimization problem is formulated by jointly adjusting the transmit power, the phase and the frequency shift at each reflection element. To solve above non-convex problem with highly coupled optimization variables, a penalty-based algorithm is proposed wherein the majorization-minimization technique and block successive upper bound minimization technique are adopted. Simulation results demonstrate that 3D beam focusing can be realized by STM-IRS to distinguish the warder and the legitimate receiver in both angle and range domains. Besides, the proposed scheme outperforms the scheme without frequency shift and other existing frequency shift schemes.

To realize the vision of the Internet of Things (IoT), mobile-edge computing (MEC) has recently emerged as a promising paradigm to meet the computation demand from mobile users (MUs). In this article, we study the network performance in large-scale stochastic MEC wireless networks, where the tasks can be computed locally by the local computation capabilities (LCCs) or be offloaded to MEC servers for edge computing. To this end, a MEC network is modeled featuring random node distribution, dynamic task requests, orthogonal frequency-division multiple access, task retransmission, and parallel computing in MEC servers. Given the model, a 2-D discrete-time Markov chain is first adopted to characterize the task execution process, including local computing and task offloading. Based on the coupling between communication and computing, the average outage probability of the task transmission and the average MEC computation load are derived by integrating the stochastic geometry and queuing theory. Furthermore, by jointly analyzing the local computation latency, transmission latency, and edge computation latency, we derive the average end-to-end latency of the task execution. Our results show that the LCCs in MUs can improve the network performance, including communication and computation performance, in stochastic MEC networks. In addition, useful guidelines for MEC network provisioning and planning are provided to avoid either the local computing or the task offloading being the latency performance bottleneck.

In this paper, the downlink outage performance of full-duplex (FD) multi-cell networks considering interference cancellation at receivers is investigated. Different from previous FD cellular works, where all the interference is assumed to be perfectly cancelled, we propose the concept of strong interference region to distinguish strong interference and weak interference. A practical interference cancellation scheme is proposed to suppress the strong interference. Instead of assuming full-loaded cells in the analysis on FD networks, we consider the dynamic traffic request of the users in the stochastic networks where the cells may not always actively transmit and/or receive signals, consequently they do not always introduce interference to others. The probabilities of base stations (BSs) working in the FD, downlink, uplink and idle modes have been derived. To evaluate the system performance, we derive the outage probability and throughput. The simulation results show that outage performance is significantly improved compared to that without interference cancellation. Meanwhile, after cancelling the strong interference, the performance approaches that of cancelling all the interference. The impacts of the number of user equipments (UEs), the traffic request rate, the density of BSs and the size of the strong interference region on outage performance and throughput performance are further revealed.

Probabilistic shaping (PS) combined with bipolar amplitude shift keying modulation is a promising transmission scheme. However, such 1-dimensional PS scheme inevitably suffers shaping loss in Rayleigh fading channels due to the lack of signal diversity. In this paper, we design a rotated quadrature amplitude modulation based PS strategy. With the discrete inputs, the ergodic constellation constrained (CC) capacity is derived based on the mutual information conditioned on full channel state information available at the receiver, which is found to be mutually influenced by both the probability mass function (PMF) and the rotation angle (RA) of the input signals. Furthermore, the closed-form cutoff rate is also derived to simplify the analysis, which is the lower bound of the mutual information with finite decoding complexity. Correspondingly, the optimizations of RA and PMF are both considered for maximizing the ergodic CC capacity and the cutoff rate, respectively, where the single parameter RA is firstly obtained by the exhaustive search. And then, the optimal PMFs of the subproblem for the fixed RAs and the fixed constellation scaling factor are obtained. Furthermore, with this non-equiprobable transmission scheme, the closed-form pairwise error probability is derived for the first time, which also validates the superiority of the proposed PS scheme in comparison with the uniform schemes with elaborate rotations.

Probabilistic shaping (PS) combined with amplitude shift keying modulation is a spectrally efficient transmission scheme. To exploit the shaping gain in fading channels, we design a rotated quadrature amplitude modulation (QAM) based PS strategy. With discrete inputs, we first derive the ergodic constellation constrained (CC) capacity, which is found to be mutually influenced by both the probability mass function (PMF) and the rotation angle (RA) of input signals. Correspondingly, the optimal PMF and RA for maximizing the ergodic CC capacity are attained by the alternative optimization method. Furthermore, based on this non-equiprobable transmission scheme, the closed- form pairwise error probability is obtained for the first time. Finally, compared with the uniform scheme with elaborate rotation, the proposed PS strategy shows more than 1 dB gain in terms of both the efficiency and the error performance.

Multi-User scheduling is challenging due to the channel unbalance problem, which leads to system performance degradation. In this paper, two optimal multi-user scheduling schemes maximizing the system throughput are proposed for the fixed and adaptive power transmission scenarios of the full-duplex (FD) multi-user buffer-aided relay system, respectively. Independent and non-identically distributed (i.ni.d.) model is used to characterize the unbalanced channels of different links. In particular, the optimal weight factor of each pair is designed based on the statistical channel state information in both scenarios. With the weight factors, the proposed schemes are able to balance the throughput gaps between different links. In addition, we propose an optimal power allocation scheme with closed-form expressions under average power constraint for the adaptive power transmission scenario. By combining the optimal weight factor and the power allocation scheme, novel optimal selection function is obtained to facilitate the selection process. Considering the specific i.ni.d. Rayleigh fading, the system throughput is further derived in both cases. Theoretical analysis is verified by the numerical simulations and the results demonstrate the superiority of the proposed schemes.

In this paper, we investigate fundamental throughput and delay tradeoffs in cognitive radio networks (CRN) with a primary user (PU) and a cooperative secondary user (SU). Considering the user fairness, we propose a novel cooperation scheme, where the PU transmits packets with a probability of α instead of always occupying the spectrum, in exchange for the SU's cooperation. The unauthorized SU can sense the environment periodically and get access to the licensed spectrum when the PU is idle. The SU will either transmit its own packets or forward the PU's packets based on a priority factor β. Considering the bursty nature of the sources, Markov chain model is used to characterize the evolution of buffer states. Based on the steady state probabilities, the average buffer length and the system's stable throughput region are obtained. The impacts of the cooperation scheme (α,β) on the throughput tradeoff between the PU and the SU are theoretically analyzed. We also derive the average end-to-end transmission delay of the two users. The throughput-delay tradeoff and the impacts of the link qualities on the system performance are analyzed. The accuracy of the analytical results are validated by simulations.

Exploiting cognition to the cache-enabled device-to- device (D2D) communication underlaying the multi- channel cellular network is the main focus of this paper. D2D pairs perform direct communications via sensing the available cellular channels, bypassing the base station (BS). Dynamic service is considered and the network performance is evaluated with the stochastic geometry. Node locations are first modeled as mutually independent Poisson Point Processes, and the service queueing process is formulated. Then the corresponding tier association and cognitive access protocol are developed. The delay and the length for the queue at the BS and D2D transmitter are further elaborated, with modeling the traffic dynamics of request arrivals and departures as the discrete-time multiserver queue with priorities. Moreover, impacts of the physical layer and content-centric features on the system performance are jointly investigated to provide a valuable insight.

Caching popular multimedia content is a promising way to unleash the ultimate potential of wireless networks. In this paper, we propose and analyze cache-based content delivery in a three-tier heterogeneous network (HetNet), where base stations (BSs), relays, and device-to-device (D2D) pairs are included. We advocate proactively caching popular content in the relays and parts of the users with caching ability when the network is off-peak. The cached content can be reused for frequent access to offload the cellular network traffic. The node locations are first modeled as mutually independent Poisson point processes (PPPs) and the corresponding content access protocol is developed. The average ergodic rate and outage probability in the downlink are then analyzed theoretically. We further derive the throughput and the delay based on the multiclass processor-sharing queue model and the continuous-time Markov process. According to the critical condition of the steady state in the HetNet, the maximum traffic load and the global throughput gain are investigated. Moreover, impacts of some key network characteristics, e.g., the heterogeneity of multimedia contents, node densities, and the limited caching capacities, on the system performance are elaborated on to provide valuable insight.

Pushing and caching the popular multimedia data is a promising way to unleash the ultimate potential of wireless networks. In this paper, we contribute to proposing and analyzing the push-based and cache-based content delivery in a three-tier heterogeneous network, where base stations, relays and device-to-device (D2D) pairs are included. We propose to proactively push the popular contents to the relays and parts of the users with caching ability via broadcasting when the network is off-peak. The cached contents can be reused for frequent access to offload the cellular network traffic. The node locations are first modeled as mutually independent Poisson Point Processes (PPPs) and the corresponding content access protocol is developed. The average ergodic rates in the downlink are then analyzed theoretically. We further derive the global throughput gain and the impact of network characteristics on the system performance is illustrated. Simulation results show that the proposed system has significant performance gain, especially for the high density network.

Pushing and caching the popular multimedia data can effectively reduce the redundant content transmission and cope with the explosive traffic growth. In this paper, we contribute to analyzing the push-based and cache-based content delivery in the heterogeneous network (HetNet). When the network load is off-peak, the most popular contents can be pushed to the relays and the cache-enabled users via broadcasting, and then be cached down to be reused for frequent access. The locations of the base stations, relays and device-to-device pairs are first modeled as mutually independent Poisson Point Processes (PPPs). Then the energy consumption is derived based on the access protocol and the tier association priority. The impacts of network characteristics such as the heterogeneity of multimedia contents, node densities and the limited caching capacity are further elaborated. Besides, the node densities allocation strategy is discussed for full use of the caching resources, which provides valuable insights on the wireless intelligent network planning.

Energy harvesting is an efficient method for extending the lifetime of energy-constrained networks. In this paper, we develop a wireless energy harvesting and information transfer protocol in cognitive two-way relay networks, in which a secondary network scavenges energy from ambient signals of primary network while shares the spectrum by assisting the primary transmission. In particular, two primary users exchange information through an energy harvesting secondary user which firstly harvests energy from the received primary signals and then uses the harvested energy to forward the remaining primary signals along with the secondary signals. The exact expressions of the outage probabilities for the primary network are analytically formulated. Besides, we derive the lower and upper bounds of the outage probability for the secondary network. Following aforementioned deduction, we analyze the energy efficiency of the whole system. Simulation results show that we can achieve maximum energy efficiency if we set up proper parameters. Finally, numerical results verify our theoretical derivation and demonstrate that the proposed protocol enables the high-quality transmission for both the primary and secondary network without extra relay energy consumed.

Storing the popular contents in the caches to enable frequency reuse, wireless cooperative caching approach offers an exciting new way to unleash the ultimate potential of wireless networks. In this paper, we formulate the optimal caching problem to minimize the energy consumption in the wireless cooperative caching network by considering some important constraints, including the limited storage capacity, the content popularity and the content access protocol. A sub-optimal caching strategy is then proposed to handle the optimal content placement in the caches, reducing the energy consumption. Simulation results show that the proposed sub-optimal caching scheme has significant energy saving compared with the random caching scheme. Furthermore, the impact of the network resource and parameters on the system performance is also investigated in terms of the energy saving and the cache hit rate.