Proceedings of the 11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustn 2015 # Using Joint Particle Swarm Optimization and Genetic Algorithm for Resource Allocation in TD-LTE Systems

**Abstract:** Abstract-This paper presents a joint radio resource allocation scheme in LTE/LTE-A systems. In order to maximize system throughput while satisfying the minimum user rate requirement, the resource allocation is modeled as a convex optimization with constraints in this paper, which is proved to be NP-hard. Hence, a heuristic approach based on joint Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is proposed. The proposed method exploits the benefits of GA and PSO so that it could avoid the low speed…

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“…The results indicate a significant performance difference of the ABC algorithm among others algorithms. It can notice from Figure 5 that PSO shows faster transient convergence relative to ABC and GSA, especially during the first 50 iterations at v r = [0, 8], v r = [8,16], v r = [16,25], and v r = [25, 33]. However, as illustrated in Figure 5, ABC shows faster convergence rate to the minimum solution at various speeds range.…”

confidence: 92%

“…The results indicate a significant performance difference of the ABC algorithm among others algorithms. It can notice from Figure 5 that PSO shows faster transient convergence relative to ABC and GSA, especially during the first 50 iterations at v r = [0, 8], v r = [8,16], v r = [16,25], and v r = [25, 33]. However, as illustrated in Figure 5, ABC shows faster convergence rate to the minimum solution at various speeds range.…”

confidence: 92%

“…On the other side, the best global objective function is defined through the beginning of the process up to the current generation. The velocity and position of each particle are defined by (7) and (8), respectively. The remaining steps can be easily followed from the flow chart in Figure 2, in addition to Eberhart and Kennedy.…”

confidence: 99%

“…The candidate solution X i is initialized between the minimum and maximum boundaries of the space, termed x min and x max , respectively, such that x i,j (t) ∈ x j min , x j max . On the other side, the velocity 21) with N intv being the number of intervals.…”

confidence: 99%

“…The authors in [15], [16] have proposed solutions to the MaxRate-MinReq problem based on meta heuristics while [17] presents an exact solution. In [15] the authors define the MCS allocation based on Tabu Search.…”

confidence: 99%

“…However, the proposed solution is not compared to the optimal solution and no outage results are provided. In [16], Particle Swarm Optimization is used in order to perform subcarrier and power allocation. However, the problem is simplified by assuming continuous mapping between SNR and transmit data rate.…”

confidence: 99%