#(WSNs) are under rapid deployment. Planning and optimization techniques play a vital role in the deployment and operation of almost types of networks. Specifically, the adoption of optimization and planning procedures are still in progress during the lifetime of a broadband radio access network. The proper adoption of planning and optimization procedures enables the successfully deployment and expansion of the BRANs. In the initial phase, planning deals with issues of network dimensioning and configuration, including the number and locations of base stations (BSs) and their configuration parameters. (Re-) optimization tasks take place during network operation; frequently, a network is subject to reoptimization in order to adapt to changing demands and additional service requirements. It is worth noting the direct application of the optimization and/or planning solutions obtained in the context of broadband cellular system-based networks is not optimal for the adhoc networks. Resource optimization (RO) techniques, primarily power/energy consumption minimization, are becoming increasingly important in wireless systems and networks design, since battery technology evolution has not followed the explosive demand of mobile devices. Specifically, typical optimization problem in WSNs consists in efficiently reduce the required energy consumption while maximizing the lifetime of the network sensors. For that, source and path redundancy techniques is commonly used. As a result, the number of active sensor nodes can be optimized in order to sense and communicate with base station (BS), while a time slots duration strategy to each sensor nodes is assumed. Due to the large amount of investments spent on radio access, appropriate planning and optimization procedures are crucial to any business model. As a benefit, a well-planned network, especially BRAN, requires less infrastructure, mainly fewer BS sites, which has been proven to be a severe constraint in provisioning 3G/4G networks. Besides, well-planned BRAN makes more efficient use of radio resource, offering extra capacities under the same infrastructure.
[1]
Geoffrey Ye Li,et al.
Fundamental trade-offs on green wireless networks
,
2011,
IEEE Communications Magazine.
[2]
Slawomir Stanczak,et al.
Resource Allocation in Wireless Networks: Theory and Algorithms
,
2006,
Lecture Notes in Computer Science.
[3]
H. Vincent Poor,et al.
Transmitter Waveform and Widely Linear Receiver Design: Noncooperative Games for Wireless Multiple-Access Networks
,
2010,
IEEE Transactions on Information Theory.
[4]
Geoffrey Ye Li,et al.
Distributed Interference-Aware Energy-Efficient Power Optimization
,
2011,
IEEE Transactions on Wireless Communications.
[5]
Lajos Hanzo,et al.
Green radio: radio techniques to enable energy-efficient wireless networks
,
2011,
IEEE Communications Magazine.
[6]
H. Vincent Poor,et al.
An energy-efficient approach to power control and receiver design in wireless data networks
,
2005,
IEEE Transactions on Communications.
[7]
H. Vincent Poor,et al.
Joint Receiver and Transmitter Optimization for Energy-Efficient CDMA Communications
,
2007,
IEEE Journal on Selected Areas in Communications.
[8]
Michael L. Honig,et al.
Advances in Multiuser Detection
,
2009
.
[9]
H. Vincent Poor,et al.
Energy-Efficient Resource Allocation in Wireless Networks
,
2007,
IEEE Signal Processing Magazine.