Delay-Optimal Buffer-Aware Probabilistic Scheduling with Adaptive Transmission

Cross-layer scheduling is a promising way to improve Quality of Service (QoS) given a power constraint. In this paper, we investigate the system with random data arrival and adaptive transmission. Probabilistic scheduling strategies aware of the buffer state are applied to generalize conventional deterministic scheduling. Based on this, the average delay and power consumption are analysed by Markov reward process. The optimal delay-power tradeoff curve is the Pareto frontier of the feasible delay-power region. It is proved that the optimal delay-power tradeoff is piecewise-linear, whose vertices are obtained by deterministic strategies. Moreover, the corresponding strategies of the optimal tradeoff curve are threshold-based, hence can be obtained by a proposed effective algorithm. On the other hand, we formulate a linear programming to minimize the average delay given a fixed power constraint. By varying the power constraint, the optimal delay-power tradeoff curve can also be obtained. It is demonstrated that the algorithm result and the optimization result match each other, and are further validated by Monte-Carlo simulation.Comment: 6 pages, 4 figures, accepted by IEEE ICCC 201

A new class of parallel data convolutional codes

We propose a new class of parallel data convolutional codes (PDCCs) in this paper. The PDCC encoders inputs are composed of an original block of data and its interleaved version. A novel single self-iterative soft-in/soft-out a posteriori probability (APP) decoder structure is proposed for the decoding of the PDCCs. Simulation results are presented to compare the performance of PDCCs

On the capacity and normalisation of ISI channels

[Abstract]: We investigate the capacity of various ISI channels with additive white Gaussian noise. Previous papers showed a minimum Eb/N0 of −4.6 dB, 3 dB below the capacity of a flat channel, is obtained using the water-pouring capacity formulas for the 1 + D channel. However, these papers did not take into account that the channel power gain can be greater than unity when water-pouring is used. We present a generic power normalization method of the channel frequency response, namely peak bandwidth normalisation, to facilitate the fair capacity comparison of various ISI channels. Three types of ISI channel, i.e., adder channels, RC channels and magnetic recording channels, are examined. By using our channel power gain normalization, the capacity curves of these ISI channels are shown