In this paper, we consider a multiuser single-cell transmission facilitated by a full duplex (FD) base station (BS). We formulate two multi-objective optimization problems (MOOPs) via the weighted Tchebycheff method to jointly minimize the two desirable system design objectives namely the total downlink and uplink transmit power. In the first MOOP, multiuser interference is suppressed while in the second MOOP, multiuser interference is rather exploited. In order to solve the non-convex MOOPs, we propose a two-step iterative algorithm to optimize jointly the receive beamformer, transmit beamformer and uplink transmit power, respectively. Simulation results show the proposed scheme achieves a scalable performance-complexity trade-off that allows performance improvements compared to existing solutions.

In this paper, we consider a multi-user full duplex (FD) mobile edge computing (MEC) system, where a FD base station (BS) integrated with a MEC server, simultaneously transmits information signals to downlink users through the downlink and receive computation tasks for execution by the MEC server from mobile devices in the uplink. We study the trade-off between the offloading energy and latency by minimize the total offloading energy and latency via a weighted multi-objective optimization problem. First, we propose a design strategy based on the traditional interference suppression in the downlink, and then, we proposed a second design based on downlink interference exploitation. We employ Lagrangian methods to solve the two non-convex designs via an iterative algorithm. Simulation results not only show the trade-off between the offloading energy and latency, but also show the substantial gains achieved by the proposed FD schemes compared with the baseline half duplex schemes.

In this paper, we investigate the offloading energy and latency trade-off in a multiuser full-duplex (FD) system. We consider a multi-user FD system where a FD base station (BS), equipped with a mobile-edge computing (MEC) server, carries out data transmission in the downlink while at the same time receiving computational tasks from mobile devices in the uplink. Our main aim is to study the trade-off between the offloading energy and latency, which are known to be very important and desirable system objectives for both the system operator and users. In practice, there always exists a trade-off between these two objectives. Toward this aim, we formulate two weighted multi-objective optimization problems (MOOPs), one where the multi-user interference (MUI) is suppressed and the other where MUI is rather exploited. As a result, our proposed MOOPs allow for a scalable trade-off between the two objectives. To tackle the non-convexity of the formulations, we design an iterative algorithm through Lagrangian method. We also address the scenario of imperfect channel state information (CSI) at the FD BS. For the imperfect CSI case, we apply convex relaxations and transformation using the S-procedure to tackle the non-convexity of the formulations. Simulation results show the effectiveness of the proposed FD schemes compared with the existing baseline half duplex schemes and the superiority of MUI exploitation over suppression.

This paper considers a multiuser full-duplex (FD) wireless communication system, where an FD radio base station (BS) serves multiple single-antenna half-duplex uplink and downlink users simultaneously. Unlike conventional interference mitigation approaches, we propose using knowledge of the data symbols and the channel state information (CSI) at the FD radio BS to exploit the multi-user interference constructively rather than to suppress it. We propose a multi-objective optimization problem (MOOP) via the weighted Tchebycheff method to study the tradeoff between the two desirable system design objectives, namely the total downlink transmit power and the total uplink transmit power, at the same time ensuring the required quality-of-service (QoS) for all users. In the proposed MOOP, we adapt the QoS constraints for the downlink users to accommodate constructive interference for both generic phase shift keying modulated signals and for quadrature amplitude modulated signals. We also extended our work to a robust design to study the system with imperfect uplink and downlink CSI. The simulation results and analysis show that significant power savings can be obtained. More importantly, however, the MOOP approach here allows for the power saved to be traded off for both uplink and downlink power savings, leading to an overall energy efficiency improvement in the wireless link.

In this paper, we consider the power minimization problem in a multi-user full-duplex communication system by employing a multi-objective optimization problem via the weighted Tchebycheff method. We propose to exploit the multi-user interference by using the knowledge of the data symbols and channel state information at the full-duplex base station. Simulation results show that significant power savings can be obtained, which leads to substantial reduction of the self- interference power in the full-duplex systems.