Scheduling jobs with hard deadlines over Multiple Access and Degraded Broadcast Channels

We consider the problem of scheduling jobs with given start and finish times over two classes of multi-user channels, namely Multiple Access Channels and Degraded Broadcast Channels, and derive necessary and sufficient conditions for feasible scheduling of the jobs

Optimal Save-Then-Transmit Protocol for Energy Harvesting Wireless Transmitters

In this paper, the design of a wireless communication device relying exclusively on energy harvesting is considered. Due to the inability of rechargeable energy sources to charge and discharge at the same time, a constraint we term the energy half-duplex constraint, two rechargeable energy storage devices (ESDs) are assumed so that at any given time, there is always one ESD being recharged. The energy harvesting rate is assumed to be a random variable that is constant over the time interval of interest. A save-then-transmit (ST) protocol is introduced, in which a fraction of time {\rho} (dubbed the save-ratio) is devoted exclusively to energy harvesting, with the remaining fraction 1 - {\rho} used for data transmission. The ratio of the energy obtainable from an ESD to the energy harvested is termed the energy storage efficiency, {\eta}. We address the practical case of the secondary ESD being a battery with {\eta} < 1, and the main ESD being a super-capacitor with {\eta} = 1. The optimal save-ratio that minimizes outage probability is derived, from which some useful design guidelines are drawn. In addition, we compare the outage performance of random power supply to that of constant power supply over the Rayleigh fading channel. The diversity order with random power is shown to be the same as that of constant power, but the performance gap can be large. Furthermore, we extend the proposed ST protocol to wireless networks with multiple transmitters. It is shown that the system-level outage performance is critically dependent on the relationship between the number of transmitters and the optimal save-ratio for single-channel outage minimization. Numerical results are provided to validate our proposed study.Comment: This is the longer version of a paper to appear in IEEE Transactions on Wireless Communication

Optimal Energy Allocation for Wireless Communications with Energy Harvesting Constraints

We consider the use of energy harvesters, in place of conventional batteries with fixed energy storage, for point-to-point wireless communications. In addition to the challenge of transmitting in a channel with time selective fading, energy harvesters provide a perpetual but unreliable energy source. In this paper, we consider the problem of energy allocation over a finite horizon, taking into account channel conditions and energy sources that are time varying, so as to maximize the throughput. Two types of side information (SI) on the channel conditions and harvested energy are assumed to be available: causal SI (of the past and present slots) or full SI (of the past, present and future slots). We obtain structural results for the optimal energy allocation, via the use of dynamic programming and convex optimization techniques. In particular, if unlimited energy can be stored in the battery with harvested energy and the full SI is available, we prove the optimality of a water-filling energy allocation solution where the so-called water levels follow a staircase function.Comment: 27 pages, 6 figures, accepted for publications at IEEE Transactions on Signal Processin

Reducing power consumption in LEO satellite network

Current low earth orbit (LEO) satellite network display poor power efficiency, running network devices at full capacity all the time regardless of the traffic matrix and the distribution of the population over the Globe. Most of the research on energy efficiency of LEO satellites has focused on component level or link level. Therefore, this kind of research is not holistic to try to look at the satellite system as a single node. To enhance the energy efficiency. The solution should exploits multipath routing and load balancing. LEO network is overprovisioned, and hence selectively shutting down some satellite nodes and links during off-peaks hours seems like a good way to reduce energy consumption. In this paper, we exploit the fact that due to geographical and climatic conditions, some satellite links are expected to be loaded with data while others remain unused. Our approach is to power down satellite nodes and links during period of low traffic, while guaranteeing the connectivity and QoS. Finding the optimal solution is NP-problem and therefore, we explore in this work two heuristic algorithms. We evaluate our heuristics on a realistic LEO topology and real traffic matrices. Simulation results show that the power saving can be significant

Energy-efficient optimal power allocation in integrated wireless sensor and cognitive satellite terrestrial networks

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach’s method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint

Call admission control for interactive multimedia satellite networks.

Master of Science in Engineering (Electronic). University of KwaZulu-Natal, Durban 2015.Satellite communication has become an integral component of global access communication network due mainly to its ubiquitous coverage, large bandwidth and ability to support for large numbers of users over fixed and mobile devices. However, the multiplicity of multimedia applications with diverse requirements in terms of quality of service (QoS) poses new challenges in managing the limited and expensive resources. Furthermore, the time-varying nature of the propagation channel due to atmospheric and environmental effects also poses great challenges to effective utilization of resources and the satisfaction of users’ QoS requirements. Efficient radio resource management (RRM) techniques such as call admission control (CAC) and adaptive modulation and coding (AMC) are required in order to guarantee QoS satisfaction for user established connections and realize maximum and efficient utilization of network resources. In this work, we propose two CAC policies for interactive satellite multimedia networks. The two policies are based on efficient adaptation of transmission parameters to the dynamic link characteristics. In the first policy which we refer to as Gaussian Call Admission Control with Link Adaptation (GCAC-LA), we invoke the central limit theorem to statistically multiplex rate based dynamic capacity (RBDC) connections and obtain an aggregate bandwidth and required capacity for the multiplex. Adaptive Modulation and Coding (AMC) is employed for transmission over the time-varying wireless channel of the return link of an interactive satellite network. By associating users’ channel states to particular transmission parameters, the amount of resources required to satisfy user connection requirements in each state is determined. Thus the admission control policy considers in its decision, the channel states of all existing and new connections. The performance of the system is investigated by simulation and the results show that AMC significantly improves the utilization and call blocking performance by more than twice that of a system without link adaptation. In the second policy, a Game Theory based CAC policy with link adaptation (GTCAC-LA) is proposed. The admission of a new user connection under the GTCAC-LA policy is based on a non-cooperative game that is played between the network (existing user connections) and the new connection. A channel prediction scheme that predicts the rain attenuation on the link in successive intervals of time is also proposed. This determines the current resource allocation for every source at any point in time. The proposed game is played each time a new connection arrives and the strategies adopted by players are based on utility function, which is estimated based on the required capacity and the actual resources allocated. The performance of the CAC policy is investigated for different prediction intervals and the results show that multiple interval prediction scheme shows better performance than the single interval scheme. Performance of the proposed CAC policies indicates their suitability for QoS provisioning for traffic of multimedia connections in future 5G networks

Optimal energy allocation and admission control for communications satellites

Abstract—We address the issue of optimal energy allocation and admission control for communications satellites in earth orbit. Such satellites receive requests for transmission as they orbit the earth, but may not be able to serve them all, due to energy limitations. The objective is to choose which requests to serve so that the expected total reward is maximized. The special case of a single energy-constrained satellite is considered. Rewards and demands from users for transmission (energy) are random and known only at request time. Using a dynamic programming approach, an optimal policy is derived and is characterized in terms of thresholds. Furthermore, in the special case where demand for energy is unlimited, an optimal policy is obtained in closed form. Although motivated by satellite communications, our approach is general and can be used to solve a variety of resource allocation problems in wireless communications. Index Terms—Communication, dynamic programming, resource allocation, satellite. I