Joint user association, subchannel assignment, and power allocation in full‐duplex OFDMA heterogeneous networks (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.
Transactions on Emerging Telecommunications Technologies, 2017
In this paper, we propose a heterogeneous cellular network based on orthogonal frequency division multiple access consisting of full-duplex femtorelays. Then, we design schemes for the uplink radio resource allocation. The goal of the proposed schemes is to maximize the sum rate, taking into account the back-haul and transmission power constraints. Moreover, the superiority of the proposed system is shown by comparing it with the half-duplex femtorelay-assisted counterpart. Since the proposed resource allocation optimization problem is nonconvex and intractable, we divide it into subcarrier and transmission power allocation subproblems and then use an iterative algorithm to solve each of them. Toward this end, in each iteration, subcarriers are allocated via a binary linear program, while the successive convex approximation method is adapted to transform the nonconvex transmission power allocation subproblem into a sequence of convex subproblems. To achieve this goal, we use 1 of the 3 proposed approaches, namely, dual, arithmetic-geometric mean approximation, and difference of 2 concave functions. In addition, we investigate the performance, convergence, and computational complexity of these approaches. The simulation results reveal that the proposed approaches are close to the optimal solution while providing less computational complexity. Moreover, they illustrate that even by considering self-interference in the full-duplex mode, the sum rate will be increased approximately by 41% in comparison with the half-duplex mode.
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.
On the uplink spectral efficiency of full-duplex cooperative OFDMA systems
2016 8th International Symposium on Telecommunications (IST), 2016
In this paper, we develop a resource allocation algorithm for uplink of in-band full-duplex (FD) cellular networks. The FD cellular network is assumed to be based on orthogonal frequency division multiple access (OFDMA) and consists of a base station communicating with multiple users. Some of the users in the network act as relay for other users and help them to transmit their data to the base station. These relays are FD and work based on amplify and forward (AF) protocol. By appropriate selection of the relays and optimized allocation of subcarriers and powers to all users, we try to maximize the total sum rate of the network. During this optimization, we also impose some constraints on the users' quality of service (QoS) and power. We propose a new algorithm to select the best relays based on the users' maximum data rate and also use Linear Assignment Problem Jonker-Volgenant (LAPJV) algorithm for subcarrier assignment. It is proved that the resulting optimization problem can be converted to a convex problem, and hence it can be solved by standard numerical methods. The simulation results demonstrate the effect of the proposed scheme on the sum rate and coverage of the network.
Sum rate maximization in the uplink of multi-cell OFDMA networks
2011 7th International Wireless Communications and Mobile Computing Conference, 2011
Resource allocation in orthogonal frequency division multiple access (OFDMA) networks plays an imperative role to guarantee the system performance. However, most of the known resource allocation schemes are focused on maximizing the local throughput of each cell, while ignoring the significant effect of inter-cell interference. This paper investigates the problem of resource allocation (i.e., subcarriers and powers) in the uplink of a multi-cell OFDMA network. The problem has a non-convex combinatorial structure and is known to be NP hard. Firstly, we investigate the upper and lower bounds to the average network throughput due to the inherent complexity of implementing the optimal solution. Later, a centralized sub-optimal resource allocation scheme is developed. We further develop less complex centralized and distributed schemes that are well-suited for practical scenarios. The computational complexity of all schemes has been analyzed and the performance is compared through numerical simulations. Simulation results demonstrate that the distributed scheme achieves comparable performance to the centralized resource allocation scheme in various scenarios.
Sum-Rate Optimization Problem for Multiuser OFDM Systems
Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications, 2015
A multiuser Orthogonal Frequency Division Multiplexing (OFDM) system with perfect channel knowledge and limited power at base station is studied to maximize the average system throughput. Data rate and bit error rate (BER) can be adaptively changed with the channel variation. An efficient and low complexity algorithm for subcarrier and power allocation in OFDM systems is proposed in this paper. We consider an OFDM downlink system where each subcarrier is used by only one user. Since our resource allocation problem is non-convex, it is not easy to find an optimal solution. Our approach is to consider a user iterative water filling algorithm (IWF), which is concave, and find a numerical method to approximate the optimal solution for our non convex problem. Our results show that each subcarrier is allocated to a user by taking into account channel gains and interference caused by other users.
Resource allocation via sum-rate maximization in the uplink of multi-cell OFDMA networks
Wireless Communications and Mobile Computing, 2011
In this paper, we consider maximizing the sum-rate in the uplink of a multi-cell OFDMA network. The problem has a non-convex combinatorial structure and is known to be NP hard. Due to the inherent complexity of implementing the optimal solution, firstly, we derive an upper and lower bound to the optimal average network throughput. Moreover, we investigate the performance of a near optimal single cell resource allocation scheme in the presence of ICI which leads to another easily computable lower bound. We then develop a centralized sub-optimal scheme that is composed of a geometric programming based power control phase in conjunction with an iterative subcarrier allocation phase. Although, the scheme is computationally complex, it provides an effective benchmark for low complexity schemes even without the power control phase. Finally, we propose less complex centralized and distributed schemes that are well-suited for practical scenarios. The computational complexity of all schemes is analyzed and performance is compared through simulations. Simulation results demonstrate that the proposed low complexity schemes can achieve comparable performance to the centralized sub-optimal
Radio resource allocation for full-duplex multicarrier wireless systems
2015 International Symposium on Wireless Communication Systems (ISWCS), 2015
Full-duplex technology has the potential to double the wireless system spectral efficiency by enabling simultaneous transmission and reception at the same time on the same frequency. In this paper, we address the subcarrier and power allocation problem for full-duplex system. The problem is coupled between uplink and downlink channels due to the self-interference and inter-user interference. As the problem is non-convex, a suboptimal algorithm is proposed based on the Frank-Wolfe approach. To this end, a subcarrier and power allocation is first performed for the downlink channel, and then the uplink resource allocation is represented as a D.C. (difference of two convex functions) problem. An approximation is used to convert the D.C. problem into two convex sub-problems, which are solved iteratively to produce a lower bound approximation for the non-convex objective. Simulation results show that the algorithm achieves fast convergence regardless of different initialization points, and can significantly improve the full-duplex performance comparing to the equal resource allocation approach. Furthermore, the fullduplex system with the proposed algorithm can achieve significant gains in spectral efficiency, that reach up to 48%, comparing to half-duplex system.
2012 IEEE 75th Vehicular Technology Conference (VTC Spring), 2012
Heterogeneous cellular networks (HetNets), where lowpower base-stations are overlaid with conventional macro base-stations, is a promising technique to improve coverage and capacity of the macroonly networks. To realize the potential benefits of HetNets, it is crucial to jointly optimize the user association, channel assignment, beamforming and power control to ensure that the inter-and intra-cell interference will not overwhelm the cell-splitting gains. This paper presents an iterative algorithm to solve the joint optimization problem with an objective of maximizing the network sum rate and simultaneously guaranteeing the individual user quality-of-service. The proposed algorithm is built on the so-called convex-concave procedure, and the feasibility issue is handled by l 1 -norm heuristic. Numerical results demonstrate the large gains over currently used methods for cellular networks.
2019 IEEE Global Communications Conference (GLOBECOM), 2019
The problem of joint power and sub-channel allocation to maximize energy efficiency (EE) and spectral efficiency (SE) simultaneously in in-band full-duplex (IBFD) orthogonal frequency-division multiple access (OFDMA) network is addressed considering users' QoS in both uplink and downlink. The resulting optimization problem is a non-convex mixed integer non-linear program (MINLP) which is generally difficult to solve. In order to strike a balance between the EE and SE, we restate this problem as a multi-objective optimization problem (MOOP) which aims at maximizing system's throughput and minimizing system's power consumption, simultaneously. To this end, the ǫconstraint method is adopted to transform the MOOP into single objective optimization problem (SOOP). The underlying problem is solved via an efficient solution based on the majorization minimization (MM) approach. Furthermore, in order to handle binary subchannel allocation variable constraints, a penalty function is introduced. Simulation results unveil interesting tradeoffs between EE and SE. Index Terms-Full-duplex (FD) communication, energyefficiency (EE), spectral-efficiency (SE), mixed integer nonlinear program (MINLP), multi-objective optimization problem (MOOP), ǫ-method, majorization minimization (MM).