Research On Energy-efficient Transmission Scheduling In Wireless Multi-access Networks

With a variety of application prospects, Wireless Sensor Networks (WSNs) are currently developed under severely limited resources constraints. As the sensor nodes are usually supported by batteries, energy economization is considered as one of the main design principles for WSNs. Reducing the energy consumption of sensor nodes in order to extend the network life involves several aspects, the most important one of which concerns the transmission scheduling. Because in practical applications, WSNs generally possess multi-access channel models, the energy-efficient multi-access scheduling problem in WSNs is particularly important. We will tackle the problem form an integrated and interdisciplinary view, with the disciplines, methods and results in information theory and scheduling theory. The researches are mainly carried out in the following aspects:With the objective to minimize the transmission energy cost, we consider the energy-efficient scheduling problem in a single hop multi-access data gathering sensor network. We first prove by theoretical induction that transmitting with reduced powers decreases the energy budget in a multi-access transmission. Given the optimal transmit powers, we then examine the multi-access capacity polymatroid and argue that the optimal rate control can be achieved by controlling the successive decoding order of the transmitting sensor nodes. Consequently, the multi-access scheduling problem is reformulated into job scheduling problems and solved by adapting job scheduling policies. Concerning both the backlog lengthes and the channel state information of the sensor nodes, the proposed strategies are tailored for symmetric and asymmetric multi-access networks, respectively.From an information-theoretic point of view, we investigate the min-max power scheduling problem in multi-access transmission. Exploiting the relation between min-max optimal and lexicographical optimal, we prove that the min-max optimal vector in a contra-polymatroid is the base with the minimal distance to the equal allocation vector. Because we can realize any base of the contra-polymatroid by time sharing among the vertices, the problem searching for the min-max optimal vector is converted to a convex optimization problem solving the time sharing coefficients. By adopting the proposed method and applying the acquired min-max optimal scheduling to multi-access transmission, the network lifetime of the wireless sensor network is prolonged.We propose a practical algorithm to compute the splitting coefficients and the successive decoding order of virtual users in Gaussian Rate Splitting Multiple Access (RSMA) transmission. RSMA transmission is a code division multi-access technique which can achieve any base in the multi-access capacity polymatroid without high coding complexity or synchronization among the transmitting users. To the scope of the author, there is not any practical algorithm to compute the splitting parameters for a given power/rate allocation. Based on our proposed algorithm, a deterministic mapping is built between the system parameters and the objective rate tuple for RSMA. As a result, the application of the RSMA technique becomes possible in current communication systems.To prolong the lifetime of wireless sensor networks, we investigate the energy-efficient scheduling problem in TDMA transmission. With the objective to minimize the transmission energy under delay constraint, the problem is formulated as a discrete-time Markov decision process, and the constrained optimal policies are computed. Applying the constrained optimal policy, we minimize the energy cost per packet while guarantee a worst case average packet delay. Superior to the existing policies, the proposed scheduling determines the scheduled sensor node as well as the transmission duration of the scheduled packet only by current backlogs of the sensor nodes. As there is not any particular assumption for the multi-access, the proposed scheduling can be effectively applied to current sensor networks as well as other multi-user communication systems, such as the uplink in cellular system.