Energy minimization based Resource Scheduling for Strict Delay Constrained Wireless Communications

This paper investigates the energy consumption minimization for resource scheduling in a wireless communication. We propose to take into account a strict delay constraint for each queued packet rather than an average delay constraint, in addition to a buffer overflow constraint. The associated optimization problem can be modeled as Constraint Markov Decision Problem where the actions are the number of packets sent on the known channel at each slot. The optimal random policy is exhibited through the resolution of standard linear programming. We show the gain in energy is substantial compared to naive policy

Adaptive access and rate control of CSMA for energy, rate and delay optimization

In this article, we present a cross-layer adaptive algorithm that dynamically maximizes the average utility function. A per stage utility function is defined for each link of a carrier sense multiple access-based wireless network as a weighted concave function of energy consumption, smoothed rate, and smoothed queue size. Hence, by selecting weights we can control the trade-off among them. Using dynamic programming, the utility function is maximized by dynamically adapting channel access, modulation, and coding according to the queue size and quality of the time-varying channel. We show that the optimal transmission policy has a threshold structure versus the channel state where the optimal decision is to transmit when the wireless channel state is better than a threshold. We also provide a queue management scheme where arrival rate is controlled based on the link state. Numerical results show characteristics of the proposed adaptation scheme and highlight the trade-off among energy consumption, smoothed data rate, and link delay.This study was supported in part by the Spanish Government, Ministerio de Ciencia e Innovación (MICINN), under projects COMONSENS (CSD2008-00010, CONSOLIDER-INGENIO 2010 program) and COSIMA (TEC2010-19545-C04-03), in part by Iran Telecommunication Research Center under contract 6947/500, and in part by Iran National Science Foundation under grant number 87041174. This study was completed while M. Khodaian was at CEIT and TECNUN (University of Navarra)

A Simple Packet Transmission Scheme for Wireless Data over Fading Channels

In this paper, we present a simplified scheduling scheme for packet transmission over a fading channel which is modeled as a finite state block channel. We first derive the optimal minimum power transmission policy with constraints on both average delay and packet loss. This problem is seen to be the dual problem of the work by Rajan et. al. [1] where the packet loss rate is minimized under constraints on average delay and power. The optimal policy requires a sophisticated tablelook -up for implementation. In order to alleviate this problem, we design a simplified transmission policy that is based on checking for three control parameters: a transmission rate threshold, a channel state threshold and the transmission buffer size. Our results show that the minimum average power with the simplified scheme is very close to that achieved by the optimal policy. By relaxing the packet loss constraint, the simplified policy is also found to allow reduced buffer sizes, thereby simplifying system implementation. With the simplified scheduling policy, the transmitter can be modeled as a bulk service queue and an upper bound for the average delay is derived. Further, the packet loss rate and the average transmit power are estimated using an imbedded Markov chain technique

Resource allocation for delay constrained wireless communications

The ultimate goal of future generation wireless communications is to provide ubiquitous seamless connections between mobile terminals such as mobile phones and computers so that users can enjoy high-quality services at anytime anywhere without wires. The feature to provide a wide range of delay constrained applications with diverse quality of service (QoS) requirements, such as delay and data rate requirements, will require QoS-driven wireless resource allocation mechanisms to efficiently allocate wireless resources, such as transmission power, time slots and spectrum, for accommodating heterogeneous mobile data. In addition, multiple-input-multiple-output (MIMO) antenna technique, which uses multiple antennas at the transmitter and receiver, can improve the transmission data rate significantly and is of particular interests for future high speed wireless communications. In the thesis, we develop smart energy efficient scheduling algorithms for delay constrained communications for single user and multi-user single-input-single-output (SISO) and MIMO transmission systems. Specifically, the algorithms are designed to minimize the total transmission power while satisfying individual user’s QoS constraints, such as rate, delay and rate or delay violation. Statistical channel information (SCI) and instantaneous channel state information (CSI) at the transmitter side are considered respectively, and the proposed design can be applied for either uplink or downlink. We propose to jointly deal with scheduling of the users that access to the channel for each frame time (or available spectrum) and how much power is allocated when accessing to the channel. In addition, the algorithms are applied with modifications for uplink scheduling in IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX). The success of the proposed research will significantly improve the ways to design wireless resource allocation for delay constrained communications