Abstract
Due to the high splitting-gain of dense small cells, Ultra-Dense Network (UDN) is regarded as a promising networking technology to achieve high data rate and low latency in 5G mobile communications. In UDNs, each User Equipment (UE) may receive signals from multiple Base Stations (BSs), which impose severe interference in the networks and in turn motivates the possibility of using Coordinated Multi-Point (CoMP) transmissions to further enhance network capacity. In CoMP-based Ultra-Dense Networks, a great challenge is to tradeoff between the gain of network throughput and the worsening backhaul latency. Caching popular files on BSs has been identified as a promising method to reduce the backhaul traffic load. In this paper, we investigated content placement strategies and user association algorithms for the proactive caching ultra dense networks. The problem has been formulated to maximize network throughput of cell edge UEs under the consideration of backhaul load, which is a constrained non-convex combinatorial optimization problem. To decrease the complexity, the problem is decomposed into two suboptimal problems. We first solved the content placement algorithm based on the cross-entropy (CE) method to minimize the backhaul load of the network. Then, a user association algorithm based on the CE method was employed to pursue larger network throughput of cell edge UEs. Simulation were conducted to validate the performance of the proposed cross-entropy based schemes in terms of network throughput and backhaul load. The simulation results show that the proposed cross-entropy based content placement scheme significantly outperform the conventional random and Most Popular Content placement schemes, with with 50% and 20% backhaul load decrease respectively. Furthermore, the proposed cross-entropy based user association scheme can achieve 30% and 23% throughput gain, compared with the conventional N-best, No-CoMP, and Threshold based user association schemes.
Highlights
Inspired by the development of intelligent terminal such as smart phones, the demand for data traffic in mobile communication systems is exponentially growing
Coordinated Multi-Point (CoMP) transmissions technique is widely studied in academia and the industry, which can leverage the cooperation of multiple Base Stations (BSs) to enhance the signal to interference and noise ratio (SINR), to counteract intercell interference and to enhance network capacity in Ultra-Dense Network (UDN)
We minimize the backhaul load of the system under the assumption of the conventional N-Best user association strategy (By N-Best user association strategy, a CoMP User Equipment (UE) will associate with Nmax BSs which have N best SINRs [16]) and propose a content placement algorithm based on cross entropy, which is termed as the CPCE algorithm
Summary
Inspired by the development of intelligent terminal such as smart phones, the demand for data traffic in mobile communication systems is exponentially growing. Entropy 2019, 21, 576 the capacity per area under the limited spectrum resource due to the high splitting-gain of densely located small cells and is widely considered as one of the most promising techniques in the coming 5G It benefits load balance between Base Stations (BSs) since Small Base Stations (SBSs) can offload data traffic of Macro Base Stations (MBSs). In [5], a distributed algorithm is proposed to investigate content placement and user association jointly. In [9], the user association problem is modeled as an one-to-many game problem, based on which algorithm is proposed to maximize the average download rate under a given content placement strategy. The problem of content placement and user association is investigated jointly in large-scale cache-enabled coordinated ultra dense networks. Simulation results show that the proposed caching and user association algorithms can reduce backhaul load and improve network throughput of cell edge UEs simultaneously.
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