APPLICATION OF HEURISTIC LEARNING SPECTRUM SENSING IN COGNITIVE RADIO NETWORK
- 주제(키워드) COGNITIVE RADIO , SPECTRUM SENSING , LEARNING
- 발행기관 아주대학교
- 지도교수 YOUNG-JUNE CHOI
- 발행년도 2020
- 학위수여년월 2020. 2
- 학위명 석사
- 학과 및 전공 일반대학원 컴퓨터공학과
- 실제URI http://www.dcollection.net/handler/ajou/000000029933
- 본문언어 영어
- 저작권 아주대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
The cognitive radio is proposed to address the problem of spectrum scarcity in the current condition where the utilization of the spectrums is imbalance. The users in overutilized spectrum may access the other licensed spectrum opportunistically without causing harmful interference to the licensed user. To reduce the interference harmfulness, the unlicensed users have to detect the presence of the licensed user which is called spectrum sensing process. There are many problems in spectrum sensing process. Many works have been done to address the energy consumption problem and also increase the detection performance. There are several works have been done by using heuristic approach and also learning approach. Heuristic approaches mostly suffer from unoptimized results where the learning approaches suffer from long learning time and also the needed for prediction data. In this work, we propose the combination of prediction and heuristic approach where the users learn when to use the proper approach to increase the detection performance and also reduce the energy consumption.
more목차
CHAPTER I. INTRODUCTION 1
A. COGNITIVE RADIO NETWORK 1
B. MOTIVATION 2
C. SPECTRUM SENSING 3
D. CONTRIBUTIONS AND OUTLINES 5
CHAPTER II. BACKGROUND DISCUSSION 7
A. RELATED WORKS 7
B. FRAME STRUCTURE 9
C. PRIMARY USER MODEL 12
D. SPECTRUM SENSING: ENERGY DETECTION (ED) 14
E. PREDICTION MODEL 15
CHAPTER III. HEURISTIC LEARNING SPECTRUM SENSING 18
A. SYSTEM MODEL 18
B. MAIN IDEA 19
C. PREDICTION RELIABILITY VALUE (PRV) 21
D. UPDATING PREDICTION DATA 23
E. ERROR ON UPDATING DATA AND PRV 24
CHAPTER IV. DISCUSSION AND RESULT 25
A. SIMULATION 25
B. RESULT 26
CHAPTER V. CONCLUSION AND FUTURE WORK 34
A. CONCLUSION 34
B. FUTURE WORK 34