Unmanned Aerial Vehicles (UAVs) are becoming increasingly attractive for the ambitious expectations for 5G and beyond networks due to their several benefits. Indeed, UAV-assisted communications introduce a new range of challenges and opportunities regarding the security of these networks. Thus, in this paper we explore the opportunities that UAVs can provide for physical layer security solutions. Particularly, we analize the secrecy performance of a ground wireless communication network assisted by two friendly UAV jammers in the presence of an eavesdropper. To tackle the secrecy performance of this system, we introduce a new area-based metric, the weighted secrecy coverage, that measures the improvement on the secrecy performance of a system over a certain physical area given by the introduction of friendly jamming. Herein, the optimal 3D positioning of the UAVs and the power allocation is addressed in order to maximize the WSC. For that purpose, we provide a Reinforcement Learning-based solution by modeling the positioning problem as a Multi-Armed Bandit problem over three positioning variables for the UAVs: angle, height and orbit radius. Our results show that there is a trade-off between expediency of the positioning of the UAVs to positions of better secrecy outcome and energy expenditure, and that the proposed algorithm efficiently converges into a stable state.
In this paper, we examine the performance of the decode-and-forward (DF) relaying protocols with finite blocklength (FB). We provide the overall outage probability of three distinct DF relaying protocols, where the channels are assumed to be quasi static Rayleigh fading. More importantly, we derive the closed form expressions of the outage probability in the three relaying scenarios. We illustrate protocols where the cooperative communications outperform the direct transmission (DT). In addition, we compare the operating efficiency of the cooperative schemes in the ultra-reliable (UR) region.
In this paper we investigate the effect of interference caused by in-band full-duplex radios in device-to-device communication (D2D). While using full-duplex radios in D2D, both users transmit, compared to half-duplex D2D in which one user transmits. This is going to cause more interference in underlay D2D communication since D2D link operates on the same radio resource blocks as cellular users. We consider uplink radio resource reuse of cellular users by D2D communication, and try to maximize the number of possible D2D links constrained to the interference on the cellular user. The number of D2D pairs that can be active in the full-duplex mode is smaller than in the half-duplex mode due to more interference from transmissions of both D2D nodes. We compare the total rate of half-duplex and full-duplex modes and evaluate the benefits of full-duplex radios.
To obtain the appropriate number of layers for spatial multiplexing transmission on a high speed train equipped with moving relay nodes (MRN) cooperating with each other, the rank indicator (RI) is required. The conventional methods for calculating the RI have high levels of computational complexity and to dynamically obtain the RI based on the channel conditions require multiple times the computational complexity of a fixed rank transmission. We derive a method to reduce the computational complexity such that the RI is fixed, but the antenna positioning vary dynamically based on the channel conditions. Our simulation results show that our proposed method can achieve nearly the same throughput as with dynamic rank transmission schemes on the backhaul link with reduced complexity.
In this paper, we propose a method to connect a group of wireless sensors to LTE/LTE-A system by using the cellular users as mobile relays, with the basic principle of maintaining the normal traffic between the cellular users and eNodeB during the sensor data collection. The cellular spectrum is re-used on sensor-to-mobile relay link without employing additional frequency resources. Multi- carrier CDMA methods are suspected to be utilized by sensor nodes, where data of each sensor is spread to the whole re-used cellular spectrum to create a low data rate transmission. In order to avoid additional complex receiver on cellular terminals, the simple amplify-and-forward relaying scheme is used at mobile relays. Since eNodeB can observe the cellular traffic components in the re-used spectrum exactly, it has the capability of canceling them in the received overlapped signals, and detecting the sensor data by using advanced multi-user detection methods. Finally, the end-to-end outage probability is analyzed and a closed-form approximation is derived. The numerical results show that the approximate closed-form equation is significant and that the proposed scheme can be used to collect sensor data in LTE/LTE-A networks.
This paper considers a time division duplexing based coordinated multi-cell multiuser MIMO system. Optimization problem is sum power minimization among base stations (BSs) with minimum SINR constraint per each user. The problem is jointly non-convex with respect to transmit and receive beamformers. We propose a MIMO beamforming design where transmit and receive beamformers are updated consecutively using decentralized coordination. For receive beamforming, each user employs minimum mean squared error receiver which is then used as a precoder for uplink pilot signaling. Due to precoded pilot signaling, local effective channel state information is available at each BS. Using a primal decomposition method, originally centralized transmit beamforming optimization is decoupled between BSs and turned into a decentralized two-level optimization. At each BS, a lower BS-level optimization is cast as a second order cone program and solved using standard convex optimization tools, whereas a higher network-level optimization is solved via a projected subgradient method requiring limited backhaul information exchange among BSs. Alternating between receive and transmit beamforming optimization steps, algorithm converges to a locally optimal solution in a static channel scenario. Numerical results show similar performance as in the centralized case. Furthermore, significant performance gain over multi-cell MISO beamforming is demonstrated.
