Multi-Objective Optimization for Energy- and Spectral-Efficiency Tradeoff in In-Band Full-Duplex (IBFD) Communication (original) (raw)
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IEEE Transactions on Vehicular Technology
In this paper, we develop an energy efficient resource allocation scheme for orthogonal frequency division multiple access (OFDMA) networks with in-band full-duplex (IBFD) communication between the base station and user equipments (UEs) considering a realistic self-interference (SI) model. Our primary aim is to maximize the system energy efficiency (EE) through a joint power control and sub-carrier assignment in both the downlink (DL) and uplink (UL), where the quality of service requirements of the UEs in DL and UL are guaranteed. The formulated problem is non-convex due to the non-linear fractional objective function and the non-convex feasible set which is generally intractable. In order to handle this difficulty, we first use fractional programming to transform the fractional objective function to the subtractive form. Then, by employing Dinkelbach method, we propose an iterative algorithm in which an inner problem is solved in each iteration. Applying majorization-minimization approximation, we make the inner problem convex. Also, by introducing a penalty function to handle integer sub-carrier assignment variables, we propose an iterative algorithm for addressing the inner problem. We show that our proposed algorithm converges to the locally optimal solution which is also demonstrated by our simulation results. In addition, simulation results show that by applying the IBFD capability in OFDMA networks with efficient SI cancellation techniques, our proposed resource allocation algorithm attains a 75% increase in the EE as compared to the half-duplex system.
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 for serving multiple half-duplex (HD) downlink and uplink 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 close-to-optimal performance. In addition, FD MC-NOMA systems employing the proposed resource allocation algorithms provide a substantial system throughput improvement compared with conventional HD multicarrier orthogonal multiple access (MC-OMA) systems and other baseline schemes. In addition, our results unveil that FD MC-NOMA systems enable a fairer resource allocation compared with traditional HD MC-OMA systems.
IEEE Transactions on Communications, 2015
This paper investigates the joint transmitter and receiver optimization for the energy efficiency (EE) in orthogonal frequency-division multiple-access (OFDMA) systems. We first establish a holistic power dissipation model for OFDMA systems, including the transmission power, signal processing power, and circuit power from both the transmitter and receiver sides, while existing works only consider the one side power consumption and also fail to capture the impact of subcarriers and users on the system EE. The EE maximization problem is formulated as a combinatorial fractional problem that is NP-hard. To make it tractable, we transform the problem of fractional form into a subtractive-form one by using the Dinkelbach transformation and then propose a joint optimization method, which leads to the asymptotically optimal solution. To reduce the computational complexity, we decompose the joint optimization into two consecutive steps, where the key idea lies in exploring the inherent fractional structure of the introduced individual EE and the system EE. In addition, we provide a sufficient condition under which our proposed two-step method is optimal. Numerical results demonstrate the effectiveness of proposed methods, and the effect of imperfect channel state information is also characterized.
Resource Optimization in Full Duplex Non-Orthogonal Multiple Access Systems
IEEE Transactions on Wireless Communications, 2019
In this paper, we investigate a full duplex (FD) multiuser non-orthogonal multiple access (NoMA) communication system, based on the optimization of received signalto-interference-plus-noise ratio (SINR) per unit power. Since the communication system operates in FD mode, co-channel interference (CCI) and self-interference (SI) dominate the system's performance. Accordingly, to combat the CCI, we adopt a gametheoretic approach and propose users clustering algorithms and to suppress the SI, we formulate an optimization problem to maximize the power-normalized SINR (PN-SINR). While the user clustering optimization problem is constrained by i) the successive interference cancellation (SIC) constraint and ii) two binary constraints for the allocations of UL and DL users, the PN-SINR problem is constrained by i) total transmit power budget at the base station and uplink (UL) users, ii) the fundamental condition for the implementation of successive interference cancellation in NoMA, and iii) the minimum fairness condition for UL users. The original PN-SINR problem is non-convex and hence is converted into an equivalent subtractive-form problem, after which we propose an iterative algorithm to find the optimal power allocation policy. Properties of all the proposed algorithms are thoroughly investigated and numerical results are provided. Based on the channel conditions and suppression level of SI and CCI, the superiority of the proposed FD-NoMA system over half duplex NoMA and FD orthogonal multiple access systems is verified.
International Journal of Communication Systems, 2015
Energy efficiency (EE) has currently turn into one of the major issues in heterogeneous networks (HetNet) paradigm of today's wireless communication industry. In this paper, we optimize EE for downlink OFDMA system in HetNet, taking into account realistic network power consumption model, that is, considering circuit power. This paper investigates the EE maximization using convex optimization theory where primary optimization criterion is data rate in a downlink multiuser HetNet. Given QoS (data rate) requirement, for maximizing EE, a constrained based optimization problem is devised. Because the optimization problem is non-convex in nature, we reconstruct the optimization problem as a convex one and devise a pragmatically efficient novel resource assignment algorithm for maximizing achievable EE, with quick convergence. The considered optimization problem is transformed into a convex optimization problem by redefining the constraint using cubic inequality, which results in an efficient iterative resource allocation algorithm. In each iteration, the transformed problem is solved by using dual decomposition with a projected gradient method. Analytical insights and numerical results exhibit the potency of the devised scheme for the targeted complex wireless systems.
Transactions on Emerging Telecommunications Technologies, 2018
In-band full-duplex (FD) radio is regarded as a promising solution to enhance the spectral efficiency in the next-generation wireless networks. In this paper, the problem of joint user association, subchannel assignment, and power allocation in FD orthogonal frequency-division multiple access heterogeneous networks is considered. The weighted downlink and uplink sum rate of the network is maximized in a way that the transmit power of base stations and users remains below a given level. The problem is formulated as a nonconvex mixed-integer nonlinear programming optimization problem. Then, it is converted into a suboptimal problem, which can be solved iteratively using difference of convex programming algorithm. Numerical results show that the proposed iterative algorithm converges quickly in few numbers of iterations with different initialization points. The results also show that the sum rate of an FD heterogeneous network can be as much as 66 % higher than the sum rate of a half-duplex network.
Energy Efficiency Maximization in the Uplink Delta-OMA Networks
IEEE Transactions on Vehicular Technology, 2021
Delta-orthogonal multiple access (D-OMA) has been recently investigated as a potential technique to enhance the spectral efficiency in the sixth-generation (6G) networks. D-OMA enables partial overlapping of the adjacent sub-channels that are assigned to different clusters of users served by nonorthogonal multiple access (NOMA), at the expense of additional interference. In this paper, we analyze the performance of D-OMA in the uplink and develop a multi-objective optimization framework to maximize the uplink energy efficiency (EE) in a multi-access point (AP) network enabled by D-OMA. Specifically, we optimize the sub-channel and transmit power allocations of the users as well as the overlapping percentage of the spectrum between the adjacent sub-channels. The formulated problem is a mixed binary non-linear programming problem. Therefore, to address the challenge we first transform the problem into a single-objective problem using Tchebycheff method. Then, we apply the monotonic optimization (MO) to explore the hidden monotonicity of the objective function and constraints, and reformulate the problem into a standard MO in canonical form. The reformulated problem is then solved by applying the outer polyblock approximation method. Our numerical results show that D-OMA outperforms the conventional non-orthogonal multiple access (NOMA) and orthogonal frequency
A heuristic for maximising energy efficiency in OFDMA systems with QoS constraints
2018
OFDMA is a popular coding scheme for mobile wireless multichannel multiuser communication systems. In a previous paper, we used mixed-integer nonlinear programming to tackle the problem of maximising energy efficiency, subject to certain quality of service (QoS) constraints. In this paper, we present a heuristic for the same problem. Computational results show that the heuristic is at least two orders of magnitude faster than the exact algorithm, yet yields solutions of comparable quality.
A Heuristic for Maximising Energy Efficiency in an OFDMA System Subject to QoS Constraints
2018
OFDMA is a popular coding scheme for mobile wireless multi-channel multi-user communication systems. In a previous paper, we used mixed-integer nonlinear programming to tackle the problem of maximising energy efficiency, subject to certain quality of service (QoS) constraints. In this paper, we present a heuristic for the same problem. Computational results show that the heuristic is at least two orders of magnitude faster than the exact algorithm, yet yields solutions of comparable quality.
Energy Efficient Resource Allocation in Two-Tier OFDMA Networks with QoS Guarantees
Wireless Networks, 2017
In this paper, we study joint power and subchannel allocation problem for OFDMA based femtocell networks with focus on uplink direction. We minimize the aggregate power of all Femto user equipments and maximize the total system energy efficiency while satisfying the minimum required rate of all users. An interference limit constraint is considered to protect the QoS of macrocells. The original problem is a mixed-integer non-convex optimization problem which is converted to a convex problem using the time-sharing concept. Three algorithms are proposed to provide a scheme to optimize the goal function while meeting the constraints. The complexity order of all algorithms was investigated and was compared to other alternative solutions. The analytic and simulation results have demonstrated that the proposed algorithms could achieve significant power saving and better energy efficiency compared to existing algorithms.