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Modelling and planning fixed wireless networks

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Abstract

This paper describes a mathematical model for the automated design of fixed wireless access networks (FWA) through the automatic selection and configuration of base station sites. An optimisation algorithm is presented which generates the fixed wireless access network infrastructure design, and results are presented to illustrate the use of the model and its implementation. Economic measures based on the net present value (NPV) are defined to assess the financial viability of potential network designs. The NPV is used within the mathematical optimization framework to produce cost-effective deployments that maximize economic performance while maintaining technical constraints on the network. The model takes into account time-varying input parameters on CapEx, OpEx, revenues and subscriber requirements to model the dynamic nature of the market. Technical radio constraints taken into account include downlink area coverage, interference, capacity and availability. The model and optimisation framework are illustrated by considering the deployment and configuration of infrastructure for three scenarios representing urban, suburban and rural regions. Experiments illustrating the staged deployment of infrastructure over a number of time periods are also presented.

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Notes

  1. The costs are represented purely as floating point numbers, and hence no specific currency is implied. All input costs should be in a similar currency basis, and all NPV-based outputs will immediately be in this form.

  2. Usually these periods would be years, but there is no specific restriction for this to be the case within the model.

  3. It is assumed that no time dependence exists on infrastructure settings i.e. a sector’s settings remain fixed once deployed. Time dependent settings could be included at the expense of more complex modelling.

  4. The datasets, full results, graphics and the system (executables and input project files) can be downloaded from www.cs.cf.ac.uk/User/Steve.Hurley/fwa.

  5. Costs provided by Norwegian mobile communications operator Telenor.

  6. WiMAX forum report: http://www.wimaxforum.org/technology/downloads/WiMAX-The_Business_Case-Rev3.pdf.

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Acknowledgements

The authors are grateful to Telenor ASA, Norway for providing radio and economic data relating to the Oslo scenario and to the Radio Communications Research Unit at the Rutherford Appleton Laboratory in the UK for providing the propagation path-loss data for all the datasets used.

Author information

Authors and Affiliations

  1. School of Computer Science, Cardiff University, 5 The Parade, Cardiff, CF24 3AA, UK

    Stephen Hurley, Stuart Allen & Richard Taplin

  2. Department of Computer Science, Sheffield University, Regent Court, 211 Portobello Street, Sheffield, S1 4DP, UK

    Desmond Ryan

Authors
  1. Stephen Hurley
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  2. Stuart Allen
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  3. Desmond Ryan
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  4. Richard Taplin
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Corresponding author

Correspondence to Stephen Hurley.

Appendices

Appendix 1: Stage 2 optimization modifiers

  • Add Channel to Random Sector—adds a random channel to a random sector, unless the sector has its full channel allocation.

  • Add Enough Channels to Overloaded Sector—adds channels to a randomly chosen overloaded sector until either the sector is no longer overloaded or the maximum number of channels is reached.

  • Add Optimal Sector—adds a sector at the site that is closest to the centre of mass of the uncovered users. The new sector is given maximum power, and the azimuth adjusted to maximise network coverage, the sector is then tested with all antenna types for maximum coverage.

  • Add Random Sector with Re-assignment—adds a sector at a random site using default antenna and polarisation. It also adds one channel and sets the azimuth to a random value. The modifier then loops over all users and reassigns to the new sector if it is the strongest sector.

  • Best Sector for all Users—this loops over all users and finds the strongest signal sector for each, the user is then reassigned if necessary.

  • Best Sector for Failing Users—similar to above but applies only to not served users.

  • Change Channel for Random Sector—changes one of the channels in use at a random sector.

  • Delete Channel from Random Sector—removes a randomly chosen channel from a random sector.

  • Move All Sectors at Random Site—at a random site, move all its sectors to a different randomly chosen site, each sector’s parameters are preserved.

  • Random Antenna for a Random Sector—at a random site change the antenna to a random one from the antenna list.

  • Random Bearing for a Random Sector—at a random sector change the azimuth to a random value from 0 to 359.

  • Random RTP for All Users—this changes the employed RTP for all users. For each user u the employed RTP is randomly selected from S(u).

  • Remove Lowest Revenue Sector—this finds the sector that is contributing the least income to the network and removes it.

Stage 3 optimisation modifiers

  • In addition to the Stage 2 modifiers the following are also available:

  • Add Random Sector—adds a sector at a random site. A random antenna is used pointing North with a tilt of zero, one channel is added.

  • Add Sector at Overloaded Site—this adds a sector at a site with overloaded sectors. The sector has a random azimuth and each user which is not served is assigned to the new sector.

  • Best Bearing for a Random Sector—for a random sector check all azimuth values and select the one which maximises NPV.

  • Best Power for a Random Sector—as above but check all power values.

  • Best Tilt for a Random Sector—as above but check all tilt values.

  • Change Deployment Period for a Random Site—this changes the deployment period for a randomly chosen site, to one from the list of possible deployment periods.

  • Change Server Random User—this selects a random user and assigns it to a randomly selected sector.

  • Join Close Sites –—the first site is chosen randomly, and the second site is the closest occupied site. All sectors at the second site are added to the first site, preserving settings. No user re-assignment takes place.

  • Move Random Sector—this moves a randomly chosen sector to a randomly chosen new site. All users at the original sector are assigned to the new sector, and all sector parameters are preserved.

  • Nudge Bearing Random Sector—this changes the azimuth of a random sector within a small range (e.g. 10°). The azimuth chosen gives the maximum NPV.

  • Nudge Tilt Random Sector—as above but using tilt.

  • Optimal Deployment for all Sites—reassigns the deployment periods for all sites in order to maximize overall NPV. Each site is tested at all periods and the period that has the largest NPV is selected for that site.

  • Optimal User Inclusion for a Random Sector—this checks all the users currently covered by a randomly selected sector and sorts them in order of their bandwidth to income ratio. Those with the lowest ratio (and hence who generate the most income for the lowest amount of bandwidth) are then iteratively re-assigned to the sector until the sector is overloaded.

  • Optimise All User Antennas—this checks all users and for each one select the antenna that maximizes NPV.

  • Random Power for a Random User—selects a random power setting for a random sector.

  • Random Tilt for a Random Sector—as above but selecting tilt.

  • Random Sector for All Users—changes the serving sector for each user to a randomly chosen sector.

  • Reassign Frequencies of a Random Sector—this assists in frequency assignment at a random sector, where all the channels are used no reassignment takes place.

  • Remove Random Sector—randomly selects a sector and removes it together, no reassignment of users take place.

  • Remove Random Site—as above but applies to all sectors at a randomly selected site.

  • Stop Serving Random User—this random de-selection of a user may allow other users at the sector to be served.

A complete description of each modifier can be found online at www.cs.cf.ac.uk/User/Steve.Hurley/fwa.

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Hurley, S., Allen, S., Ryan, D. et al. Modelling and planning fixed wireless networks. Wireless Netw 16, 577–592 (2010). https://doi.org/10.1007/s11276-008-0155-9

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