Affordable Mobile TV Services in Hybrid Cellular and DVB-H Systems

Mobile TV services are expected to become a key application in future wireless networks. The recently proposed terrestrial digital broadcast technology, DVB-H, especially designed for mobile services, is regarded as a powerful alternative to the 3G cellular networks that already offer these services out on a point-to-point basis. Unfortunately, the cost of supporting real-time streaming and full area coverage seems to be very high compared to fixed TV services. In this article we discuss hybrid IP datacast DVB-H and 3G systems as a possible solution for providing affordable network infrastructure and services. Our approach is DVB-H centric. The 3G cellular system plays the role of providing interactivity, error reporting, and repair for the DVB-H broadcast channel. To enable an easy and efficient interworking of DVB-H and 3G, we employ forward error correction at the application layer with digital fountain coding. The main way to provide lower cost services is to avoid full DVB-H area coverage from the beginning and to perform an incremental DVB-H network deployment that follows the user demand. In this direction, to hide the discontinuity in coverage from the perception of users, we propose to take advantage of the bursty character of DVB-H transmissions and the mobility of users. This is possible by sending additional parity data, either with the DVB-H or the cellular network, in the time intervals between original service bursts. We evaluate the potential DVB-H infrastructure cost savings determined by transmitting additional parity data in DVB-H when targeting vehicular users. The implications of delivering parity data through the cellular network also are discussed. The numerical investigations show a potential for significant cost savings compared with the traditional approaches     

User bandwidth usage-driven hnn neuron excitation method for maximum resource utilization within packet-switched communication networks

Mobile and wireless systems beyond 3G are being designed under the user-centric paradigm. Dynamic resource allocation (DRA) is a topic on intensive research to address efficiently such paradigm. Hopfield neural networks (HNN) have proved useful in the past to solve this kind of complex optimization problems. Recently, various approaches have been proposed to realize HNN-based user-centric DRA. However, the initial algorithms suffer from severe instability problems impacting the overall performance. This letter analyses the source of the existing limitations and proposes an enhanced formulation, ensuring maximum resource utilization while optimizing the convergence of the neural network. The letter highlights the improved performance in terms of optimum convergence and bandwidth utilization