Cell Association With User Behavior Awareness in Heterogeneous Cellular Networks

Abstract

In heterogeneous cellular networks (HetNets) with macro base station (MBS) and multiple small BSs (SBSs), cell association of user equipment (UE) affects UE transmission rate and network throughput. Conventional cell association rules are usually based on UE received signal-to-interference-andnoise-ratio (SINR) without being aware of other UE statistical characteristics, such as user movement and distribution. User behaviors can indeed be exploited for improving long term network performance. In this paper, we investigate UE cell association in HetNets by exploiting both individual and clustering user behaviors with aim to maximize long-term system throughput. We model the problem as a stochastic optimization problem, and prove that it is PSPACE-hard. For mathematical tractability, we solve the problem in two steps. In the first step, we investigate UE association for a specific SBS. We use restless multi-armed bandit model to derive association priority index for the SBS. In the second step, we develop an Index Enabled Association (IDEA) policy for making cell association decisions in general HetNets based on the indices derived in the first step. IDEA determines a set of admissible BSs for a UE based on SINR, and then associates the UE with the BS that has the smallest index in the set. We conduct simulation experiments to compare IDEA with other three cell association policies. Numerical results demonstrate the significant advantages of IDEA in typical scenarios.

Blockchain-Enabled Wireless Internet of Things: Performance Analysis and Optimal Communication Node Deployment

“…We consider an IoT network that is composed of multiple TNs operating blockchain transactions and multiple FNs supporting blockchain service. The network coverage is set as a circular area with radius 150 m. The radius of interference area is D 0 = 50 m. The transmit power of TN is 20 dBm, and the noise power is −104 dBm [29]. The transaction packet length is 256 bits [30], and the transaction arrival rate is (1/1800) s −1 [24].…”

Leveraging mobility and content caching for proactive load balancing in heterogeneous cellular networks

“…Some schemes such as the work of Coucheney et al consider either users' mobility or users' file demand information. Besides, there exist few contributions that considered mobility and caching together such as users' mobility‐aware caching and user‐association and user behavior aware cell‐association . The focus of these studies was to reduce mobility handovers and reactive load balancing instead of proactive content caching for better LB gains and QoE optimization.…”

“…Besides, there exist few contributions that considered mobility and caching together such as users' mobility-aware caching and user-association 22 and user behavior aware cell-association. 13 The focus of these studies was to reduce mobility handovers and reactive load balancing instead of proactive content caching for better LB gains and QoE optimization. Gholami et al 27 proposed a reactive traffic offloading approach for effective capacity maximization in the HetNets exploiting their user association and power allocation algorithm.…”

“…Various load balancing (LB) solutions have been proposed (eg, see other works) to address the uneven load issue; however, they operate in reactive mode. Under the vast deployment of nodes such as HetNets, these reactive LB policies may become a bottleneck that hinders network to deliver contents seamlessly and leads to worse user experience.…”

“…Among the aforementioned challenges, imbalanced load distribution between macro and small cells is a long-standing problem in these HetNets, which results in inefficient utilization of systems' installed capacity and users' QoE degradation. 7,8 Various load balancing (LB) solutions have been proposed (eg, see other works [7][8][9][10][11][12][13] ) to address the uneven load issue; however, they operate in reactive mode. Under the vast deployment of nodes such as HetNets, these reactive LB policies may become a bottleneck that hinders network to deliver contents seamlessly and leads to worse user experience.…”