Downlink beamforming and resource allocation in multicell MISO-OFDMA systems (original) (raw)
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Resource Allocation for Maximizing Weighted Sum Min-Rate in Downlink Cellular OFDMA Systems
2010 IEEE International Conference on Communications, 2010
This paper considers the downlink of a cellular orthogonal frequency division multi-access (OFDMA) system, in which multiple base stations (BS) are coordinated by a centralized resource allocation algorithm. We address the problem of maximizing the weighted sum min-rate (WSMR) subject to a total power constraint at each BS, in terms of jointly optimizing coordinated BSs' subcarrier and power allocation. In particular, this problem leads to a resource allocation that guarantees similar rates to users in each cell. An iterative algorithm is proposed to optimize subcarrier and power allocation alternatively, so that the WSMR keeps increasing until convergence. In each iteration, the subcarrier allocation is updated by solving a mixed integer linear programming problem for each cell, while the power allocation is updated by solving a successive set of convexoptimization problems with an algorithm based on Karush-Kuhn-Tucker conditions. The effectiveness of the algorithm is illustrated by numerical experiments.
Reduced complexity QoS aware resource allocation technique for MISO-OFDMA systems
2014 International Conference on Computing, Networking and Communications (ICNC), 2014
In this paper, we propose a reduced complexity resource allocation technique for the downlink of Multiple-Input Single-Output Orthogonal Frequency Division Multiple-Access (MISO-OFDMA) system. The proposed algorithm efficiently allocates frequency resources among users per subcarrier such that a group of users are simultaneously assigned on the same subcarrier with minimum amount of interference through zero forcing beamforming (ZFBF). The proposed algorithm considers quality of service (QoS) in terms of minimum user rate for each user and preserves fairness among users. QoS plays a key role in fulfillment of users demand of high bandwidth data services in modern wireless systems. Simulation results reveals that the proposed algorithm outperforms other reference algorithms in terms of sum rate, minimum user rate, QoS and preserves a very good fairness performance. Complexity of proposed algorithm is measured by execution time needed and compared to reference algorithms. Simulation results show a further reduction in complexity.
IEEE Transactions on Signal Processing, 2000
This paper considers the downlink of a cellular orthogonal frequency division multi-access (OFDMA) system, in which multiple base stations (BSs) are coordinated by a centralized resource allocation algorithm. We address the problem of maximizing the weighted sum of the minimal user rates (WSMR) of coordinated cells subject to a total power constraint at each BS, in terms of jointly optimizing coordinated BSs' subcarrier and power allocation. In particular, the solution of this problem corresponds to a resource allocation that guarantees similar rates to all users in each cell. An iterative algorithm is proposed to optimize the subcarrier allocation and the power allocation alternatively, so that the WSMR keeps increasing until convergence. In each iteration, the subcarrier allocation is updated by solving a mixed integer linear program for each cell, while the power allocation is updated by solving a successive set of convex optimization problems with a duality-based numerical algorithm. The effectiveness of the algorithm is illustrated by numerical experiments.
Resource allocation in uplink wireless multi-cell OFDMA networks
Computer Standards & Interfaces, 2016
We propose resource allocation models for wireless multi-cell orthogonal frequency division multiple access (OFDMA) networks. The models maximize signal to interference noise ratio (SINR) and capacity with SINR produced in an OFDMA network subject to user power and subcarrier assignment constraints. We derive mixed integer programming formulations for the case when maximizing SINR and piecewise linear approximations for the capacity objective. A variable neighborhood search (VNS) metaheuristic is proposed to compute near optimal solutions. Our numerical results indicate that VNS provides near optimal solutions and better feasible solutions than CPLEX and DICOPT solvers in significantly less computational cost.
2012
This paper considers the downlink of a cellular orthogonal frequency division multi-access (OFDMA) system, in which multiple base stations (BS) are coordinated by a centralized resource allocation algorithm. We address the problem of maximizing the weighted sum min-rate (WSMR) subject to a total power constraint at each BS, in terms of jointly optimizing coordinated BSs' subcarrier and power allocation. In particular, this problem leads to a resource allocation that guarantees similar rates to users in each cell. An iterative algorithm is proposed to optimize subcarrier and power allocation alternatively, so that the WSMR keeps increasing until convergence. In each iteration, the subcarrier allocation is updated by solving a mixed integer linear programming problem for each cell, while the power allocation is updated by solving a successive set of convexoptimization problems with an algorithm based on Karush-Kuhn-Tucker conditions. The effectiveness of the algorithm is illustrated by numerical experiments.
Distributed Resource Optimization in Multicell OFDMA Networks
2012
We consider the joint allocation of receiver, bit, and power to subcarriers in the downlink of multicell orthogonal frequency-division multiple-access (OFDMA) networks. Assuming that the cells share the entire bandwidth and that the rates are discrete, we formulate the joint allocation problem as a nonlinear mixed integer program (MIP), which however has exponential worst-case complexity. We capitalize on the capability of the receivers to measure the interference-plus-noise on every subcarrier and decompose the joint problem into a set of smaller-scale linear MIPs solved by individual base stations. Accordingly, we propose a distributed algorithm with linear complexity, in which the base stations participate in the problem solution in a round-robin manner. Simulation results demonstrate the effectiveness of the proposed algorithm in comparison with the iterative waterfilling algorithm and the successive optimal solution, by means of standard branch-and-cut solvers, of the individual MIPs.
Low complexity QoS-aware subcarrier allocation for MISO-OFDMA systems
IEICE Communications Express, 2014
A low complexity Quality-of-Service (QoS)-aware sub-carrier allocation/user-selection technique for the downlink of Multiple-Input Single-Output Orthogonal Frequency Division Multiple-Access (MISO-OFDMA) system is proposed. The algorithm allows simultaneous transmission to multiple users on the same sub-carrier through zero-forcing beamforming (ZFBF). The proposed algorithm enhances QoS by preserving minimum rate for each user while providing high bandwidth data services. Simulation results reveals that our algorithm outperforms other reference algorithms in terms of average sum-rate per sub-carrier and QoS, while lower complexity is attained by the proposed algorithm in terms of execution time needed compared to reference algorithms.
Transmit beamforming and power allocation for downlink OFDMA systems
2009
This paper considers a transmit beamforming and subcarrier power allocation method for orthogonal frequency division multiple access (OFDMA) systems. As the beamforming vector control criterion, we employ the maximization of so-called signal-to-leakage-plus-noise ratio (SLNR) at each base station, which enable us to obtain closed form beamforming vector by using only locally available information. We also discuss the local optimality of the SLNR based beamforming vector. As for the subcarrier power allocation, two different approaches are employed, namely, the equalization of signal-to-interferenceplus-noise ratio (SINR) for subcarriers and the maximization of sum rate of subcarriers. Computer simulation results show the validity of the transmit beamforming and power allocation method with highlighting the difference between the two power allocation algorithms.
Radio resource allocation in OFDMA multi-cell networks
2010
In this paper, the problem of allocating users to radio resources (i.e., subcarriers) in the downlink of an OFDMA cellular network is addressed. We consider a multi-cellular environment with a realistic interference model and a margin adaptive approach, i.e., we aim at minimizing total transmission power while maintaining a certain given rate for each user. The computational complexity issues of the resulting model is discussed and proving that the problem is NP-hard in the strong sense. Heuristic approaches, based on network flow models, that finds optima under suitable conditions, or "reasonably good" solutions in the general case are presented. Computational experiences show that, in a comparison with a commercial state-of-the-art optimization solver, the proposed algorithms are effective in terms of solution quality and CPU times.
Resource allocation for OFDMA systems with multi-cell joint transmission
2012 IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2012
This paper considers the downlink resource allocation of a coordinated multi-cell cluster in OFDMA systems with universal frequency reuse. Multi-cell joint transmission is considered via zero-forcing precoding. Furthermore, joint optimization of the user selection and power allocation across multiple subchannels and multiple cells is studied. The objective is to maximize the weighted sum rate under per-base-station power constraints. Based on general duality theory, two iterative resource allocation algorithms are proposed and compared with the optimal solution, which requires an exhaustive search of all possible combinations of users over all subchannels. Simulation results show that the two proposed algorithms achieve a performance very close to the optimal, with much lower computational complexity. In addition, we show that joint user set selection across multiple subchannels significantly improves the system performance in terms of the weighted sum rate.