In this paper, we investigate resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems employing a full-duplex (FD) base station (BS) for serving multiple half-duplex (HD) downlink (DL) and uplink (UL) users simultaneously. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted sum system throughput. We apply monotonic optimization to develop an optimal joint power and subcarrier allocation policy. The optimal resource allocation policy serves as a system performance benchmark due to its high computational complexity. Furthermore, a suboptimal iterative scheme based on successive convex approximation is proposed to strike a balance between computational complexity and optimality. Our simulation results reveal that the proposed suboptimal algorithm achieves a closeto-optimal performance. Besides, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared to conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. Also, our results unveil that the proposed FD MC-NOMA systems achieve a fairer resource allocation compared to traditional HD MC-OMA systems. ). Zhiguo Ding is with the School of Computing and Communications, Lancaster University, United Kingdom (email: z.ding@lancaster.ac.uk). This paper has been accepted in part for presentation at IEEE Globecom 2016 [1]. 2 I. INTRODUCTIONMulticarrier multiple access techniques have been widely adopted in broadband wireless communication systems over the last decade, due to their flexibility in resource allocation and their ability to exploit multiuser diversity [2]- [5]. In conventional multicarrier systems, a given radio frequency band is divided into multiple orthogonal subcarriers and each subcarrier is allocated to at most one user to avoid multiuser interference (MUI). The spectral efficiency of such systems can be improved significantly by performing joint user scheduling and power allocation. In [3], the authors studied the resource allocation algorithm design for energy-efficient communication in multi-cell orthogonal frequency division multiple access (OFDM) systems. In [4], an asymptotically optimal power control and subcarrier allocation algorithm was proposed to maximize the transmission rate in OFDM systems with multiple relays. The authors of [5] proposed a distributed subcarrier, power, and rate allocation algorithm for the maximization of the weighted sum throughput of relay-assisted OFDM systems. However, even with the schemes proposed in [3]-[5], the spectral resources are still underutilized as some subcarriers may be assigned exclusively to users with poor channel conditions to ensure fairness in resource allocation.Non-orthogonal multiple access (NOMA) has recently received significant attention since it enables the multiplexing of multiple users simultaneously utilizing the same frequency resource, which improves s...

In this paper, we investigate the resource allocation algorithm design for multicarrier solar-powered unmanned aerial vehicle (UAV) communication systems. In particular, the UAV is powered by solar energy enabling sustainable communication services to multiple ground users. We study the joint design of the three-dimensional (3D) aerial trajectory and the wireless resource allocation for maximization of the system sum throughput over a given time period. As a performance benchmark, we first consider an offline resource allocation design assuming non-causal knowledge of the channel gains. The algorithm design is formulated as a mixed-integer non-convex optimization problem taking into account the aerodynamic power consumption, solar energy harvesting, a finite energy storage capacity, and the quality-of-service (QoS) requirements of the users. Despite the non-convexity of the optimization problem, we solve it optimally by applying monotonic optimization to obtain the optimal 3D-trajectory and the optimal power and subcarrier allocation policy. Subsequently, we focus on online algorithm design which only requires real-time and statistical knowledge of the channel gains. The optimal online resource allocation algorithm is motivated by the offline scheme and entails a high computational complexity. Hence, we also propose a low-complexity iterative suboptimal online scheme based on successive convex approximation. Our simulation results reveal that both proposed online schemes closely approach the performance of the benchmark offline scheme and substantially outperform two baseline schemes. Furthermore, our results unveil the tradeoff between solar energy harvesting and power-efficient communication. In particular, the solar-powered UAV first climbs up to a high altitude to harvest a sufficient amount of solar energy and then descents again to a lower altitude to reduce the path loss of the communication links to the users it serves.

In this paper, we investigate the power efficient resource allocation algorithm design for secure multiuser wireless communication systems employing a full-duplex (FD) base station (BS) for serving multiple half-duplex (HD) downlink (DL) and uplink (UL) users simultaneously. We propose a multiobjective optimization framework to study two conflicting yet desirable design objectives, i.e., total DL transmit power minimization and total UL transmit power minimization. To this end, the weighed Tchebycheff method is adopted to formulate the resource allocation algorithm design as a multiobjective optimization problem (MOOP). The considered MOOP takes into account the quality-ofservice (QoS) requirements of all legitimate users for guaranteeing secure DL and UL transmission in the presence of potential eavesdroppers. Thereby, secure UL transmission is enabled by the FD BS and would not be possible with an HD BS. The imperfectness of the channel state information of the eavesdropping channels and the inter-user interference channels is incorporated for robust resource allocation algorithm design. Although the considered MOOP is non-convex, we solve it optimally by semidefinite programming (SDP) relaxation. Simulation results not only unveil the trade-off between the total DL transmit power and the total UL transmit power, but also confirm the robustness of the proposed algorithm against potential eavesdroppers. Index TermsFull-duplex radio, physical layer security, multi-objective optimization, non-convex optimization. are also with the University of British Columbia, Vancouver, Canada. This paper has been accepted in part for presentation at the IEEE Globecom 2015 [1]. 2 I. INTRODUCTION The exponential growth in high data rate communication has triggered a tremendous demand for radio resources such as bandwidth and energy. An important technique for reducing the energy and bandwidth consumption of wireless systems while satisfying quality-of-service (QoS) requirements is multiple-input multiple-output (MIMO), as it offers extra degrees of freedom for efficient resource allocation. However, the MIMO gain may be difficult to achieve in practice due to the high computational complexity of MIMO receivers. As an alternative, multiuser MIMO (MU-MIMO) has been proposed as an effective technique for realizing the MIMO performance gain. In particular, in MU-MIMO systems, a transmitter equipped with multiple antennas (e.g. a base station (BS)) serves multiple single-antenna users which shifts the computational complexity from the receivers to the transmitter [2]. Yet, the spectral resource is still underutilized even if MU-MIMO is employed as long as the BS operates in the traditional half-duplex (HD) mode, where uplink (UL) and downlink (DL) communication are separated orthogonally in either time or frequency which leads to a significant loss in spectral efficiency. Full-duplex (FD) wireless communication has recently received significant attention from both academia and industry due to its potential to double the spectral effi...

In this paper, we study resource allocation design for secure communication in intelligent reflecting surface (IRS)assisted multiuser multiple-input single-output (MISO) communication systems. To enhance physical layer security, artificial noise (AN) is transmitted from the base station (BS) to deliberately impair the channel of an eavesdropper. In particular, we jointly optimize the phase shift matrix at the IRS and the beamforming vectors and AN covariance matrix at the BS for maximization of the system sum secrecy rate. To handle the resulting nonconvex optimization problem, we develop an efficient suboptimal algorithm based on alternating optimization, successive convex approximation, semidefinite relaxation, and manifold optimization. Our simulation results reveal that the proposed scheme substantially improves the system sum secrecy rate compared to two baseline schemes.

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This paper investigates the application of non-orthogonal multiple access (NOMA) in millimeter wave (mmWave) communications by exploiting beamforming, user scheduling and power allocation. Random beamforming is invoked for reducing the feedback overhead of considered systems. A non-convex optimization problem for maximizing the sum rate is formulated, which is proved to be NP-hard. The branch and bound (BB) approach is invoked to obtain the ǫ-optimal power allocation policy, which is proved to converge to a global optimal solution. To elaborate further, a low complexity suboptimal approach is developed for striking a good computational complexity-optimality tradeoff, where matching theory and successive convex approximation (SCA) techniques are invoked for tackling the user scheduling and power allocation problems, respectively. Simulation results reveal that: i) the proposed low complexity solution achieves a near-optimal performance; and ii) the proposed mmWave NOMA systems is capable of outperforming conventional mmWave orthogonal multiple access (OMA) systems in terms of sum rate and the number of served users. Index Terms Millimeter wave (mmWave), non-orthogonal multiple access (NOMA), power allocation, user scheduling J. Cui and P. Fan are with the Institute

In this paper, we study the resource allocation algorithm design for multiple-input single-output (MISO) multicarrier non-orthogonal multiple access (MC-NOMA) systems, in which a full-duplex base station serves multiple half-duplex uplink and downlink users on the same subcarrier simultaneously. The resource allocation is optimized for maximization of the weighted system throughput while the information leakage is constrained and artificial noise is injected to guarantee secure communication in the presence of multiple potential eavesdroppers. To this end, we formulate a robust non-convex optimization problem taking into account the imperfect channel state information (CSI) of the eavesdropping channels and the quality-ofservice (QoS) requirements of the legitimate users. Despite the non-convexity of the optimization problem, we solve it optimally by applying monotonic optimization which yields the optimal beamforming, artificial noise design, subcarrier allocation, and power allocation policy. The optimal resource allocation policy serves as a performance benchmark since the corresponding monotonic optimization based algorithm entails a high computational complexity. Hence, we also develop a low-complexity suboptimal resource allocation algorithm which converges to a locally optimal solution. Our simulation results reveal that the performance of the suboptimal algorithm closely approaches that of the optimal algorithm. Besides, the proposed optimal MISO NOMA system can not only ensure downlink and uplink communication security simultaneously but also provides a significant system secrecy rate improvement compared to traditional MISO orthogonal multiple access (OMA) systems and two other baseline schemes. Index TermsNon-orthogonal multiple access (NOMA), multicarrier systems, full-duplex radio, physical layer security, imperfect channel state information, non-convex and combinatorial optimization.

In this paper, we investigate robust resource allocation algorithm design for multiuser downlink multiple-input single-output (MISO) unmanned aerial vehicle (UAV) communication systems, where we account for the various uncertainties that are unavoidable in such systems and, if left unattended, may severely degrade system performance.We jointly optimize the two-dimensional (2-D) trajectory and the transmit beamforming vector of the UAV for minimization of the total power consumption. The algorithm design is formulated as a non-convex optimization problem taking into account the imperfect knowledge of the angle of departure (AoD) caused by UAV jittering, user location uncertainty, wind speed uncertainty, and polygonal no-fly zones (NFZs). Despite the non-convexity of the optimization problem, we solve it optimally by employing monotonic optimization theory and semidefinite programming relaxation which yields the optimal 2-D trajectory and beamforming policy. Since the developed optimal resource allocation algorithm entails a high computational complexity, we also propose a suboptimal iterative low-complexity scheme based on successive convex approximation to strike a balance between optimality and computational complexity. Our simulation results reveal not only the significant power savings enabled by the proposed algorithms compared to two baseline schemes, but also confirm their robustness with respect to UAV jittering, wind speed uncertainty, and user location uncertainty. Moreover, our results unveil that the joint presence of wind speed uncertainty and NFZs has a considerable impact on the UAV trajectory. Nevertheless, by counteracting the wind speed uncertainty with the proposed robust design, we can simultaneously minimize the total UAV power consumption and ensure a secure trajectory that does not trespass any NFZ. ). This paper was presented in part at IEEE Globecom 2018 [1]. 2 be employed as aerial base stations to offer temporary communication links in a timely and cost-effective manner. Moreover, due to their high mobility and maneuverability, UAVs can adapt their trajectories based on the actual environment and terrain which improves system performance [3]. As a result, UAV-assisted communication systems have drawn significant attention from both academia and industry. For instance, the authors of [4] studied suboptimal UAV trajectory design for maximization of the energy-efficiency of UAV communication systems. The authors of [5] proposed a suboptimal joint trajectory, power allocation, and user scheduling algorithm for maximization of the minimum user throughput in multi-UAV systems.Secure UAV communications was investigated in [6] where the trajectory of a UAV and its transmit power were jointly optimized to maximize the system secrecy rate. The authors of [7] proposed solar-powered UAV communication systems and studied the jointly optimal resource allocation and UAV trajectory design for maximization of the system sum throughput. In fact, the throughput of UAV communication systems can be further i...