TY - GEN
T1 - QoE-aware resource allocation for mixed traffics in heterogeneous networks based on Kuhn-Munkres algorithm
AU - Wang, Niwei
AU - Fei, Zesong
AU - Kuang, Jingming
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/25
Y1 - 2017/1/25
N2 - This paper studies the resource allocation for the downlink transmission in a heterogeneous network with mixed traffics. From the users' side of view, the quality of experience (QoE) is a subjective measurement, based on which the network utility function is defined and taken as a valuation of the system performance. Because the macrocell and picocell are overlaid, the pico base station (PBS) compensates the performance loss of the macrocell by paying for the assigned subcarriers. For the subcarrier allocation, the weighted bipartite graph (WBG) is constructed and a revised Kuhn-Munkres (KM) algorithm is exploited to find the perfect matching. For the power allocation, the first-order derivative of the network utility function is discussed and the optimal power solution is achieved. Simulation results demonstrate that the proposed algorithm always outperforms the average power allocation algorithm and the proportional fairness (PF) algorithm. In addition, this advantage becomes more obvious with the increasing of the cell radius. Moreover, as the cell radius increases, the normalized QoE performance becomes worse.
AB - This paper studies the resource allocation for the downlink transmission in a heterogeneous network with mixed traffics. From the users' side of view, the quality of experience (QoE) is a subjective measurement, based on which the network utility function is defined and taken as a valuation of the system performance. Because the macrocell and picocell are overlaid, the pico base station (PBS) compensates the performance loss of the macrocell by paying for the assigned subcarriers. For the subcarrier allocation, the weighted bipartite graph (WBG) is constructed and a revised Kuhn-Munkres (KM) algorithm is exploited to find the perfect matching. For the power allocation, the first-order derivative of the network utility function is discussed and the optimal power solution is achieved. Simulation results demonstrate that the proposed algorithm always outperforms the average power allocation algorithm and the proportional fairness (PF) algorithm. In addition, this advantage becomes more obvious with the increasing of the cell radius. Moreover, as the cell radius increases, the normalized QoE performance becomes worse.
KW - Kuhn-Munkres Algorithm
KW - QoE
KW - mixed traffics
KW - resource allocation
KW - utility function
UR - http://www.scopus.com/inward/record.url?scp=85013955244&partnerID=8YFLogxK
U2 - 10.1109/ICCS.2016.7833650
DO - 10.1109/ICCS.2016.7833650
M3 - Conference contribution
AN - SCOPUS:85013955244
T3 - 2016 IEEE International Conference on Communication Systems, ICCS 2016
BT - 2016 IEEE International Conference on Communication Systems, ICCS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Communication Systems, ICCS 2016
Y2 - 14 December 2016 through 16 December 2016
ER -