The conference's extensive keynote and plenary schedule concluded this morning with the highly-informative addresses of leading industry experts highlighting the next wave of transformational communications and the evolving needs, expectations and requirements of companies and individuals worldwide.

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This paper focuses on the unslotted cognitive radio networks in which the secondary users (SUs) are not synchronized with the primary users (PUs). The SUs can opportunistically utilize the wireless channel as long as the channel is not occupied by the PUs. Due to the half-duplex nature of the wireless medium, the SUs may inevitably impose interference to the PUs because the SUs cannot precisely predict when the PUs becomes active again, and stop transmitting in time. To overcome this challenge, we propose an interference-confined adaptive transmission scheme, which can dynamically adjust the transmission duration of the SUs based on the statistical information of PUs' activity such as to confine the interference with PUs to the acceptable level. Also conducted are extensive simulations to validate and evaluate our proposed scheme. The simulation results show that our proposed scheme can significantly outperform the existing transmission schemes.Index Terms-Cognitive radio networks, adaptive transmission scheme, opportunistic spectrum access, medium access control (MAC).

Effective capacity is a useful technique to characterize the system throughput with statistical delay-constrained quality of service (QoS) guarantees. In this paper, we integrate effective capacity theory into superposition-coding (SPC) based multicast transmission to devise the efficient channel-aware multicasting scheme in wireless networks. Specifically, we propose to optimize the effective capacity for multicast transmissions subject to the specified loss-rate constraint and the statistical delay QoS requirement in terms of the QoS exponent. We use superposition coding in wireless multicast to handle heterogeneous channel fading across multicast receivers, and apply the pre-drop strategy to gain more flexible rate control. Under our proposed framework, we derive the optimal pre-drop strategy and the optimal power/rate allocation for each layer of superposition coding. Simulation analyses present insightful observations on tradeoff between effective capacity and the QoS requirements, and demonstrate the superiority of the SPC-based scheme over the existing timesharing (TS) based multicast scheme.

Abstract-Due to the time-varying wireless channels, deterministic quality of service (QoS) is usually difficult to guarantee for real-time multi-layer video transmissions in wireless networks. Consequently, statistical QoS guarantees have become an important alternative in supporting real-time video transmissions. In this paper, we propose an efficient framework to model the statistical delay QoS guarantees, in terms of QoS exponent, effective bandwidth/capacity, and delay-bound violation probability, for multi-layer video transmissions over wireless fading channels. In particular, a separate queue is maintained for each video layer, and the same delay bound and corresponding violation probability threshold are set up for all layers. Applying the effective bandwidth/capacity analyses on the incoming video stream, we obtain a set of QoS exponents for all video layers to effectively characterize this delay QoS requirement. We then develop a set of optimal adaptive transmission schemes to minimize the resource consumption while satisfying the diverse QoS requirements under various scenarios, including video unicast/multicast with and/or without loss tolerance. Simulation results are also presented to demonstrate the impact of statistical QoS provisionings on resource allocations of our proposed adaptive transmission schemes.Index Terms-Mobile multicast, wireless networks, rate control, layered video streaming, statistical QoS guarantees.