Abstract
With a growing demand for high-quality mobile live video streaming services, cellular networks are facing an unprecedented challenge of dramatically increased mobile data usage. Recently, device-to-device (D2D) aided multicasting has been introduced and considered as one of the promising techniques to tackle such imminent mobile live video streaming dilemma of cellular networks by enabling direct data transmissions among users in proximity. The clustering strategy is essential to the D2D-aided multicasting in cellular networks. To address this issue, a novel clustering policy is presented in this paper, under which a BS simply groups the associated users based on their received sounding reference signal (SRS) strength and selects the users with the largest average received SRSs as the cluster head in each group to maximize the multicasting performance. Further, by applying the idea of multi-armed bandits, the multicasting latency induced by the process of clustering and cluster head selection can be significantly reduced. We analyze the performance of the D2D-aided multicasting network. The effectiveness of the proposed multi-armed bandit based clustering strategy is demonstrated through extensive simulations.
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Notes
- 1.
It is worth noting that given n users in the k-th cluster, if \({T_k^j(t)\ge n-1}\), \(C_k^j(t) = 0\).
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Wu, Z. (2023). D2D-Aided Multicasting with Multi-armed Bandit Based Clustering. In: Liang, Q., Wang, W., Liu, X., Na, Z., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2022. Lecture Notes in Electrical Engineering, vol 873. Springer, Singapore. https://doi.org/10.1007/978-981-99-1260-5_25
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DOI: https://doi.org/10.1007/978-981-99-1260-5_25
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