Title
Maximizing The Throughput Guarantees In Wireless Networks Under Imperfect Channel Knowledge
Abstract
In our earlier work, we described an optimization problem and corresponding scheduling algorithm aimed at obtaining maximum throughput guarantees in wireless networks. To further improve the short-term performance, we also proposed two adaptive versions of the optimal algorithm. Results from the simulations showed that the adaptive algorithms perform significantly better than other well-known scheduling algorithms in networks based on Mobile WiMAX, HSDPA, LTE and WINNER I. However, there were several idealistic assumptions in that analysis, the most important of which is that each user estimates its carrier-to-noise ratio (CNR) perfectly, and there is no feedback delay. In practice however, the channel estimation is not perfect, and there is always some delay in the feedback channel. In this paper, we assume that a maximum a posteriori (MAP) predictor is employed for the CNR, so that the system takes the feedback delay and the channel noise into account. We then investigate the effect of imperfect channel prediction and delay on the throughput guarantees promised to all the users in the wireless network. A procedure to reduce the probability of outage in case of imperfect channel prediction is also proposed.
Year
DOI
Venue
2012
10.1109/WCNC.2012.6214163
2012 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC)
Keywords
Field
DocType
maximum a posteriori,scheduling algorithms,mobile communication,optimization problem,wireless network,carrier to noise ratio,optimization,maximum likelihood estimation,hsdpa,scheduling,wireless networks,scheduling algorithm,lte,throughput,wimax
Wireless network,Computer science,Scheduling (computing),Carrier-to-noise ratio,Communication channel,Computer network,WiMAX,Maximum a posteriori estimation,Throughput,Optimization problem
Conference
ISSN
Citations 
PageRank 
1525-3511
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Jawad Rasool1272.00
Geir E. Øien238143.38