QoE-Driven Channel Allocation and Handoff Management for Seamless Multimedia in Cognitive 5G Cellular Networks

• Published in: IEEE transactions on vehicular technology Vol. 66; no. 7; pp. 6569 - 6585
• Main Authors: Piran, Md Jalil, Tran, Nguyen H., Doug Young Suh, Ju Bin Song, Choong Seon Hong, Zhu Han
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Cellular communication; Cellular networks; Cellular radio; Channel allocation; Channel capacity; Channels; Cognitive radio; Cognitive radio (CR) networks; Computer simulation; Delays; fifth-generation (5G) cellular networks; handoff; Handoff queueing; Markov chains; Multimedia; Multimedia communication; quality of experience (QoE); Stations; Streaming media; User satisfaction; Video transmission; Wireless networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2016.2629507

Cognitive radio (CR) is among the promising solutions for overcoming the spectrum scarcity problem in the forthcoming fifth-generation (5G) cellular networks, whereas mobile stations are expected to support multimode operations to maintain connectivity to various radio access points. However, particularly for multimedia services, because of the time-varying channel capacity, the random arrivals of legacy users, and the on-negligible delay caused by spectrum handoff, it is challenging to achieve seamless streaming leading to minimum quality of experience (QoE) degradation. The objective of this paper is to manage spectrum handoff delays by allocating channels based on the user QoE expectations, minimizing the latency, providing seamless multimedia service, and improving QoE. First, to minimize the handoff delays, we use channel usage statistical information to compute the channel quality. Based on this, the cognitive base station maintains a ranking index of the available channels to facilitate the cognitive mobile stations. Second, to enhance channel utilization, we develop a priority-based channel allocation scheme to assign channels to the mobile stations based on their QoE requirements. Third, to minimize handoff delays, we employ the hidden markov model (HMM) to predict the state of the future time slot. However, due to sensing errors, the scheme proactively performs spectrum sensing and reactively acts handoffs. Fourth, we propose a handoff management technique to overcome the interruptions caused by the handoff. In such a way that, when a handoff is predicted, we use scalable video coding to extract the base layer and transmit it during a certain interval time before handoff occurrence to be shown during handoff delays, hence providing seamless service. Our simulation results highlight the performance gain of the proposed framework in terms of channel utilization and received video quality.