Resource allocation for high-speed railway downlink MIMO-OFDM system using quantum-behaved particle swarm optimization

Abstract

Resource allocation problem in high-speed railway wireless communication networks is one of the key issues to improve the efficiency of resource utilization. However, traditional resource allocation methods cannot be directly applied to this special communication system. In this paper, we propose a resource allocation approach for high-speed railway downlink orthogonal frequency-division multiplexing (OFDM) system with multiple-input multiple-output (MIMO) antennas. Sub-carriers, antennas, time slots, and power are jointly considered, which is formulated as a mixed-integer nonlinear programming problem. The effect of the moving speed on Doppler shift is analyzed to calculate the inter-carrier interference power. The objective is to maximize the throughput under the constraint of total transmission power. In order to reduce computational complexity, suboptimal solution to the optimization problem is obtained by quantum-behaved particle swarm optimization. Simulation results show that the proposed resource allocation strategy has a better performance compared with an existing one.Index Terms-Resource allocation, high-speed railway, MIMO, OFDM, quantum-behave particle swarm optimization.

Dynamic resource allocation for multimedia services delivery in cellular/infostation integrated HSR networks

“…The data packet size is 100 bits. Moreover, the related simulation parameters are set to be T s = 1.33 × 10 -4 s, f c = 2.6 GHz, c = 3 × 10 8 m/s, B = 7.5 kHz, N 0 = 2 × 10 -7 W/Hz (Zhao et al, 2013). We consider Poisson arrival processes with different average data rates for users, where the average arrival data rate for a user is randomly selected from the set {3,4,5,6} (packets per time slot).…”

Analysis and Optimization of Resource Control in High-Speed Railway Wireless Networks

“…(2) while ∈ [0, ] do (3) for = 1 to do (4) Obtain ( ) by solving (20a) and (20b); (5) Obtain AC actions ( ) by solving (25); (6) Obtain RA actions ( ) by solving problem (27a) -(27d); 7Update Θ( + 1) according to (4), (7) and (9); (8) end for (9) end while.…”

“…A HSR communication system based on radio over fiber technology was proposed in [3], which can increase the system throughput and help to reduce the number of handoffs. Multi-input multi-output (MIMO) antennas were employed to improve the throughput performance of the HSR wireless networks [4,5]. However, these works were carried out only to improve the throughput performance in HSR wireless networks.…”

Resource scheduling for hybrid broadcasting and cellular networks

“…An RS algorithm according to different types of services is researched in [10]. In research [11], a multi-dimensional resource allocation strategy in high speed mobility scenario is discussed by taking sub-carrier, antennas, time slots, and power resources into consideration. In [12], broadcasting scheduling algorithm on minimizing the average response time of users is discussed.…”