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May 4, 20151 Mobile Computing COE 446 Network Planning Tarek Sheltami KFUPM CCSE COE Principles of Wireless.

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Presentation on theme: "May 4, 20151 Mobile Computing COE 446 Network Planning Tarek Sheltami KFUPM CCSE COE Principles of Wireless."— Presentation transcript:

1 May 4, Mobile Computing COE 446 Network Planning Tarek Sheltami KFUPM CCSE COE Principles of Wireless Networks K. Pahlavan and P. Krishnamurth

2 May 4, Outline  Channel Allocation Techniques and Capacity Expansion  Fixed Channel Allocation (FCA)  Channel Borrowing Techniques  Selecting Free Channels  Dynamic Channel Allocation (DCA)  Cell-based techniques  Interference-based techniques  Comparison between FCA and DCA

3 May 4, Change the frequency allocation methodology  Channel Allocation Techniques and Capacity Expansion 1. Fixed Channel Allocation (FCA)  Divide the available spectrum by the cluster size to determine the number of radio channels per cell  N c = W/B, C c = N c /N  C c is then distributed in the cells in a manner to minimize the adjacent channel interference  In FDMA each radio channel corresponds to one user  TDMA and CDMA, each radio channel carries several time slots or codes associated with voice channels

4 May 4, Change the frequency allocation methodology.. Fixed Channel Allocation (FCA)  Simple to implement if the traffic is uniform  In practice traffic changes with time due to the movement of MT  high probability of call blocking in some cells and poor utilization of the available BW

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7 7  For a uniform distribution of the traffic, the calculated probability of blockage for each cell is 2%  If the traffic becomes non-uniform, the blockage rate will be changed and over all the average will not remain 2%  Our goal is to increase the number of channels in cells with the higher traffic load and decrease it in cells with lower traffic load so that overall blockage rate of the network is minimized  The number of channels per cell and the cost function to be minimized is the probability of call blocking  The minimization process is far complex than uniformly distributed traffic case  The optimization problem is now a function of N c variables and, in addition, the regular frequency reuse pattern for FCA can not be used Change the frequency allocation methodology..

8 May 4,  Channel Borrowing Techniques  High-traffic cells borrow channels from low-traffic cells  Temporarychannel borrowingStaticchannel borrowing  Temporary channel borrowing and Static channel borrowing  Temporary channel borrowing  Temporary channel borrowing, high traffic cells return the borrowed channels after the call is completed  Static channel borrowing  Static channel borrowing, channels are distributed among cells according to the available statistics of the traffic and changed in a predictive manner Change the frequency allocation methodology..

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11 May 4,  Selecting Free Channels 1. Simple Borrowing Schemes  All the channels are available for borrowing  Better under light or moderate traffic loads 2. Hybrid borrowing scheme  Channels are partitioned, some of them can be borrowed and other can not be borrowed  Some of the suggested borrowing techniques are found to be capable of supporting up to 35% more traffic than uniformly distributed FCA  Channels require additional computational complexity and frequent switching of channels Change the frequency allocation methodology..

12 May 4,  Dynamic Channel Allocation (DCA)  Channels are placed in a pool and they are assigned to a new call according to the overall S r in all cells  Each channel can be used in any cell as long as it satisfies S r requirement for the system  The channel is returned to the pool after the cellular call is terminated  According to some simulations, the capacity is maximized when S r of every set of cochannels users is balanced around some level that is no larger than necessary  The downsize of this scheme, it is extremely complex and inefficient under high-traffic load conditions Change the frequency allocation methodology..

13 May 4,  Dynamic Channel Allocation (DCA)  Microcellular systems of high-density personal communication networks have been shown to benefit the most out of the DCA (simulation)  The cost function quantitatively ranks the available channels based on the overall interference average probability of call-blockage or parameters that somehow related to there quantities  Cost function determine the appropriateness of the channel to be selected  The difference in DCA techniques lies in the selection and optimization of this cost function  Two DCA schemes: Centralize and Distributed schemes Change the frequency allocation methodology..

14 May 4,  Dynamic Channel Allocation (DCA)  Centralized DCA, a central pool all channels exists  Distributed DCA are considered for microcellular systems where channel propagation is less predictable and traffic is denser  Distributed DCA are divided into two classes: Cell-based techniques and interference-based techniques  Cell-based techniques :  Each BS maintains and assigns the channel to the users in its cell  Cell-based techniques is very efficient, but the expense incurred additional inter-BS communication  increases the traffic in the cell Change the frequency allocation methodology..

15 May 4,  Dynamic Channel Allocation (DCA)  Interference-based techniques:  Each BS makes the channel assignment based on the RSS of the mobile in its vicinity  All channels are available to the BS and the BS makes its decision based on the local information without any need to communicate with other BSs  These schemes are self-organized, simple, efficient and fast but they suffer from additional unwanted cochannel interference which may result in channel interruption and network instability Change the frequency allocation methodology..

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