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POWER CONTROL AND ASYMPTOTIC THROUGHPUT ANALYSIS FOR THE DISTRIBUTED COGNITIVE UPLINK
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POWER CONTROL AND ASYMPTOTIC THROUGHPUT ANALYSIS FOR THE DISTRIBUTED COGNITIVE UPLINK

Category : Communication


Sub Category : CRN


Project Code : ITCM15


Project Abstract

This paper studies optimum power control and sum rate scaling laws for the distributed cognitive uplink. It is first shown that the optimum distributed power control policy is in the form of a threshold based water-filling power control. Each secondary user executes the derived power control policy in a distributed fashion by using local knowledge of its direct and interference channel gains such that the resulting aggregate (average) interference does not disrupt primary’s communication. Then, the tight sum-rate scaling laws are derived as a function of the number of secondary users N under the optimum distributed power control policy. The fading models considered to derive sum-rate scaling laws are general enough to include Rayleigh, Rician and Nakagami fading models as special cases. When transmissions of secondary users are limited by both transmission and interference power constraints, it is shown that the secondary network sum-rate scales according to 1/ enh log log (N), where nh is a parameter obtained from the distribution of direct channel power gains. For the case of transmissions limited only by interference constraints, on the other hand, the secondary network sum-rate scales according to   1 /eγg log (N), where γg is a parameter obtained from the distribution of interference channel power gains. These results indicate that the distributed cognitive uplink is able to achieve throughput scaling behavior similar to that of the centralized cognitive uplink up to a pre-log multiplier 1/ e , whilst primary’s quality-of-service requirements are met. The factor 1/ e can be interpreted as the cost of distributed implementation of the cognitive uplink.

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT

Cognitive radio technology has recently emerged as an aspirant solution for the problem of spectrum scarcity.  

Unlike the traditional static command-and-control approach, it provides a more dynamic means for spectrum management and utilization. more specifically, cognitive radio protocols such as those in ieee 802.22 allow the cognitive users, alternatively called secondary users (sus), to dynamically share the underutilized frequency bands with primary users (pus) both in time and space under various forms of primary quality-of-service (qos) protections.

 

PROPOSED CONCEPT

      It also investigates multiuser diversity gains for the distributed cognitive uplink by deriving tight sum-rate capacity scaling laws under the optimum distributed power control mechanisms.

       In the centralized uplink, the secondary base-station (SBS) is primarily responsible for the power control task. That is, it first acquires global knowledge of direct (from SUs to the SBS) and interference (from SUs to PUs) channel gains via a feedback mechanism, and then exploits this knowledge to obtain the optimum transmission power level for each SU by respecting primary QoS requirements. Finally, the allocated transmission power levels are broadcasted to SUs by the SBS at each fading block.

ALGORITHM / TECHNIQUE

     Centralized band manager or perfect instantaneous CSI feedback between primary and secondary networks.

ALGORITHM / TECHNIQUE

    Optimum Power Control And Throughput Scaling In (DTPIL) Networks

 

DRAWBACKS

 

Ø  Performance of the capacity (throughput)         is low.

Ø  Sensitivity to noise.

ADVANTAGES

 

      Performance of the capacity (throughput)  rate is high

     Noise  is less


 
 
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