Fuzzy Modeling of Uplink Transmit Power Control in a CDMA Network

From its beginning, transmit power has always placed a significant constraint on the performance of wireless radio systems. The transmit power control problem can be characterized as that of maintaining adequate power in each transmitted waveform so as to increase the expectation that the minimum required SIR at the receiver will at least be reached. This has been shown not to be a trivial endeavor due to the variability of the physical channel with time as well as interference and other practical constraints on “infinitely” increasing transmit power. Several power control algorithms have been proposed, of which the class of distributed and autonomous transmit power control algorithms have been shown in literature to perform quite satisfactorily when compared to centralized schemes due to the moderate complexity that is achievable; and the vast control and signaling overhead that is saved. This thesis work explores the application of fuzzy control to the subject of modeling uplink transmit power control in code division multiple access system…


CHAPTER 1: Introduction
1.1 Background
1.2 Problem formulation
1.3 Thesis outline
CHAPTER 2: The mobile cellular Environment
2.1 The mobile radio propagation environment
2.2 The mobile cellular radio propagation environnent
CHAPTER 3: Radio Resource Management (RRM)
3.1 Radio resource management (RRM) problems in cellular mobile radio environment
3.2 Overview of radio resource management strategies in literature
3.2.1 Channel allocation
3.2.2 Handoff and handoff priority
3.2.3 Transmit power control
3.3 Power control as a mechanism for providing differentiated QoS
CHAPTER 4: Fuzzy set and System
4.1 Some background
4.2 Fuzzy set theory
4.2.1 Fuzzy operations
4.2.2 Fuzzy aggregation
4.2.3 Linguistic variables and fuzzy connectives
4.3 Fuzzy control
4.3.1 Step 1 – Select linguistic states
4.3.2 Step 2 – Fuzzify input
4.3.3 Step 3 – Formulate inference rules
4.3.4 Step 4 – Determine the fuzzy implication
4.3.5 Step 5 – Defuzzify output
4.4 Fuzzy PI control
CHAPTER 5: Proposed simulation scenario
5.1 A TPC framework
5.2 System model
5.3 Conclusions and future work

Author: Victor Uzoechi, Kenneth Osigwe

Source: Blekinge Institute of Technology

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