Author : Guidan Yao
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Book Synopsis Information Freshness and Delay Optimization in Unreliable Wireless Systems by : Guidan Yao
Download or read book Information Freshness and Delay Optimization in Unreliable Wireless Systems written by Guidan Yao and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid development of time-critical applications in wireless networks like video streaming and augmented reality, there have been significant efforts been made to deliver time-efficient services in terms of different time-related metrics, i.e., delay and the age. However, the problems become increasingly challenging in the wireless environment because of the inherent unreliability of the wireless channel. In this dissertation, we investigate optimal transmission scheduling policies in terms of either delay or the age in variety of unreliable wireless systems. We take into account heterogenous transmission choices in terms of transmission delay and error probability, and transmission with energy constraints. We show that making optimal transmission decisions can greatly improve latency in terms of delay and age. We develop an integrated mmWave-sub-6 GHz architecture, where packets can be delivered via either mmWave or sub-6 GHz interface. Our goal is to combat the intermittency of the mmWave and thus reduce the resultant delay with aid of scheduling design and usage of the sub-6 GHz. To this end, we show that the delay- optimal policy for the system is of threshold-type, i.e., packets should always be routed to the mmWave interface as long as the number of packets in the system is smaller than the state-dependent threshold. Moreover, numerical results demonstrate that under heavy traffic, integrating sub-6 GHz with mmWave can reduce the average delay by over 70%. We also study age minimization with heterogenous transmission choices. In particular, we consider a status update system, in which update packets are sent to the destination via a wireless medium that allows for multiple rates, where a higher rate also naturally corresponds to a higher error probability. We design a low-complexity optimal scheduler that selects between two different transmission rate and error prob- ability pairs to be used at each transmission epoch. To this end, we show that there exists a threshold-type policy that is age-optimal, and that the objective function is quasi-convex or non-decreasing in the threshold. In wireless sensor networks or IoT systems, devices are usually energy limited. Further, different knowledge of channel state information (CSI) may require differ- ent policies to minimize the age under energy constraints. To get some insights on transmission scheduling with imperfect CSI, we consider a system, where updates are periodically generated and transmitted to the destination over a time-correlated fading channel. And we consider two practical ways to obtain the CSI: (i) CSI is revealed by the feedback on transmissions, (ii) CSI is available via delayed channel sensing. Our goal is to find transmission control (transmission or suspension) policy that minimizes the long-term average age under a constraint on the average energy. For either case, we prove that the optimal policy is a randomized mixture of no more than two stationary deterministic threshold-type policies. With the properties, we design low-complexity structure-aware algorithms. Finally, we consider both energy and distortion requirements and consider a status update system, where an access point collects samples from multiple sensors and transmits the collected samples to the destination over error-prone channels. Our goal is to minimize the long-term average age under constraints on the long-term average energy and distortion of each update, where the distortion is determined by the number of collected samples. Under the assumption that the distortion requirement is a non-decreasing function of the age, we show that the optimal policy is a mixture of two stationary deterministic policies, each of which is optimal for a parameterized average cost problem and is of a threshold-type, i.e., transmission is conducted when the age exceeds a threshold and the distortion requirement is met. We derive the average cost as a piecewise function of threshold, and obtain the optimal threshold in the last interval. With these, we develop a low-complexity algorithm for the original problem. Moreover, we provide a closed-form solution to the parameterized problem with constant distortion function.
