Traffic Offloading with Channel Allocation in Cache-Enabled Ultra-Dense Wireless Networks

Abstract

Traffic offloading via device-to-device communications is expected to play a major role to meet the exponential data traffic growth in wireless networks. In this work, we focus on the problem of user capacity maximization in ultra dense heterogeneous networks with device-to-device cooperation, where a large number of users in a given geographical area request common data content, such as video on demand streaming, with strict quality of service guarantees. We aim at finding the best strategy for delivering the content either over long range connectivity from the access points or short range connectivity from peer mobile terminals while meeting a target rate per served user. We formulate the multi-user resource management problem as an optimization problem including traffic offloading and channel allocation considering a very high user density reaching up to 1.75 users per square meter. We extend the system model to include mobile terminals acting as content owners by having the content cached locally, in order to further enhance the network's capacity and coverage. We then propose an iterative resource management solution, which first solves the optimization sub-problem of traffic offloading with orthogonal channels, and then optimally allocates channels to the transmitters with minimized interference due to channel reuse. We also propose efficient sub-optimal hierarchical tree-based algorithms that operate in real time with dynamic and fast solutions for ultra dense networks. For performance evaluation, we consider a realistic scenario consisting of a stadium topology with thousands of mobile terminals active simultaneously. We generate results as a function of a wide range of system parameters, and demonstrate that the proposed algorithms achieve near-optimal performance with notably low time complexity.