Power Minimization of UAV-Assisted Full-Duplex Mobile Relaying via Hybrid Trajectory Design

This paper solved a propulsion power minimization problem subject to a total data-bits constraint of an unmanned aerial vehicle (UAV) enabled full-duplex mobile relaying system, where a full-duplex UAV relay is dispatched as a mobile relay to assist data transfer from a source to a destination by using three trajectory flying modes, namely, the UAV first flies in a circle above the source, next flies to the destination in a straight line, and finally flies in a circle above the destination until all the data bits has been transferred. Since the propulsion power minimization problem is a non-convex mixed integer programming problem and its closed-form solution is hard to obtain, it is transformed to three sub-problems so as to simplify its solution. After solving the three sub-problems, an iterative algorithm is proposed to achieve a sub-optimal solution to the propulsion power minimization problem, leading to a new hybrid circular/straight trajectory (HCST) design. Computer simulations are conducted and the results validated the proposed HCST design. It is shown that compared to the straight or circular flight trajectory design, the HCST performs well in terms of energy saving for the long distance and big data communication cases.

Power Minimization Using Rate Splitting With Statistical CSI in Cloud-Radio Access Networks

Minimizing the power consumption in mobile communication networks while ensuring a minimum quality of service (QoS) for applications is essential in light of the unprecedented expected increase in the number of connected devices and the associated data traffic beyond the fifth generation of wireless networks (B5G). This paper considers a cloud-radio access network (C-RAN) model where a central processor (CP) is connected to the base stations (BSs) via limited capacity fronthaul links. In the context of our C-RAN setting, we consider the practical case where the CP has only statistical knowledge of channel state information (CSI). While conventional wireless systems adopt the treating interference as noise (TIN) strategy to deal with the interference in the network, this paper instead considers that the CP applies the rate splitting (RS) strategy by dividing each user’s message into two parts: a private part to be decoded by the intended user only and a common part to be decoded by a subset of users, for the sole reason of interference mitigation in the network. To best account for the channel estimation errors, this paper addresses the problem of transmit power minimization under minimum QoS constraints on the achievable ergodic rate per user, so as to determine the beamforming vectors of the private and common messages as well as the rate allocated to all the users. The considered problem is of stochastic, complex, and non-convex nature. This paper addresses the problem intricacies through an iterative approach that leverages both the sample average approximation (SAA) technique and the weighted minimum mean squared error (WMMSE) algorithm to obtain a stationary point of the optimization problem in the asymptotic regime. The numerical results demonstrate the gain achieved with the RS strategy as compared to TIN, especially under high QoS requirements.