5 research outputs found
Optimising BFWA networks
Get PDFBroadband Fixed Wireless Access (BFWA) networks are an attractive
alternative to cable-based technologies, in offering low-cost, high-speed data
services, telephony and video-on-demand to residential and business users.
However, in order to compete successfully with available alternative
telecommunications solutions, the planning and design of efficient networks
is crucial.
This thesis presents two tools that enable the planning and evaluation of
BFWA networks. AgentOpt is a network design and optimisation tool. A
detailed account of the novel scheme, using the principles of emergent, selforganising
systems, which AgentOpt employs for finding profit-optimal
networks is given. The use of two distinct types of agent entity allows the
multi-objective profit/coverage nature of the network planning problem to be
satisfied. AgentOpt networks are compared with designs produced by other
methods to establish to what extent this decentralised agent approach can
optimise BFWA networks.
The Network Validation Tool (NVT) analyses the network designs produced
by AgentOpt and other automatic cell planning tools (ACPs). This is achieved
through simulating the subscription take-up of the potential users in the
network. By repetition of this process, statistical data about the various design
configurations of the network is produced. This allows a planning engineer to
compare and contrast network solutions that may differ in design but perform
similarly in terms of expected profit. In this work the NVT is used to
formulate some general guidelines about the best-practice use of ACPs
Optimisation of BFWA Networks using Emergent Intelligence
No full textThis paper presents a detailed account of a novel scheme for finding profit optimal BFWA networks, extending an existing network optimisation tool, and using the principles of emergent, self-organising systems. We describe how populations of agents representing potential users and base sites will disseminate and react to `local' information to optimise global objectives. The use of two distinct types of agent entity allows the multi-objective profit/coverage nature of the optimisation to be satisfied. Preliminary results are presented to indicate the potential of the scheme
