I, base station: Cognisant robots and future wireless access networks

Author(s):  
H. Claussen ◽  
L.T.W. Ho ◽  
H.R. Karimi ◽  
F.J. Mullany ◽  
L.G. Samuel
Author(s):  
Chetna Singhal ◽  
Swades De

The advent of heterogeneous Broadband Wireless Access Networks (BWANs) has been to support the ever increasing cellular networks' data requirements by increasing capacity, spectrum efficiency, and network coverage. The focus of this chapter is to discuss the implementation details (i.e. architecture and network components), issues associated with heterogeneous BWANs (i.e. handovers, network selection, and base station placement), and also the various resource allocation schemes (i.e. shared resource allocation in split handover and inter-RAT self-organizing networks) that can improve the performance of the system by maximizing the capacity of users.


2009 ◽  
Vol 21 (8) ◽  
pp. 534-536 ◽  
Author(s):  
E. Wong ◽  
A.G. Prasanna ◽  
C. Lim ◽  
Ka Lun Lee ◽  
A. Nirmalathas

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Peng Du ◽  
Yuan Zhang

This paper studies the base stations deployment problem in orthogonal frequency-division multiple access (OFDMA) based private wireless access networks for smart grid (SG). Firstly, we analyze the differences between private wireless access networks for SG and public cellular access networks. Then, we propose scheduling and power control based algorithms for the radio resource allocation subproblem and K-means, simulated annealing (SA), and particle swarm optimization (PSO) based algorithms for the base station (BS) location selection subproblem and iterate over these two sets of algorithms to solve the target problem. Simulation results show that the proposed method can effectively solve the target problem. Specifically, the combination of power control based resource allocation algorithm and PSO based location selection algorithm is recommended.


Author(s):  
Rongrong Qian ◽  
Yuan Qi

“Economies of scale” (called scale effect for notational convenience in this work), as a long run concept in microeconomics, refers to reductions in unit cost as the size of a facility and the usage levels of other inputs increase (Wikipedia, 2013). This chapter applies the concept of scale effect in microeconomics to the studies of algorithmic complexity within which the scale effect can be defined as the feature that the unit complexity (i.e., complexity per instance) of the algorithm decreases as the number of instances of algorithm increases while maintaining the performance. In this chapter, the Early-Termination Fixed-Complexity Sphere Detector (ET-FSD) is developed to exploit scale effect for the multiple-antenna system, which has to detect signals of multiple users under the constraint of sum complexity (e.g., the base-station systems always encounter the run-time limit of signal detection of all the users). Based on the study of ET-FSD, future directions of scale effect research for algorithmic complexity issues appearing in wireless access networks are presented as well.


2020 ◽  
pp. 1-1
Author(s):  
Min-Yu Huang ◽  
You-Wei Chen ◽  
Run-Kai Shiu ◽  
Hua Wang ◽  
Gee-Kung Chang

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