Journal of Communications and Information Networks
Print ISSN 2096-1081 CN 10-1375/TN
Editor-in-Chief: Wei Zhang
The performance of a device-to-device (D2D) underlay communication system is limited by the co-channel interference between cellular users (CUs) and D2D devices. To address this challenge, a reconfigurable intelligent surface (RIS) aided D2D underlay system is studied in this paper. A two-timescale optimization scheme is proposed to reduce the required channel training and feedback overhead, where transmit beamforming at the base station(BS)and power control at the D2D transmitters are adapted to instantaneous effective channel state information (CSI); and the RIS phase shifts are adapted to slow-varying channel mean. Based on the two-timescale optimization scheme, we aim to maximize the D2D ergodic weighted sum-rate (WSR)subject to a given outage probability constrained signal-to-interference-plus-noise ratio (SINR) target for each CU. The two-timescale problem is decoupled into two sub-problems, and the two sub-problems are solved iteratively. Numerical results verified that the two-timescale based optimization performs better than two baselines, and also demonstrated a favourable trade-off between system performance and CSI overhead.
In cognitive radio networks, the jamming attacks, which have the same ability with secondary users (SUs) but access the licensed channels without considering the carrier sense multiple access protocol, can disguise a primary user(PU)or SU to occupy the licensed channels, thus resulting in failing to access the licensed channels for PUs and SUs. Employing full/half duplex cognitive frequency hopping (CFH), where users sense the occupancy of licensed channels and then dynamically adjust the hopping parameters, can mitigate the hostile jamming. However, due to the explosive growth of serves and data traffic, it is very difficult to significantly increase the anti-jamming results and achieve high capacities with full/half duplex CFH for both PUs and SUs in cognitive radio networks. To achieve efficient anti-jamming and high capacities for PUs and SUs, in this paper we propose the orbital angular momentum (OAM)-based hybridduplex CFH scheme, which jointly uses the half-duplex cooperative sensing and full-duplex transmission modes for PUs and SUs in cognitive radio networks. Using the OAM-based hybrid-duplex CFH scheme, PUs and SUs can identify the occupancy of licensed channels with halfduplex fashion, thus significantly reducing the probability of signals jammed. Then, based on the sensing results, the signals are allowed to be transmitted and received by the same time-slots, carrier frequencies, and OAM-modes. The average capacities of PUs and SUs are derived, respectively. Extensively numerical results show that our proposed OAM-based hybrid-duplex CFH scheme can significantly increase the capacities of PUs and SUs in cognitive radio networks under hostile jamming attacks.
In this paper, an unmanned aerial vehicle (UAV)-aided wireless emergence communication system is studied, where a UAV is deployed to support ground user equipments (UEs) for emergence communications. We aim to maximize the number of the UEs served, the fairness, and the overall uplink data rate via optimizing the trajectory of UAV and the transmission power of UEs. We propose a deep Q-network (DQN) based algorithm, which involves the well-known deep neural network (DNN)and Q-learning, to solve the UAV trajectory problem. Then, based on the optimized UAV trajectory, we further propose a successive convex approximation(SCA) based algorithm to tackle the power control problem for each UE. Numerical simulations demonstrate that the proposed DQN based algorithm can achieve considerable performance gain over the existing benchmark algorithms in terms of fairness, the number of UEs served and overall uplink data rate via optimizing UAV’s trajectory and power optimization.
Intelligent reflecting surface (IRS) is a promising technology for its capability of reflecting the incident signal towards the desired user. IRS can improve the efficiency of wireless communication systems. This paper introduces IRS into a device-to-device (D2D) communications system to improve the throughput of the D2D network. We adopt the block coordinate descent algorithm and semidefinite relaxation technique to optimize the beamforming vector, power allocation and phase shift matrix. Simulation results demonstrate that IRS is able to enhance the throughput of the D2D communications system, and the proposed algorithm significantly outperforms the other benchmark algorithms.
Due to space limitation, mutual coupling occurs almost invisibly in array antennas. In this paper, the mutual coupling effects on the two most popular categories of array antennas, i. e. , phased arrays and multiple-input multiple-output (MIMO) antennas, are reviewed. Some misconceptions regarding the mutual coupling effects are uncovered. It is shown that the steering pattern of a phased array at an arbitrary scanning angle can be readily calculated once the embedded radiation patterns of the array elements (including the mutual coupling effect)are obtained. As antenna spacing decreases, absorption loss increases, yet the phase terms tend to add up constructively as antenna spacing reduces, which may overcompensate the absorption loss due to mutual coupling. Thus, the array efficiency may be increased by reducing the antenna spacing. A patch antenna array is used to illustrate this phenomenon. It is further shown that while mutual coupling tends to reduce the correlation of two-element arrays, it has a negligible effect on the overall correlations of larger arrays. Finally, various mutual coupling reduction techniques are briefly presented. Two feasible techniques for large planar arrays are used to illustrate the benefits of array decoupling.
This paper studies a dynamic multi-user wireless network, where users have no knowledge of the arrival rate and size of data block and suffer from a constraint on long-term average power consumption. Considering such a network, we address the problem of dynamically optimizing channel/power allocation, so as to minimize the long-term average data backlog. The design problem is shown to be a constrained Markov decision process. In order to solve the problem without knowledge on dynamics of the system, we introduce post-decision states and propose a resource allocation algorithm based on reinforcement learning. Since the channel/power allocation problem is coupled, the multiuser decision problem suffers from curses of dimensions(of state/action/outcome space). This makes centralized decision-making and optimization on channel/power allocation suffer from a long convergence time. As a countermeasure, a partially distributed resource allocation framework is proposed. The multiuser power allocation problem is decoupled into single-user decision problems, while channel allocation optimization is performed in a centralized manner. In order to further reduce computational complexity, we propose a low-complexity reinforcement learning method. Simulation results reveal that the proposed algorithm outperforms the state-of-the-art myopic optimizations in terms of energy efficiency and the backlog performance.
It is commonly believed that orbital angular momentum (OAM) multiplexing is only suitable for short-range communications in line-of-sight (LoS) scenario and multipath propagation would be detrimental for OAM communications. It has been demonstrated very recently that OAM multiplexing could work in rich isotropic multipath environment when the conventional spatial equalization is used for data detection. Moreover, the resulting channel capacity is comparable to that of a conventional multiple-input multiple-output system. Nevertheless, the rich isotropic multipath environment is an ideal multipath scenario. In this paper, we investigate the performance of OAM multiplexing in arbitrary multipath environment. Contrary to the common belief, it is shown that multipath can be beneficial for OAM multiplexing in terms of channel capacity. Particularly, the OAM capacity increases with enlarged angular spread of the channel and reaches its maximum when the angular spread is comparable to the divergence angle of the OAM beam. Based on the study, the OAM multiplexing is further investigated for base station(BS)applications. It is shown that OAM based BS antennas are comparable to(or even outperform) the conventional BS antennas in terms of channel capacity.
A low-profile cylindrical dielectric resonator antenna (CDRA) with enhanced impedance bandwidth is proposed via sharing a single triple-mode dielectric resonator. Initially, the resonant frequencies of TM01δ and TM02δ modes of a conventional CDRA are maintained far away from each other under central probe feed. Next, a circular disk with an annular ring is loaded around the conventional CDRA, aiming to excite an additional mode between these dual modes. The electric fields demonstrate that the previous TM02δ mode is transformed into the TM03δ mode for the modified CDRA, and an additional TM02δ mode is successfully excited between the TM01δ and TM03δ modes. As a result, the resonant frequencies of these three radiative modes are reallocated in proximity to each other, thus achieving the desired bandwidth enhancement. In addition, considering the small input impedance of the CDRA, a microstrip feeding line is introduced underneath the central probe for good impedance matching. With these arrangements, the resultant antenna can generate an extended bandwidth under simultaneous radiation of TM01δ, TM02δ, and TM03δ modes. Finally, the proposed CDRA is designed, fabricated, and measured to validate the predicted performance. The simulated and measured results show that the impedance bandwidth (|S11|＆lt; ?10 dB of the antenna is dramatically extended from 8% to about 62% (2. 83～5. 36 GHz), while keeping a stable conical radiation pattern. In particular, a low profile property of about 0.15 free space wavelength is achieved as well.
Massive machine type communication (mMTC) is anticipated to be an essential part of fifth generation (5G) networks. The main challenge for mMTC devices (mMTCDs) is the design of an access authentication scheme that can fulfill the security and privacy requirements of 5G applications, which have specific conditions, including rigorous latency and simultaneous access. Thus, a novel 5G authentication and key agreement (5G-AKA) protocol was introduced by the 3rd generation partnership project (3GPP) to achieve mMTCD access authentication. However, 5GAKA protocol comes with some security vulnerabilities and significant delay for real-time mMTC applications, particularly when mMTCDs concurrently roam into new networks. In order to address the real-time secure and efficient access issues of multiple mMTCDs, this paper proposes a lightweight and efficient group authentication protocol for mMTC in 5G wireless networks. The proposed protocol, which integrates bilinear maps and an aggregate certificateless signature mechanism, can achieve several security goals, including avoidance of signaling congestion in the authentication process, mutual authentication, session key agreement, perfect forward/backward secrecy, and masked attack and key escrow resistance. Compared to existing conventional protocols, the proposed protocol demonstrates robust security and improved performance in terms of signaling cost authentication, bandwidth consumption and computational cost.
