In this paper, we investigate the outage performance of simultaneous wireless information and power transfer (SWIPT) based Decode-and-Forward (DF) relay networks, where the relay needs to simultaneously forward information for two relaying links, primary relaying link and parasitic relaying link. The primary relaying link is the traditional source-relay-destination relay system. While in the parasitic relaying link, the parasitic source, i.e., Internet-of-Things (IoT) tag, is not connected to the stable power source and thus has to backscatter the signals from the primary source to convey its information. The relay not only harvests energy from Radio Frequency (RF) signals from both sources but also forwards messages to their corresponding destinations. The primary source and destination are unaware of the parasitic backscatter transmission, but the relay and parasitic destination can employ successive interference cancellation (SIC) detector to eliminate the interference from the primary link and detect the message from the parasitic source. In order to investigate the interplay between the primary and parasitic relaying links, the outage probabilities of both relaying links are derived. Besides, the effects of system parameters, i.e., power splitting coefficient, forwarding power allocation coefficient and backscatter reflection coefficient, on the system performance are discussed. Simulation results verify our theoretical analysis. In the meanwhile, it is revealed that the advised relaying system has far larger sum throughput than the one with only primary relaying link and the parasitic relaying link can gain considerable throughput at the cost of negligible degradation of primary throughput.
<p>In this paper, we focus on intelligent reflecting surface (IRS) assisted multiuser simultaneous wireless information and power transfer (SWIPT) systems with hardware impairments (HWIs), which result from the aggregate effect of in-phase and quadrature-phase imbalance (IQI), power amplifier non-linearity, quantization distortion, phase noise, etc. Improper Gaussian signaling (IGS) is employed to combat the signal distortion incurred by HWIs and the interference from other users. We aim to maximize the minimum achievable information rate among all users by jointly optimizing the active beamforming vectors, passive reflecting coefficients, and power splitting coefficients, subject to the minimum harvested energy requirements of these users and the total power budget at the transmitter. Due to the intricate coupling between the reflecting coefficients and beamforming vectors, we propose a two-level iterative optimization algorithm to solve this non-convex problem. Based on the above, we also study the weighted rate-energy region maximization problem. Numerical results show that the use of IGS significantly outperforms traditional proper Gaussian signaling (PGS) in the considered systems and also affirm the effectiveness of the proposed optimization algorithm.</p>
Over-the-air computation is a promising technique for efficiently aggregating data in sensor networks. This method requires that signals from all nodes arrive at the sink aligned in signal magnitude, which faces the reliability issue, especially in times of channel fading. To solve this problem, in this paper, we propose an amplify-and-forward based relay, Coherent Relay with Node Scheduling (CohR-NS), where a relay node is used to help forward signals of multiple nodes. Relay transmission power (TP) increases with the number of nodes using the relay, which is a bottleneck. We investigate how relay TP changes with relay position, and under the constraint of relay TP, study (i) how to select nodes to use relay when not all nodes requiring a relay can be supported simultaneously, (ii) how to select more nodes to use relay so as to reduce node TP, when there is a surplus in relay TP. We formulate this as an ILP (integer linear programming) problem, propose an efficient heuristic method, and confirm its effectiveness by simulation evaluation.
<p>Intelligent reflecting surface (IRS) is considered as an enabling technology for millimeter wave (mmWave) communications since it can provide an extra reflection link to increase the macrodiversity gains and improve the transmission performance. These advantages principally rely on the assumption that the blocking of direct and reflection links is mutually independent. However, due to the nonnegligible sizes of blockages in some practical cases, both links may be simultaneously blocked by the same blockage, which is the so-called blockage correlation. To this end, in this work we investigate the impact of blockage correlation in the IRS-assisted mmWave communication systems. Firstly, we provide a new joint line-of-sight/non-line-of-sight (LOS/NLOS) probability model with blockage correlation. The correlation coefficient of direct and reflection link states is also derived. Secondly, we study the effects of blockage correlation on the system performance of IRS-assisted mmWave communication systems by deriving the expression of transmission success probability. Moreover, we provide a deployment optimization algorithm for IRS when blockage correlation is considered. Finally, simulations verify our theoretical results and validate the IRS deployment optimization algorithm. It is shown that the widelyused independent blocking assumption not only always incur an overestimation of the performance of IRS-assisted mmWave communication systems, but also misdirect the optimal deployment of IRS.</p>
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