Joint Relay Selection and Power Allocation in Large-Scale MIMO Systems with Untrusted Relays and Passive Eavesdroppers

In this paper, a joint relay selection and power allocation (JRP) scheme is proposed to enhance the physical layer security of a cooperative network, where a multiple antennas source communicates with a single-antenna destination in presence of untrusted relays and passive eavesdroppers (Eves). The objective is to protect the data confidentially while concurrently relying on the untrusted relays as potential Eves to improve both the security and reliability of the network. To realize this objective, we consider cooperative jamming performed by the destination while JRP scheme is implemented. With the aim of maximizing the instantaneous secrecy rate, we derive a new closed-form solution for the optimal power allocation and propose a simple relay selection criterion under two scenarios of non-colluding Eves (NCE) and colluding Eves (CE). For the proposed scheme, a new closed-form expression is derived for the ergodic secrecy rate (ESR) and the secrecy outage probability as security metrics, and a new closed-form expression is presented for the average symbol error rate (SER) as a reliability measure over Rayleigh fading channels. We further explicitly characterize the high signal-to-noise ratio slope and power offset of the ESR to highlight the impacts of system parameters on the ESR. In addition, we examine the diversity order of the proposed scheme to reveal the achievable secrecy performance advantage. Finally, the secrecy and reliability diversity-multiplexing tradeoff of the optimized network are provided. Numerical results highlight that the ESR performance of the proposed JRP scheme for NCE and CE cases is increased with respect to the number of untrustworthy relays.Comment: 18 pages, 10 figures, IEEE Transactions on Information Forensics and Security (In press

Wireless powered D2D communications underlying cellular networks: design and performance of the extended coverage

Because of the short battery life of user equipments (UEs), and the requirements for better quality of service have been more demanding, energy efficiency (EE) has emerged to be important in device-to-device (D2D) communications. In this paper, we consider a scenario, in which D2D UEs in a half-duplex decode-and-forward cognitive D2D communication underlying a traditional cellular network harvest energy and communicate with each other by using the spectrum allocated by the base station (BS). In order to develop a practical design, we achieve the optimal time switching (TS) ratio for energy harvesting. Besides that, we derive closed-form expressions for outage probability, sum-bit error rate, average EE and instantaneous rate by considering the scenario when installing the BS near UEs or far from the UEs. Two communication types are enabled by TS-based protocol. Our numerical and simulation results prove that the data rate of the D2D communication can be significantly enhanced.Web of Science58439939

A Lightweight Secure and Resilient Transmission Scheme for the Internet of Things in the Presence of a Hostile Jammer

In this article, we propose a lightweight security scheme for ensuring both information confidentiality and transmission resiliency in the Internet-of-Things (IoT) communication. A single-Antenna transmitter communicates with a half-duplex single-Antenna receiver in the presence of a sophisticated multiple-Antenna-Aided passive eavesdropper and a multiple-Antenna-Assisted hostile jammer (HJ). A low-complexity artificial noise (AN) injection scheme is proposed for drowning out the eavesdropper. Furthermore, for enhancing the resilience against HJ attacks, the legitimate nodes exploit their own local observations of the wireless channel as the source of randomness to agree on shared secret keys. The secret key is utilized for the frequency hopping (FH) sequence of the proposed communication system. We then proceed to derive a new closed-form expression for the achievable secret key rate (SKR) and the ergodic secrecy rate (ESR) for characterizing the secrecy benefits of our proposed scheme, in terms of both information secrecy and transmission resiliency. Moreover, the optimal power sharing between the AN and the message signal is investigated with the objective of enhancing the secrecy rate. Finally, through extensive simulations, we demonstrate that our proposed system model outperforms the state-of-The-Art transmission schemes in terms of secrecy and resiliency. Several numerical examples and discussions are also provided to offer further engineering insights

AI-Generated Incentive Mechanism and Full-Duplex Semantic Communications for Information Sharing

The next generation of Internet services, such as Metaverse, rely on mixed reality (MR) technology to provide immersive user experiences. However, the limited computation power of MR headset-mounted devices (HMDs) hinders the deployment of such services. Therefore, we propose an efficient information sharing scheme based on full-duplex device-to-device (D2D) semantic communications to address this issue. Our approach enables users to avoid heavy and repetitive computational tasks, such as artificial intelligence-generated content (AIGC) in the view images of all MR users. Specifically, a user can transmit the generated content and semantic information extracted from their view image to nearby users, who can then use this information to obtain the spatial matching of computation results under their view images. We analyze the performance of full-duplex D2D communications, including the achievable rate and bit error probability, by using generalized small-scale fading models. To facilitate semantic information sharing among users, we design a contract theoretic AI-generated incentive mechanism. The proposed diffusion model generates the optimal contract design, outperforming two deep reinforcement learning algorithms, i.e., proximal policy optimization and soft actor-critic algorithms. Our numerical analysis experiment proves the effectiveness of our proposed methods. The code for this paper is available at https://github.com/HongyangDu/SemSharingComment: Accepted by IEEE JSA

Spectral Efficient and Energy Aware Clustering in Cellular Networks

The current and envisaged increase of cellular traffic poses new challenges to Mobile Network Operators (MNO), who must densify their Radio Access Networks (RAN) while maintaining low Capital Expenditure and Operational Expenditure to ensure long-term sustainability. In this context, this paper analyses optimal clustering solutions based on Device-to-Device (D2D) communications to mitigate partially or completely the need for MNOs to carry out extremely dense RAN deployments. Specifically, a low complexity algorithm that enables the creation of spectral efficient clusters among users from different cells, denoted as enhanced Clustering Optimization for Resources' Efficiency (eCORE) is presented. Due to the imbalance between uplink and downlink traffic, a complementary algorithm, known as Clustering algorithm for Load Balancing (CaLB), is also proposed to create non-spectral efficient clusters when they result in a capacity increase. Finally, in order to alleviate the energy overconsumption suffered by cluster heads, the Clustering Energy Efficient algorithm (CEEa) is also designed to manage the trade-off between the capacity enhancement and the early battery drain of some users. Results show that the proposed algorithms increase the network capacity and outperform existing solutions, while, at the same time, CEEa is able to handle the cluster heads energy overconsumption

Game-Theoretic based Power Allocation for a Full Duplex D2D Network

International audienceThis paper tackles the power allocation optimization problem of a Full duplex(FD) D2D underlaying cellular network. In particular, we aim at providing a distributed power allocation algorithm for this type of network. Towards this end, first, we formulate the PA problem as a non-cooperative game in which each user decides how much power to transmit over its allocated channel to maximize its link's energy-efficiency (EE). Next, we show that this game admits a unique Nash equilibrium (NE) point which can be obtained through an iterative process. After that, we show that this iterative algorithm can be implemented in a fully distributed manner. Finally, we compare our proposed distributed algorithm with the conventional centralized algorithms and simulation results show the importance of the proposed solution