Friday, January 20, 2012

Automatic and Optimized Cell-Mesh Planning in WiMAX RESULTS



Our goal is to define the best conditions to cover rural remote users by the usage of PMP and multihop topologies. We defined four scenarios with different population density and topographical condition. We also defined three different set of values for traffic requirements classified as low, medium, and high requirements, presented in Table 1. Finally, we included in the results PMP, relay, and mesh topologies.
Table 1: Traffic Parameters for Different Requirements 
Traffic Requirements
Rgranted
Rvoice
Rbe
ρ
Low
20,000
24,000
10,000
0.025 Erl
Medium
60,000
24,000
40,000
0.025 Erl
High
120,000
24,000
80,000
0.050 Erl
We use the following metrics to deeply analyze the performance of the solutions found by the optimization algorithm and compare the different topologies considered.
  • Image from book as previously defined.
  • The ratio between the number of connected users and the number of used base stations (|Cu|/|Bu|). This is the value Image from book previously defined before normalization.
  • Average frame occupancy percentage: This variable determines how much of the frame is occupied on every base station. This variable is important to measure if a multi-point solution can improve a PMP solution.
  • Equivalent modulation and coding schema: In WiMAX standard [22], there are several levels of transmission profiles defined, ranging from 1/2 BPSK to 3/4 64QAM. Every transmission profile is defined by the coding factor and the modulation factor. We define a quantity by the product of these two values, equivalent to the amount of bits that are sent within one QAM symbol into an OFDM symbol. The lowest value is 0.5 and the higher value is 4.5. We calculate the average value for all the users connected to every base station. An average value near 4.5 means that the solution has a high spectrum efficiency, equivalent to say that all users have the best link conditions possible.
In Figure 1, we present a solution for the low population density and flat terrain scenario with PMP topology. Dark triangles represent sites location. Each antenna in every site is represented by its radiation pattern with a black line indicating its orientation. The connection from users to base stations is represented by a solid line with the same color of the radiation pattern. Information text near the base station indicates the site index, the frame occupancy percentage, and the base station transmission power. In Figure 2 we present a mesh topology solution for the same terrain shown in Figure 1. Every site includes all the base stations that were used on the PMP solution. The information about each site is the site index and the average frame occupancy percentage of all base stations used. Gray curves represent terrain heights.

 
Figure 1: Example solution for a PMP topology.

 
Figure 2: Example solution for a mesh topology.
In the following we discuss the behavior of each one of the performance metrics with respect to the number of sites. We focus then on the number of users that can connect to the system as a function of traffic requirements and the terrain characteristics for all three topologies. We finally discuss the optimization objective function. We found interesting to split multihop solutions into relay and mesh, because when the mesh solution performs near the relay solution, it means that the relay solution as proposed in study group IEEE 802.16j  could be enough over a full mesh solution.
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