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IEEE Wireless Communications and Networking Conference 18-21 April 2010, Sydney, Australia. Planning of Relay Station Locations in IEEE 802.16 (WiMAX) Networks. Zakhia Abichar, Ahmed E. Kamal and J. Morris Chang Department of Electrical and Computer Engineering Iowa State University, USA.
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IEEE Wireless Communications and Networking Conference 18-21 April 2010, Sydney, Australia Planning of Relay Station Locations in IEEE 802.16 (WiMAX) Networks Zakhia Abichar, Ahmed E. Kamal and J. Morris Chang Department of Electrical and Computer Engineering Iowa State University, USA
Outline • Introduction • Problem formulation • Optimization • Results
Introduction • IEEE 802.16 (WiMAX) presents an architecture that uses Relay Stations (RS) • One Base Station (BS) might connect to several RSs to extend its range • RSs are cheaper than a BS • They don’t need connection to Internet • They relay data in wireless to BS • Hence, they can be installed in rural or remote areas • RSs are presented in IEEE 802.16j standard (ratified in May 2009) • In this work, we see how to plan the location of RSs
Problem • There is one BS • There is a coverage area • There are multiple users with demands • We need to find the locations of RSs • And the links of the rates
BS RS possible location Test Point (user) Formulation • We use a grid system • Given are BS, RS sites, TP sites and demands (in Mbps) • We need to find: • RS positions • Links used • Rate on each link A planning problem
Optimization • R={1,2,…,n} is the set of relay sites • T={1,2,…,m} is the set of test points (TPs) • Decision Variables When either of the D variables below are 1, we need to find the corresponding link rate, given by f
Topology Constraints • If the link from BS to RSi exists, then RSi should exist • Similarly, when a link between RSi and RSj exists, then RSi and RSj should exist • Also, when a link is assigned between RSi and TPj, then RSi should exist • Finally, a TP is assigned to BS or to one RS only
Flow Constraints • At the BS, the sum of data flow out = the sum of data for all TPs • At the BS: • There is a problem, f and D are decision variables. This is not linear! • We are solving with CPLEX. It requires linear equations • Then, we use transforms: • Solved using Q, a large number: Above equation becomes
Flow Constraints • At an RS, the sum of data flow in = the sum of data flow out • Similarly, we use transforms: • Equation above becomes: • It is solved with: and
Flow Constraints • At the TP, the same of all flows at the TP are equal to its demand: • Using previous transforms, equation above becomes (to make it linear):
Constraint on the Link Capacity • For every link in the grid, there is a maximum rate, m • The assigned rate, f, should be less or equal to m • Subject to physical layer (PHY) rates
Objective Function • Minimize the number of RSs
Numerical Results • The rates are assigned as in the table • We will show solution of planning • We also show planning with obstacles in planning area This table gives the values of m, the maximum rate possible
Solution Method • We solve the problem by CPLEX • a computer program that solves optimization • Since the size of this problem is somehow small, we don’t use approximation algorithm • One BS can support a limited number of RSs • The RSs don’t have internet connection • Thus, if we use a very large number of RS, the performance becomes low • Besides, the planning is done only once
Planning Solution • Number of RSs used: 3 • Flow conservation at every link • All TPs satisfied Planning problem Solution
Obstacles • In real life, there would be obstacles in the planning area • Mountains, lakes, buildings, etc. • We consider two types • Lake-type: cancels RS location, doesn’t cancel trespassing link • Mountain-type: cancels RS location, cancels trespassing link • Mountain-type is more difficult than lake-type
Planning with Lake-type Obstacle • Same TPs demands as before • Lake obstacles introduced • Number of used RSs is 4 • It was 3 with no obstacles • Links passing over lake, but RS in lake
Planning with Mountain-type Obstacle • Same TPs demands as before • Mountain obstacles introduced • Number of used RSs is 5 • It was 4 with lake, and 3 with no obstacles • Links go around the mountain, no RSs on it
Conclusion • We present a solution on how to plan the location of RSs to extend the range of a BS • We formulate the problem by optimization • We show examples on how our solution can be used • We show real-life cases of having obstacles in the planning area • With more obstacles, we need more RSs