Elements of information theory
Elements of information theory
Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
Multiuser Detection
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
A power control MAC protocol for ad hoc networks
Proceedings of the 8th annual international conference on Mobile computing and networking
Energy-efficient packet transmission over a wireless link
IEEE/ACM Transactions on Networking (TON)
Joint multiuser detection and optimal spectrum balancing for digital subscriber lines
EURASIP Journal on Applied Signal Processing
Joint scheduling and power control for wireless ad hoc networks
IEEE Transactions on Wireless Communications
Joint Optimization of Transmit Power-Time and Bit Energy Efficiency in CDMA Wireless Sensor Networks
IEEE Transactions on Wireless Communications
Power control and capacity of spread spectrum wireless networks
Automatica (Journal of IFAC)
On adaptive transmission for energy efficiency in wireless data networks
IEEE Transactions on Information Theory
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We consider a constrained energy optimization called Minimum Energy Scheduling Problem (MESP) for a wireless network of users transmitting over time slots, where the constraints arise because of interference between wireless nodes that limits their transmission rates along with load and duty-cycle (ON-OFF) restrictions. Since traditional optimization methods using Lagrange multipliers do not work well and are computationally expensive given the nonconvex constraints, we consider approximation schemes for finding the optimal (minimum energy) transmission schedule by discretizing power levels over the interference channel. First, we show the toughness of approximating MESP for an arbitrary number of users N even with a fixed M. For any r r,r)-bicriteria approximation for this MESP, unless P = NP. Conversely, we show that there exist good approximations for MESP with given N users transmitting over an arbitrary number of M time slots by developing fully polynomial (1,1+Ɛ) approximation schemes (FPAS). For any Ɛ0, we develop an algorithm for computing the optimal number of discrete power levels per time slot (o(1/Ɛ)), and use this to design a (1,1+Ɛ)-FPAS that consumes no more energy than the optimal while violating each rate constraint by at most a 1+Ɛ-factor. For wireless networks with low-cost transmitters, where nodes are restricted to transmitting at a fixed power over active time slots, we develop a two-factor approximation for finding the optimal fixed transmission power value Popt that results in the minimum energy schedule.