4 research outputs found

    Opportunistic Relaying in Time Division Broadcast Protocol with Incremental Relaying

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    In this paper, we investigate the performance of time division broadcast protocol (TDBC) with incremental relaying (IR) when there are multiple available relays. Opportunistic relaying (OR), i.e., the โ€œbestโ€ relay is select for transmission to minimize the systemโ€™s outage probability, is proposed. Two OR schemes are presented. The first scheme, termed TDBC-OIR-I, selects the โ€œbestโ€ relay from the set of relays that can decode both flows of signal from the two sources successfully. The second one, termed TDBC-OIR-II, selects two โ€œbestโ€ relays from two respective sets of relays that can decode successfully each flow of signal. The performance, in terms of outage probability, expected rate (ER), and diversity-multiplexing tradeoff (DMT), of the two schemes are analyzed and compared with two TDBC schemes that have no IR but OR (termed TDBC-OR-I and TDBC-OR-II accordingly) and two other benchmark OR schemes that have no direct link transmission between the two sources

    Performance Analysis, Resource Allocation and Optimization of Cooperative Communication Systems under Generalized Fading Channels

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    The increasing demands for high-speed data transmission, efficient wireless access, high quality of service (QoS) and reliable network coverage with reduced power consumption impose demanding intensive research efforts on the design of novel wireless communication system architectures. A notable development in the area of communication theory is the introduction of cooperative communication systems. These technologies become promising solution for the next-generation wireless transmission systems due to their applicability in size, power, hardware and price constrained devices, such as cellular mobile devices, wireless sensors, ad-hoc networks and military communications, being able to provide, e.g., diversity gain against fading channels without the need for installing multiple antennas in a single terminal. The performance of the cooperative systems can in general be signi๏ฌcantly increased by allocating the limited power efficiently. In this thesis, we address in detail the performance analysis, resource allocation and optimization of such cooperative communication systems under generalized fading channels. We focus ๏ฌrst on energy-efficiency (EE) optimization and optimal power allocation (OPA) of regenerative cooperative network with spatial correlation effects under given power constraint and QoS requirement. The thesis also investigates the end-to-end performance and power allocation of a regenerative multi-relay cooperative network over non-homogeneous scattering environment, which is realistic case in practical wireless communication scenarios. Furthermore, the study investigates the end-to-end performance, OPA and energy optimization analysis under total power constraint and performance requirement of full-duplex (FD) relaying transmission scheme over asymmetric generalized fading models with relay self-interference (SI) effects.The study ๏ฌrst focuses on exact error analysis and EE optimization of regenerative relay systems under spatial correlation effects. It ๏ฌrst derives novel exact and asymptotic expressions for the symbol-error-rates (SERs) of M -ary quadrature amplitude and M -ary phase-shift keying (M -QAM) and (M -PSK) modulations, respectively, assuming a dual-hop decode-and-forward relay system, spatial correlation, path-loss effects and maximum-ratio-combing (MRC) at the destination. Based on this, EEoptimization and OPA are carried out under certain QoS requirement and transmit power constraints.Furthermore, the second part of the study investigates the end-to-end performance and power allocation of MRC based regenerative multi-relay cooperative system over non-homogeneous scattering environment. Novel exact and asymptotic expressions are derived for the end-to-end average SER for M -QAM and M -PSK modulations.The offered results are employed in performance investigations and power allocation formulations under total transmit power constraints.Finally, the thesis investigates outage performance, OPA and energy optimization analysis under certain system constraints for the FD and half-duplex (HD) relaying systems. Unlike the previous studies that considered the scenario of information transmission over symmetric fading conditions, in this study we considered the scenario of information transmission over the most generalized asymmetric fading environments.The obtained results indicate that depending on the severity of multipath fading, the spatial correlation between the direct and relayed paths and the relay location, the direct transmission is more energy-efficient only for rather short transmission distances and until a certain threshold. Beyond this, the system bene๏ฌts substantially from the cooperative transmission approach where the cooperation gain increases as the transmission distance increases. Furthermore, the investigations on the power allocation for the multi-relay system over the generalized small-scale fading model show that substantial performance gain can be achieved by the proposed power allocation scheme over the conventional equal power allocation (EPA) scheme when the source-relay and relay-destination paths are highly unbalanced. Extensive studies on the FD relay system also show that OPA provides signi๏ฌcant performance gain over the EPA scheme when the relay SI level is relatively strong. In addition, it is shown that the FD relaying scheme is more energy-efficient than the reference HD relaying scheme at long transmission distances and for moderate relay SI levels.In general, the investigations in this thesis provide tools, results and useful insights for implementing space-efficient, low-cost and energy-efficient cooperative networks, speci๏ฌcally, towards the future green communication era where the optimization of the scarce resources is critical

    ๋ฌด์„  ์ค‘๊ณ„ ๋„คํŠธ์›Œํฌ์—์„œ ์‹ ํ˜ธ๋Œ€์žก์Œ๋น„์˜ ๋ˆ„์ ๋ถ„ํฌํ•จ์ˆ˜ ๊ธฐ๋ฐ˜ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์˜ ์„ฑ๋Šฅ ๋ถ„์„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2015. 8. ์ด์žฌํ™.๋ฌด์„  ์ค‘๊ณ„ ๊ธฐ์ˆ ์€ ์ฐจ์„ธ๋Œ€ ๋ฌด์„ ํ†ต์‹  ์‹œ์Šคํ…œ์—์„œ ์š”๊ตฌ๋˜๋Š” ๋†’์€ ์„œ๋น„์Šค ํ’ˆ์งˆ ๋ฐ ๋ฐ์ดํ„ฐ ์ „์†ก๋ฅ  ๋‹ฌ์„ฑ์„ ์œ„ํ•ด ๊ณ ๋ ค๋˜๊ณ  ์žˆ๋Š” ๋Œ€ํ‘œ์ ์ธ ๊ธฐ์ˆ  ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ๋ฌด์„  ์ค‘๊ณ„ ๊ธฐ์ˆ ์ด ๊ฐ–๊ณ  ์žˆ๋Š” ๋‹ค์–‘ํ•œ ์žฅ์ ์œผ๋กœ ์ธํ•ด ํ˜„์žฌ๊นŒ์ง€ IEEE 802.16j ๋ฐ 3GPP LTE-Advanced ๋“ฑ์˜ ๋ฌด์„ ํ†ต์‹  ์‹œ์Šคํ…œ ํ‘œ์ค€์— ๋ฐ˜์˜๋˜๊ธฐ๋„ ํ•˜์˜€๋‹ค. ์‹ค์งˆ์ ์œผ๋กœ ๋‘ ๋…ธ๋“œ ์‚ฌ์ด ์ฑ„๋„์˜ ํ†ต๊ณ„์  ํŠน์„ฑ์€ ๊ทธ๋“ค์˜ ์œ„์น˜์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง€๊ธฐ ๋•Œ๋ฌธ์— ๊ฐ ์ฑ„๋„๋“ค์˜ ํ†ต๊ณ„์  ํŠน์„ฑ์€ ์„œ๋กœ ๋™์ผํ•˜์ง€ ์•Š๋‹ค. ๊ฐ ์ฑ„๋„๋“ค์˜ ํ†ต๊ณ„์  ํŠน์„ฑ์ด ๋™์ผํ•˜์ง€ ์•Š์„ ๋•Œ, ๋ฌด์„  ์ค‘๊ณ„ ๊ธฐ์ˆ ์—์„œ ๊ฐ€์žฅ ์œ ์šฉํ•œ ๊ธฐ๋ฒ• ์ค‘ ํ•˜๋‚˜์ธ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์€ ํŠน์ • ์ค‘๊ณ„๊ธฐ๋“ค์ด ๋” ์ž์ฃผ ์„ ํƒ๋˜๋Š” ๋“ฑ์˜ ๊ณต์ •์„ฑ ๋ฌธ์ œ๋ฅผ ์œ ๋ฐœ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ํŠนํžˆ, ์ด ๋ฌธ์ œ๋Š” ์ œํ•œ๋œ ๋ฐฐํ„ฐ๋ฆฌ๋ฅผ ๊ฐ€์ง„ ์ค‘๊ณ„๊ธฐ๋“ค๋กœ ๊ตฌ์„ฑ๋œ ๋„คํŠธ์›Œํฌ์—์„œ ๋„คํŠธ์›Œํฌ์˜ ์ˆ˜๋ช…์„ ์ค„์ด๊ฒŒ ํ•˜๋Š” ์š”์ธ์ด ๋  ์ˆ˜ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ด๋Ÿฌํ•œ ๋„คํŠธ์›Œํฌ์—์„œ๋Š” ์‚ฌ์šฉ์ž๋“ค์˜ ํ†ต์‹  ์‹ ๋ขฐ๋„ ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ์ค‘๊ณ„๊ธฐ์—์„œ์˜ ์„ ํƒ ๊ณต์ •์„ฑ๋„ ํ•จ๊ป˜ ๊ณ ๋ คํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฌด์„  ์ค‘๊ณ„ ๋„คํŠธ์›Œํฌ์—์„œ ์‚ฌ์šฉ์ž๋“ค์˜ ํ†ต์‹  ์‹ ๋ขฐ๋„์™€ ์ค‘๊ณ„๊ธฐ ๊ฐ„์˜ ์„ ํƒ ๊ณต์ •์„ฑ์„ ํ•จ๊ป˜ ๊ณ ๋ คํ•˜๊ธฐ ์œ„ํ•ด ์ˆ˜์‹  ์‹ ํ˜ธ๋Œ€์žก์Œ๋น„์˜ ๋ˆ„์ ๋ถ„ํฌํ•จ์ˆ˜๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ์ƒˆ๋กœ์šด ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ฃผ์š”ํ•œ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ๋จผ์ €, ๋‚˜์นด๊ฐ€๋ฏธ-m ํŽ˜์ด๋”ฉ ์ฑ„๋„ ํ™˜๊ฒฝ์„ ๊ฐ€์ง„ ์ผ๋ฐฉํ–ฅ ์ค‘๊ณ„ ๋„คํŠธ์›Œํฌ๋ฅผ ์œ„ํ•œ ํ”„๋กœ์•กํ‹ฐ๋ธŒ(proactive) ๋ฐ ๋ฆฌ์•กํ‹ฐ๋ธŒ(reactive) ๋ฐฉ์‹์˜ ์ˆ˜์‹  ์‹ ํ˜ธ๋Œ€์žก์Œ๋น„ ๋ˆ„์ ๋ถ„ํฌํ•จ์ˆ˜ ๊ธฐ๋ฐ˜ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๊ฐ๊ฐ์˜ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์„ ์œ„ํ•ด ์ค‘๊ณ„๊ธฐ ์„ ํƒ ํ™•๋ฅ ์„ ์œ ๋„ํ•˜์—ฌ ์ œ์•ˆ๋œ ๊ฐ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•๋“ค์˜ ํ‰๊ท  ์ค‘๊ณ„๊ธฐ ๊ณต์ •์„ฑ์„ ๋ถ„์„ํ•œ๋‹ค. ๋˜ํ•œ ๊ฐ ์„ ํƒ ๊ธฐ๋ฒ•์— ๋Œ€ํ•œ ๋ถˆ๋Šฅ ํ™•๋ฅ ์„ ์ˆ˜์‹์œผ๋กœ ์œ ๋„ํ•˜๊ณ , ์œ ๋„ํ•œ ๋ถˆ๋Šฅ ํ™•๋ฅ ์„ ์ ๊ทผ์  ํ‘œํ˜„์œผ๋กœ ๋‚˜ํƒ€๋‚ด์–ด ๊ฐ ๊ธฐ๋ฒ•๋“ค์ด ์–ป์„ ์ˆ˜ ์žˆ๋Š” ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ๋ชจ์˜์‹คํ—˜์„ ํ†ตํ•ด ์–ป์–ด์ง„ ํ‰๊ท  ์ค‘๊ณ„๊ธฐ ๊ณต์ •์„ฑ๊ณผ ๋ถˆ๋Šฅ ํ™•๋ฅ ์ด ์œ ๋„ํ•œ ํ‰๊ท  ์ค‘๊ณ„๊ธฐ ๊ณต์ •์„ฑ ๋ฐ ๋ถˆ๋Šฅ ํ™•๋ฅ  ๊ฐ’๊ณผ ์ผ์น˜ํ•จ์„ ํ™•์ธํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์ด ์ค‘๊ณ„๊ธฐ๋“ค ์‚ฌ์ด์— ๊ณต์ •์„ฑ์„ ์™„๋ฒฝํ•˜๊ฒŒ ๋ณด์žฅํ•˜๊ณ  ๋„คํŠธ์›Œํฌ ์ˆ˜๋ช…์„ ์ฆ๊ฐ€์‹œํ‚ค๋ฉฐ, ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜๊ฐ€ ์ค‘๊ณ„๊ธฐ์˜ ์ˆ˜์™€ ํŽ˜์ด๋”ฉ ํŒŒ๋ผ๋ฏธํ„ฐ m ๊ฐ’์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง์„ ํ™•์ธํ•œ๋‹ค. ๋‘˜์งธ, ๋‚˜์นด๊ฐ€๋ฏธ-m ํŽ˜์ด๋”ฉ ์ฑ„๋„ ํ™˜๊ฒฝ์„ ๊ฐ€์ง„ ์–‘๋ฐฉํ–ฅ ์ค‘๊ณ„ ๋„คํŠธ์›Œํฌ๋ฅผ ์œ„ํ•œ ํ”„๋กœ์•กํ‹ฐ๋ธŒ ๋ฐ ๋ฆฌ์•กํ‹ฐ๋ธŒ ๋ฐฉ์‹์˜ ์ˆ˜์‹  ์‹ ํ˜ธ๋Œ€์žก์Œ๋น„ ๋ˆ„์ ๋ถ„ํฌํ•จ์ˆ˜ ๊ธฐ๋ฐ˜ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆ๋œ ํ”„๋กœ์•กํ‹ฐ๋ธŒ ๋ฐฉ์‹์˜ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์— ๋Œ€ํ•ด์„œ๋Š” ์ •ํ™•ํ•œ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ํ™•๋ฅ ์˜ ์œ ๋„๋ฅผ ํ†ตํ•ด ํ‰๊ท  ์ค‘๊ณ„๊ธฐ ๊ณต์ •์„ฑ์„ ๋ถ„์„ํ•œ๋‹ค. ์ œ์•ˆ๋œ ๋ฆฌ์•กํ‹ฐ๋ธŒ ๋ฐฉ์‹์˜ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์— ๋Œ€ํ•ด์„œ๋Š” ์ค‘๊ณ„๊ธฐ ์„ ํƒ ํ™•๋ฅ ์˜ ์ ๋ถ„ ๋ฐ ๊ทผ์‚ฌ ํ‘œํ˜„์„ ์œ ๋„ํ•˜์—ฌ ํ‰๊ท  ์ค‘๊ณ„๊ธฐ ๊ณต์ •์„ฑ์„ ๋ถ„์„ํ•œ๋‹ค. ๋˜ํ•œ ๊ฐ ์„ ํƒ ๊ธฐ๋ฒ•์— ๋Œ€ํ•œ ๋ถˆ๋Šฅ ํ™•๋ฅ ์„ ์ˆ˜์‹์œผ๋กœ ์œ ๋„ํ•˜๊ณ , ์œ ๋„ํ•œ ๋ถˆ๋Šฅ ํ™•๋ฅ ์„ ์ ๊ทผ์  ํ‘œํ˜„์œผ๋กœ ๋‚˜ํƒ€๋‚ด์–ด ๊ฐ ๊ธฐ๋ฒ•๋“ค์ด ์–ป์„ ์ˆ˜ ์žˆ๋Š” ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜๋ฅผ ๋ถ„์„ํ•œ๋‹ค. ๋ชจ์˜์‹คํ—˜์„ ํ†ตํ•ด ์–ป์–ด์ง„ ํ‰๊ท  ์ค‘๊ณ„๊ธฐ ๊ณต์ •์„ฑ๊ณผ ๋ถˆ๋Šฅ ํ™•๋ฅ ์ด ์œ ๋„ํ•œ ํ‰๊ท  ์ค‘๊ณ„๊ธฐ ๊ณต์ •์„ฑ ๋ฐ ๋ถˆ๋Šฅ ํ™•๋ฅ  ๊ฐ’๊ณผ ์ผ์น˜ํ•จ์„ ํ™•์ธํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์ด ์ค‘๊ณ„๊ธฐ๋“ค ์‚ฌ์ด์— ๊ณต์ •์„ฑ์„ ์™„๋ฒฝํ•˜๊ฒŒ ๋ณด์žฅํ•˜๊ณ  ๋„คํŠธ์›Œํฌ ์ˆ˜๋ช…์„ ์ฆ๊ฐ€์‹œํ‚ค๋ฉฐ, ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜๊ฐ€ ์ค‘๊ณ„๊ธฐ์˜ ์ˆ˜์™€ ํŽ˜์ด๋”ฉ ํŒŒ๋ผ๋ฏธํ„ฐ m ๊ฐ’์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง์„ ํ™•์ธํ•œ๋‹ค.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
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