무선 중계 네트워크에서 신호대잡음비의 누적분포함수 기반 중계기 선택 기법의 성능 분석

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 이재홍.무선 중계 기술은 차세대 무선통신 시스템에서 요구되는 높은 서비스 품질 및 데이터 전송률 달성을 위해 고려되고 있는 대표적인 기술 중 하나이다. 무선 중계 기술이 갖고 있는 다양한 장점으로 인해 현재까지 IEEE 802.16j 및 3GPP LTE-Advanced 등의 무선통신 시스템 표준에 반영되기도 하였다. 실질적으로 두 노드 사이 채널의 통계적 특성은 그들의 위치에 따라 달라지기 때문에 각 채널들의 통계적 특성은 서로 동일하지 않다. 각 채널들의 통계적 특성이 동일하지 않을 때, 무선 중계 기술에서 가장 유용한 기법 중 하나인 중계기 선택 기법은 특정 중계기들이 더 자주 선택되는 등의 공정성 문제를 유발시킬 수 있다. 특히, 이 문제는 제한된 배터리를 가진 중계기들로 구성된 네트워크에서 네트워크의 수명을 줄이게 하는 요인이 될 수 있다. 따라서 이러한 네트워크에서는 사용자들의 통신 신뢰도 뿐만 아니라, 중계기에서의 선택 공정성도 함께 고려할 필요가 있다. 본 논문에서는 무선 중계 네트워크에서 사용자들의 통신 신뢰도와 중계기 간의 선택 공정성을 함께 고려하기 위해 수신 신호대잡음비의 누적분포함수를 기반으로 하는 새로운 중계기 선택 기법을 제안한다. 주요한 연구 결과는 다음과 같다. 먼저, 나카가미-m 페이딩 채널 환경을 가진 일방향 중계 네트워크를 위한 프로액티브(proactive) 및 리액티브(reactive) 방식의 수신 신호대잡음비 누적분포함수 기반 중계기 선택 기법을 제안한다. 각각의 중계기 선택 기법을 위해 중계기 선택 확률을 유도하여 제안된 각 중계기 선택 기법들의 평균 중계기 공정성을 분석한다. 또한 각 선택 기법에 대한 불능 확률을 수식으로 유도하고, 유도한 불능 확률을 점근적 표현으로 나타내어 각 기법들이 얻을 수 있는 다이버시티 차수를 분석한다. 모의실험을 통해 얻어진 평균 중계기 공정성과 불능 확률이 유도한 평균 중계기 공정성 및 불능 확률 값과 일치함을 확인한다. 그리고 제안된 기법이 중계기들 사이에 공정성을 완벽하게 보장하고 네트워크 수명을 증가시키며, 다이버시티 차수가 중계기의 수와 페이딩 파라미터 m 값에 따라 달라짐을 확인한다. 둘째, 나카가미-m 페이딩 채널 환경을 가진 양방향 중계 네트워크를 위한 프로액티브 및 리액티브 방식의 수신 신호대잡음비 누적분포함수 기반 중계기 선택 기법을 제안한다. 제안된 프로액티브 방식의 중계기 선택 기법에 대해서는 정확한 중계기 선택 확률의 유도를 통해 평균 중계기 공정성을 분석한다. 제안된 리액티브 방식의 중계기 선택 기법에 대해서는 중계기 선택 확률의 적분 및 근사 표현을 유도하여 평균 중계기 공정성을 분석한다. 또한 각 선택 기법에 대한 불능 확률을 수식으로 유도하고, 유도한 불능 확률을 점근적 표현으로 나타내어 각 기법들이 얻을 수 있는 다이버시티 차수를 분석한다. 모의실험을 통해 얻어진 평균 중계기 공정성과 불능 확률이 유도한 평균 중계기 공정성 및 불능 확률 값과 일치함을 확인한다. 그리고 제안된 기법이 중계기들 사이에 공정성을 완벽하게 보장하고 네트워크 수명을 증가시키며, 다이버시티 차수가 중계기의 수와 페이딩 파라미터 m 값에 따라 달라짐을 확인한다.Wireless relay technology is one of the most promising technologies for the future communication systems which provide coverage extension and better quality of service (QoS) such as higher data rate and lower outage probability with few excessive network loads. Due to its advantages, it has been adopted in wireless standards such as IEEE 802.16j and 3GPP LTE-Advanced. In practice, since statistics of the channel between any two nodes vary depending on their locations, they are not identical which means that channels can experience different fading. When statistics of the channel are not identical, relay selection, which is one of the most useful techniques for wireless relay technology, can cause fairness problem that particular relays are selected more frequently than other relays. Especially, this problem can cause reduction of lifetime in the network with multiple relays having limited battery power. In this network, it is needed to focus on selection fairness for relays as well as reliability at end-users. In this dissertation, to focus on both selection fairness for relays and reliability at end-users, we propose novel relay selection schemes based on cumulative distribution functions (CDFs) of signal-to-noise ratios (SNRs) in wireless relay networks. The dissertation consists of two main results. First, we propose the proactive and the reactive relay selection schemes based on CDFs of SNRs for one-way relay networks over Nakagami-m fading channels. If a relay is selected before the source transmission, it is called as proactive relay selection. Otherwise, if a relay is selected after the source transmission, it is called as reactive relay selection. For both the proactive and the reactive relay selection schemes, we analyze average relay fairness by deriving relay selection probability. For the proactive relay selection scheme, we obtain diversity order by deriving the integral and asymptotic expressions for outage probability. Also, for the reactive relay selection scheme, we obtain diversity order by deriving the exact closed-form and asymptotic expressions for outage probability. Numerical results show that the analytical results of the proposed schemes match the simulation results well. It is shown that the proposed schemes guarantee strict fairness among relays and extend network lifetime. Also, it is shown that diversity order depends on the number of relays and fading severity parameters. Second, we propose the proactive and the reactive relay selection schemes based on CDFs of SNRs for two-way relay networks over Nakagami-m fading channels. For the proactive relay selection scheme, we analyze average relay fairness by deriving relay selection probability. Also, we analyze diversity order by deriving the integral and asymptotic expressions for outage probability. For the reactive relay selection scheme, we analyze average relay fairness by deriving the integral and asymptotic expressions for relay selection probability. Also, we obtain diversity order by deriving the asymptotic expression for outage probability. Numerical results show that the analytical results of the proposed schemes match the simulation results well. It is shown that the proposed schemes guarantee strict fairness among relays and extend network lifetime. Also, it is shown that diversity order depends on the number of relays and fading severity parameters.Contents Abstract i 1 Introduction 1 1.1 Background and Related Work . . . . . . . . . . . . . . . . . . . . . 2 1.1.1 Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.1.2 Wireless Relay Technology . . . . . . . . . . . . . . . . . . . . 3 1.2 Outline of Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.3 Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2 Relay Selection Based on CDFs of SNRs for One-Way Relay Networks 14 2.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.1.1 Proactive CDF-Based Relay Selection . . . . . . . . . . . . . 19 2.1.2 Reactive CDF-Based Relay Selection . . . . . . . . . . . . . . 20 2.2 Performance Analysis of Proactive CDF-Based Relay Selection . . . . 22 2.2.1 Average Relay Fairness Analysis . . . . . . . . . . . . . . . . . 22 2.2.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 27 2.3 Performance Analysis of Reactive CDF-Based Relay Selection . . . . 34 2.3.1 Average Relay Fairness Analysis . . . . . . . . . . . . . . . . . 34 2.3.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 36 2.4 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 2.4.1 Average Relay Fairness . . . . . . . . . . . . . . . . . . . . . . 39 2.4.2 Network Lifetime . . . . . . . . . . . . . . . . . . . . . . . . . 48 2.4.3 Outage Probability . . . . . . . . . . . . . . . . . . . . . . . . 53 2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 3 Relay Selection Based on CDFs of SNRs for Two-Way Relay Networks 66 3.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 3.1.1 Proactive CDF-based Relay Selection . . . . . . . . . . . . . . 68 3.1.2 Reactive CDF-based Relay Selection . . . . . . . . . . . . . . 72 3.2 Performance Analysis of Proactive CDF-Based Relay Selection . . . . 73 3.2.1 Average Relay Fairness Analysis . . . . . . . . . . . . . . . . . 73 3.2.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 74 3.3 Performance Analysis of Reactive CDF-Based Relay Selection . . . . 82 3.3.1 Average Relay Fairness Anlaysis . . . . . . . . . . . . . . . . . 82 3.3.2 Outage Probability Analysis . . . . . . . . . . . . . . . . . . . 86 3.4 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 3.4.1 Average Relay Fairness . . . . . . . . . . . . . . . . . . . . . . 89 3.4.2 Network Lifetime . . . . . . . . . . . . . . . . . . . . . . . . . 100 3.4.3 Outage Probability . . . . . . . . . . . . . . . . . . . . . . . . 105 3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 4 Conclusion 116 4.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 4.2 Possible Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 4.2.1 Device-to-Device (D2D) Communications . . . . . . . . . . . 118 4.2.2 Low Power Body Sensor Networks . . . . . . . . . . . . . . . 120 4.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Bibliography 122 Korean Abstract 139Docto

Cooperative Diversity in CDMA over Nakagami−m Fading Channels

Spatial diversity can be employed by sending copies of the transmitted signal using multiple antennas at the transmitter/receiver, as implemented in multiple-input multipleoutput (MIMO) systems. Spatial receive diversity has already been used in many applications with centralized systems where base station receivers are equipped with multiple antennas. However, due to the power constraints and the small size of the mobile terminal, it may not be feasible to deploy multiple transmit antennas. User cooperation diversity, a new form of space diversity, has been developed to address these limitations. Recently, user cooperative diversity has gained more attention as a less complex alternative to centralized MIMO wireless systems. It revealed the ability to improve wireless communications through reliable reception. One common network of the user cooperation diversity is the direct sequence code division multiple access (DS-CDMA) in which the Rayleigh fading channels are adopted and the orthogonality between users is assumed. The Rayleigh fading channels are unrealistic since they cannot represent the statistical characteristics of the complex indoor environments. On the other hand, Nakagami-m fading model is well known as a generalized distribution, where many fading environments can be modeled. It can be used to model fading conditions ranging from severe, light to no fading, by changing its fading parameter m. The bit-error-rate (BER) and outage probability of uplink cooperative DS-CDMA over Nakagami-m has not been addressed in the literature. Thus, in this thesis, the performance of both decode-and-forward (DF) and amplify-and-forward (AF) cooperative asynchronous DS-CDMA system over Nakagami-m fading channels is investigated. The Rake receiver is used to exploit the advantages of multipath propagation. Besides, multiuser detection (MUD) is used to mitigate the effect of multiple-access interference (MAI). We show that our proposed multi-user system achieves the full system diversity gain. The first part of the thesis introduces a new closed-form expression for the outage probability and the error probability of the DF cooperative DS-CDMA over asynchronous transmission over independent non-identical Nakagami-m fading channels. The underlying system employs MUD such as minimum mean square error (MMSE) and decorrelator detector (DD) to achieve the full diversity. The aforementioned closed-form expression is obtained through the moment generating function (MGF) for the total signal-to-noise ratio (SNR) at the base station where the cumulative density function (CDF) is obtained. Furthermore, we investigate the asymptotic behavior of the system at high SNR to calculate the achievable diversity gain. The results demonstrate that the system diversity gain is fulfilled when MUD is used to mitigate the effect of MAI. In the second part of the thesis, we study the performance of cooperative CDMA system using AF relaying over independent non-identical distribution (i.n.i) Nakagami-m fading channels. Using the MGF of the total SNR at the base station, we derive the outage probability of the system. This enables us to derive the asymptotic outage probability for any arbitrary value of the fading parameter m. The last part of the thesis investigates the optimum power allocation and optimum relay location in AF cooperative CDMA systems over i.n.i Nakagami-m fading channels. Moreover, we introduce the joint optimization of both power allocation and relay location under the transmit power constraint to minimize the outage probability of the system. The joint optimization of both power allocation and relay location is used to minimize the outage performance of the system, thereby achieving full diversity gain