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The goal of this research work is to investigate how efficient High Altitude Platforms (HAPs) can be in supporting Multimedia Broadcast/Multicast Service (MBMS) in scenarios in which the terrestrial coverage is not available. Specifically, we propose to implement an effective Radio Resources Management (RRM) policy into the HAP Radio Network Controller (H-RNC), whose main aim is to increase the overall...
Employing channel state information at the network layer, efficient routing protocols for equal-power and optimal-power allocation in a multihop network in fading are proposed. The end-to-end outage probability from source to destination is used as the optimization criterion. The problem of finding the optimal route is investigated under either known mean channel state information (CSI) or known instantaneous...
This paper discusses a Quality of Experience (QoE) driven cross-layer optimization framework for efficient network resource allocation in wireless networks. The proposed scheme jointly optimizes the application layer and the lower layers of the wireless protocol stack with the aim of improving the user's QoE. The Mean Opinion Score (MOS) is used as a common metric for user-perceived quality in the...
Distributed MIMO multi-hop relaying can provide cooperative diversity and overcome path losses, hence, boost the end-to-end (e2e) performance. By using a low-complexity adaptive scheme, where one relay stops sending the message if it is in outage and other nodes adapt to a new space-time code, robust communication links can be further achieved. The contribution of this paper is the derivation of near-optimal...
IEEE P1900.4 is an emerging standard for optimized radio resource utilization where cognitive radio technologies are used for efficient spectrum utilization. In this paper, we design and implement a cognitive wireless network system based on open documents of IEEE P1900.4, and evaluate its performance using UDP streaming and HTTP download. Our experiments show interesting results that total network...
Three applications in wireless networks where model-free stochastic learning is applicable, are discussed. The learning based optimization problems are formulated and simulation results are presented. Some open issues are also discussed.
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