We consider an IoT sensing network with multiple users, multiple energy harvesting sensors, and a wireless edge node acting as a gateway between the users and sensors. The users request for updates about the value of physical processes, each of which is measured by one sensor. The edge node has a cache storage that stores the most recently received measurements from each sensor. Upon receiving a request, the edge node can either command the corresponding sensor to send a status update, or use the data in the cache. We aim to find the best action of the edge node to minimize the average long-term cost which trade-offs between the age of information and energy consumption. We propose a practical reinforcement learning approach that finds an optimal policy without knowing the exact battery levels of the sensors. Simulation results show that the proposed method significantly reduces the average cost compared to several baseline methods.
The broadcast nature of wireless communications makes the propagation medium vulnerable to security attacks such as eavesdropping and jamming from adversarial or unauthorized users. Applying physical layer secrecy approaches will enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers, without using any secret keys. However, physical layer security approaches are typically feasible only when the source-eavesdropper channel is weaker than the source-destination channel. Cooperative jamming can be used to overcome this challenge and increase the secrecy rate. In this paper, the security of two-phase relaying system with multiple intermediate nodes and in the presence of an eavesdropper is investigated. To enhance the system secrecy rate, a joint cooperative beamforming and jamming combined with relay and jammer selections is proposed. In phase I, the source node broadcasts a signal to relays while three intermediate nodes (which act as jammers) help the source node by transmitting random jamming signals to confuse the eavesdropper. Since the friendly (cooperative) jammers create interference for both the intended relays and the eavesdropper, optimal beamforming is applied such that no interference is caused at two preselected desired relays (that are going to receive the confidential massage in phase I).In phase II, two preselected relays transmit the source message with beamforming coefficients such that the received signal at the eavesdropper is completely nulled out. Our goal in this paper is to minimize the received SNR at the eavesdropper while increasing it at the destination as much as possible by applying different methods such as cooperative beamforming, cooperative jamming and relay selection. To avoid operational complexity, we consider the minimum number of intermediate nodes that are necessary without losing the performance. Numerical results demonstrate the advantage of our proposed scheme compared with the scheme with no cooperative jamming.
We consider the problem of channel estimation in hybrid transceiver architectures operating in millimeter wave (mmWave) band. Due to the dynamic features of the environment and the sensitivity of mmWave bands to blockage and deafness, it is important to estimate mmWave channels with a low complexity and high performance algorithm. In this regard, we exploit the sparse structure of the frequency-selective mmWave channels and formulate the channel estimation problem as a sparse signal reconstruction in frequency domain. In order to solve the estimation problem, we propose a multi-stage based low complexity algorithm. Simulation results show that the proposed algorithm significantly reduces the computational complexity while preserving the quality of the estimation.
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