2 research outputs found

    On Capacity and Optimal Scheduling for the Half-Duplex Multiple-Relay Channel

    Full text link
    We study the half-duplex multiple-relay channel (HD-MRC) where every node can either transmit or listen but cannot do both at the same time. We obtain a capacity upper bound based on a max-flow min-cut argument and achievable transmission rates based on the decode-forward (DF) coding strategy, for both the discrete memoryless HD-MRC and the phase-fading HD-MRC. We discover that both the upper bound and the achievable rates are functions of the transmit/listen state (a description of which nodes transmit and which receive). More precisely, they are functions of the time fraction of the different states, which we term a schedule. We formulate the optimal scheduling problem to find an optimal schedule that maximizes the DF rate. The optimal scheduling problem turns out to be a maximin optimization, for which we propose an algorithmic solution. We demonstrate our approach on a four-node multiple-relay channel, obtaining closed-form solutions in certain scenarios. Furthermore, we show that for the received signal-to-noise ratio degraded phase-fading HD-MRC, the optimal scheduling problem can be simplified to a max optimization.Comment: Author's final version (to appear in IEEE Transactions on Information Theory

    ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ๋‹ค์ค‘ ํ™‰ ํ˜‘๋ ฅ ๋ฆด๋ ˆ์ด ํ†ต์‹  ๋ฐฉ์‹ ์—ฐ๊ตฌ

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2012. 8. ๊น€์„ฑ์ฒ .๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋ฉ€ํ‹ฐ ํ™‰ ๋ฆด๋ ˆ์ด์— ์ ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ๊ฐœ๋ฐœ ๊ณผ์ •์„ ๋‹ค๋ฃจ๊ณ  ์žˆ๋‹ค. ๊ธฐ์ง€๊ตญ ๋งŒ์„ ์ด์šฉํ•˜๋Š” ๊ธฐ์กด์˜ ํ†ต์‹  ์‹œ์Šคํ…œ์˜ ๊ฒฝ์šฐ Line-of-Sight๋ฅผ ํ™•๋ณดํ•˜๊ธฐ ํž˜๋“ค๊ณ  ์ƒ๋Œ€์ ์œผ๋กœ ํ†ต์‹  ๊ฑฐ๋ฆฌ๊ฐ€ ๋ฉ€์–ด ์‹œ์Šคํ…œ์˜ ์ฑ„๋„ ์šฉ๋Ÿ‰์„ ํ™•๋ณดํ•˜๋Š” ๋ฐ์— ์–ด๋ ค์›€์ด ์žˆ๋‹ค. ๋˜ํ•œ, ๊ธฐ์ง€๊ตญ์„ ๋งŽ์ด ๊ฑด์„คํ•จ์œผ๋กœ์จ ํ†ต์‹  ์šฉ๋Ÿ‰์„ ์ฆ๋Œ€์‹œํ‚ค๊ณ  Line-of-Sight๋ฅผ ํ™•๋ณดํ•˜๋Š” ๋ฐฉ๋ฒ•์—๋Š” ๋น„์šฉ์ด ๋งŽ์ด ์†Œ์š”๋œ๋‹ค. ๋ฉ€ํ‹ฐ ํ™‰ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ์€ ์ƒ๋Œ€์ ์œผ๋กœ ๋‚ฎ์€ ์ „์†ก ํŒŒ์›Œ์™€ ์งง์€ ๊ฑฐ๋ฆฌ๋ฅผ ์ด์šฉํ•˜์—ฌ, Line-of-Sight๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ํ™•๋ณดํ•  ์ˆ˜ ์žˆ๊ณ , ๋น„์šฉ๋„ ์ ๊ฒŒ ์†Œ๋ชจ๋œ๋‹ค๋Š” ์žฅ์ ์ด ์žˆ๋‹ค. ๋ฉ€ํ‹ฐ ํ™‰ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ์€ ์†ก์ˆ˜์‹  ๋ฐฉ๋ฒ•์— ๋”ฐ๋ผ ๋ฐ˜์ด์ค‘ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ (HDR)๊ณผ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ (FDR)์œผ๋กœ ๋‚˜๋ˆŒ ์ˆ˜ ์žˆ๋‹ค. ๋ฐ˜์ด์ค‘ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ์€ ๋ฆด๋ ˆ์ด๊ฐ€ ์†ก์‹ ๊ณผ ์ˆ˜์‹ ์„ ์‹œ๊ฐ„ ํ˜น์€ ์ฃผํŒŒ์ˆ˜ ๋Œ€์—ญ์œผ๋กœ ๋‚˜๋ˆ„์–ด ์†ก/์ˆ˜์‹  ํ•จ์œผ๋กœ์จ ๋ฆด๋ ˆ์ด์˜ ์†ก์‹ ๊ณผ ์ˆ˜์‹  ์‚ฌ์ด์— ๊ฐ„์„ญ์ด ์ผ์–ด๋‚˜์ง€ ์•Š์ง€๋งŒ, ์ƒ๋Œ€์ ์œผ๋กœ ํ†ต์‹  ์ž์›์„ ํšจ์œจ์ ์œผ๋กœ ์‚ฌ์šฉํ•˜์ง€ ๋ชปํ•œ๋‹ค๋Š” ๋‹จ์ ์ด ์žˆ๋‹ค. ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ์€ ๊ฐ™์€ ์‹œ๊ฐ„ ๋ฐ ์ฃผํŒŒ์ˆ˜ ๋Œ€์—ญ์„ ์ด์šฉํ•˜์—ฌ ์†ก์ˆ˜์‹ ์„ ํ•˜์—ฌ ํ†ต์‹  ์ž์›์„ ํšจ์œจ์ ์œผ๋กœ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ๋ฆด๋ ˆ์ด์˜ ์†ก์ˆ˜์‹  ์•ˆํ…Œ๋‚˜ ์‚ฌ์ด์—์„œ ์ž๊ธฐ ๊ฐ„์„ญ์ด ๋ฐœ์ƒํ•˜์—ฌ ๊ทธ ์„ฑ๋Šฅ์„ ํฌ๊ฒŒ ์ €ํ•˜์‹œํ‚จ๋‹ค๋Š” ๋‹จ์ ์„ ๊ฐ–๋Š”๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ๋…ผ๋ฌธ์€ ๋ฆด๋ ˆ์ด์˜ ์ž๊ธฐ ๊ฐ„์„ญ์„ ์ œ๊ฑฐํ•˜๊ณ  ๊ทธ ์žฅ์ ์„ ๊ทน๋Œ€ํ™” ํ•  ์ˆ˜ ์žˆ๋Š” ํ”„๋ฆฌ์ฝ”๋”ฉ์„ ์ œ์•ˆํ•˜์—ฌ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด์˜ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ณ ์ž ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ํฌ๊ฒŒ Block-Diagonalization์„ ์ด์šฉํ•œ FDR ์‹œ์Šคํ…œ๊ณผ Limited Feedback Precoding์„ ์ด์šฉํ•œ FDR ์‹œ์Šคํ…œ์œผ๋กœ ๋‚˜๋ˆŒ ์ˆ˜ ์žˆ๋‹ค. ๊ธฐ์กด์— ์—ฐ๊ตฌ๋œ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ ๊ด€๋ จ ์—ฐ๊ตฌ์˜ ๊ฒฝ์šฐ, Dirty Paper Coding์„ ์ด์šฉํ•˜์—ฌ Rate bound๋ฅผ ๊ตฌํ•˜๊ฑฐ๋‚˜, ์‹ค์งˆ์ ์œผ๋กœ ๋ฆด๋ ˆ์ด ํ”„๋ฆฌ์ฝ”๋”ฉ์„ ๊ณ ๋ คํ•˜์ง€ ์•Š๊ณ  ์„ฑ๋Šฅ์„ ๊ตฌํ•œ ๊ฒƒ์ด ๋Œ€๋ถ€๋ถ„์ด๋‹ค. ์‹ค์ œ ์‹œ์Šคํ…œ์„ ๊ณ ๋ คํ•˜์—ฌ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด๋ฅผ ์—ฐ๊ตฌํ•œ ๋…ผ๋ฌธ์˜ ๊ฒฝ์šฐ ๊ธฐ์ง€๊ตญ๊ณผ ๋‹จ๋ง์— ํ•œ ๊ฐœ์˜ ์†ก์ˆ˜์‹  ์•ˆํ…Œ๋‚˜๋ฅผ ์ ์šฉํ•˜๊ณ  ๋ฆด๋ ˆ์ด์—๋งŒ ๋‘ ๊ฐœ์˜ ์†ก์ˆ˜์‹  ์•ˆํ…Œ๋‚˜๋ฅผ ์ ์šฉํ•˜์—ฌ ์ž๊ธฐ ๊ฐ„์„ญ ์ฑ„๋„์˜ ์˜๊ณต๊ฐ„์„ ๊ตฌํ•ด ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ์ด๋Ÿฌํ•œ ๋ฐฉ๋ฒ•์˜ ๊ฒฝ์šฐ MIMO๋ฅผ ์ด์šฉํ•˜์—ฌ ์ฑ„๋„ ์šฉ๋Ÿ‰์„ ํ–ฅ์ƒ ์‹œํ‚ฌ ์ˆ˜ ์—†์œผ๋ฉฐ, ๋ฆด๋ ˆ์ด๊ฐ€ ๊ธฐ์ง€๊ตญ๋ณด๋‹ค๋„ ์˜คํžˆ๋ ค ๋งŽ์€ ์ˆ˜์˜ ์†ก์ˆ˜์‹  ์•ˆํ…Œ๋‚˜๋ฅผ ์‚ฌ์šฉํ•ด์•ผ ํ•œ๋‹ค. ๋˜ํ•œ, ๋ฆด๋ ˆ์ด๊ฐ€ ์—ฌ๋Ÿฌ ๊ฐœ ์กด์žฌํ•˜๋Š” ์ƒํ™ฉ์ด๋‚˜ ์‚ฌ์šฉ์ž๊ฐ€ ์—ฌ๋Ÿฌ ๋ช… ์กด์žฌํ•˜๋Š” ์ƒํ™ฉ์„ ๊ณ ๋ คํ•˜์ง€ ๋ชปํ•˜์—ฌ ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์— ํšจ๊ณผ์ ์œผ๋กœ ๋Œ€์ฒ˜ํ•  ์ˆ˜ ์—†๋‹ค๋Š” ๋‹จ์ ์ด ์žˆ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•˜๋Š” Block-Diagonalization์„ ์ด์šฉํ•œ FDR ์‹œ์Šคํ…œ์€ ํ†ต์‹  ์ฑ„๋„ ๋ฐ ์ž๊ธฐ ๊ฐ„์„ญ ์ฑ„๋„์„ ๊ฒฐํ•ฉํ•˜์—ฌ ์˜๊ณต๊ฐ„์„ ๊ตฌํ•จ์œผ๋กœ์จ ๊ธฐ์ง€๊ตญ๊ณผ ๋ฆด๋ ˆ์ด ๋ฐ ์‚ฌ์šฉ์ž๊ฐ€ ๊ฐ™์€ ์ˆ˜์˜ ์†ก์ˆ˜์‹  ์•ˆํ…Œ๋‚˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ํ†ต์‹ ์„ ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€์œผ๋ฉฐ, MIMO ์‹œ์Šคํ…œ์„ ์ ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์—ฌ ์•ˆํ…Œ๋‚˜ ์ˆ˜๋ฅผ ๋Š˜๋ ค์„œ ํ†ต์‹  ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์—ฌ๋Ÿฌ ๊ฐœ์˜ ๋ฆด๋ ˆ์ด๊ฐ€ ์žˆ๋Š” ์‹œ๋‚˜๋ฆฌ์˜ค์™€ ์—ฌ๋Ÿฌ ๋ช…์˜ ์‚ฌ์šฉ์ž๊ฐ€ ์žˆ๋Š” ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์—์„œ๋„ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด๋ฅผ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. Limited Feedback Precoding์„ ์ด์šฉํ•œ FDR ์‹œ์Šคํ…œ์€ Limited Feedback Precoding์„ ์ด์šฉํ•œ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•œ๋‹ค. Limited Feedback Precoding์€ Channel State Information์„ ํ•„์š”๋กœ ํ•˜๋Š” ๊ธฐ์กด ์•Œ๊ณ ๋ฆฌ์ฆ˜๊ณผ ๋‹ฌ๋ฆฌ ์ตœ๊ณ ์˜ ์„ฑ๋Šฅ์„ ๋‚˜ํƒ€๋‚ด๋Š” precoding์˜ index๋งŒ์„ feedback ํ•จ์œผ๋กœ์จ feedback ์–‘์„ ์ค„์ด๋ฉด์„œ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ์„ ํ–ฅ์ƒ ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ, Iterative Limited Feedback ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•จ์œผ๋กœ์จ Multi Relay ๋ฐ Multi User ์‹œ๋‚˜๋ฆฌ์˜ค์—์„œ๋„ ๋” ์ ์€ feedback ์–‘์œผ๋กœ ์–‘๋ฐฉํ–ฅ ๋ฆด๋ ˆ์ด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค.The promising concept of multi-hop relay has recently stimulated intensive research to improve the performance of wireless systems. It is well known that a cooperative link that uses a relay station (RS) not only enhances coverage but also increases the capacity of the communication system in a shadow region, wherein the strength of a signal transmitted from a base station (BS) might be less than the receiver sensitivity because of signal obstruction by geographical structures [1]. In a single-relay single-user (SRSU) half-duplex relay (HDR) system, two links (the link between a BS and an RS is called the BS-RS link and that between an RS and a mobile station (MS) is called the RS-MS link) exist with only one link operating at any given instant. Although this type of relay system is beneficial in terms of hardware simplicity, it suffers from the drawback of capacity reduction due to partitioned resources. In contrast, the advantage of a full-duplex relay (FDR) over an HDR system in terms of system capacity is that an RS in an FDR system can simultaneously transmit and receive signals in the same frequency band. Even though this advantage of an FDR system can improve system capacity, an FDR system suffers from the crucial limitation of self-interference that occurs between the signals transmitted from and received by the same RS (RS-RS link) [2]. This dissertation proposes the FDR precodings for the SRSU, multi-relay single-user (MRSU) and single-relay multi-user (SRMU) systems. In the SRSU and MRSU system, it is crucial to design an FDR precoding scheme in order to prevent aforementioned self-interference imposed by the transmitting antennas on the receiving antennas in the same relay station. In the SRMU FDR system, the multi-user interference caused by co-channel MSs must be considered. In this dissertation, I propose a precoder scheme that mitigates the residual self-interference of the relay station using block-diagonalization (BD) [3] and limited feedback precoding [4]-[5]. The proposed precoding scheme not only prevents self-interference but also provides the improved system capacity compared to HDR system. I propose the BD beamforming vectors that are designed in terms of BD criteria. The conventional technique requires 2 transmitting and receiving antennas in SISO SRSU system [6]. Compared to the conventional scheme, the proposed algorithm relaxes this restriction of the number of transmitting antennas by combining channel matrices and saves the transmit power of RSs. The proposed scheme can be adopted in multiple-input multiple-output (MIMO) SRSU, MRSU and SRMU systems. I also propose the FDR systems that are designed in terms of limited feedback criteria. The conventional FDR precodings require the channel state information of all communication channels. In the limited feedback precoding, the receiver selects one of the beamformers with the best signal-to-interference ratio (SINR) for that receiver and feeds back only the index of the optimal precoder. The proposed precoding scheme based on limited feedback precoding prevents self-interference and multi-user interference for the SRSU, MRSU and SRMU systems. I also propose iterative limited feedback precoding for the FDR system. The iterative limited feedback precoding only requires the channel state information of the adjacent relay and users. The proposed scheme not only provides less computational complexity but also achieves system performance closely to the centralized limited feedback precoding. Numerical results are illustrated to show the capacity analysis of the limited feedback and iterative limited feedback precodings for the SRSU, MRSU and SRMU systems.Contents Abstract i Contents v List of Figures viii List of Tables xi Chapter 1 Introduction ๏ผ‘ 1.1 Relay Communications ๏ผ‘ 1.2 Half-duplex relay and Full-duplex relay ๏ผ“ 1.3 Block Diagonalization (BD) and Limited Feedback precoding ๏ผ• 1.4 Dissertation Outline ๏ผ– Chapter 2 BD FDR Precoding for the SRSU System ๏ผ˜ 2.1 Motivation ๏ผ˜ 2.2 System Model ๏ผ‘๏ผ 2.3 Channel Capacity of the SRSU HDR System ๏ผ‘๏ผ‘ 2.4 Proposed Precoding Scheme for the SRSU FDR System ๏ผ‘๏ผ” 2.5 Channel Capacity of the SRSU FDR System ๏ผ‘๏ผ˜ 2.6 Simulation Results and Discussion ๏ผ‘๏ผ™ 2.7 Conclusion ๏ผ’๏ผ’ Chapter 3 BD FDR Precoding for the MRSU System ๏ผ’๏ผ“ 3.1 Motivation ๏ผ’๏ผ“ 3.2 System Model ๏ผ’๏ผ” 3.3 Channel Capacity of the MRSU HDR System ๏ผ’๏ผ˜ 3.4 Proposed Precoding Scheme for the MRSU FDR System ๏ผ“๏ผ 3.5 Channel Capacity of the MRSU FDR System ๏ผ“๏ผ” 3.6 Simulation Results and Discussion ๏ผ“๏ผ– 3.7 Conclusion ๏ผ”๏ผ Chapter 4 BD FDR Precoding for the SRMU System ๏ผ”๏ผ‘ 4.1 Motivation ๏ผ”๏ผ‘ 4.2 System Model ๏ผ”๏ผ’ 4.3 Channel Capacity of the SRMU HDR System ๏ผ”๏ผ• 4.4 Proposed FDR Precoding Scheme for the SRMU System ๏ผ”๏ผ— 4.5 Channel Capacity of the SRMU FDR System ๏ผ•๏ผ‘ 4.6 Simulation Results and Discussion ๏ผ•๏ผ’ 4.7 Conclusion ๏ผ•๏ผ– Chapter 5 Limited Feedback FDR Precoding for the SRSU System ๏ผ•๏ผ˜ 5.1 Motivation ๏ผ•๏ผ˜ 5.2 System Model ๏ผ•๏ผ™ 5.3 Proposed FDR Precoding Scheme for the SRSU System ๏ผ–๏ผ‘ 5.4 Centralized Limited Feedback Precoding Scheme for the SRSU FDR System ๏ผ–๏ผ“ 5.5 Iterative Limited Feedback Precoding Scheme for the SRSU FDR System ๏ผ–๏ผ“ 5.6 Simulation Results and Discussion ๏ผ–๏ผ” 5.7 Conclusion ๏ผ–๏ผ˜ Chapter 6 Limited Feedback FDR Precoding for the MRSU System ๏ผ–๏ผ™ 6.1 Motivation ๏ผ–๏ผ™ 6.2 System Model ๏ผ—๏ผ 6.3 Proposed FDR Precoding Scheme for the MRSU System ๏ผ—๏ผ’ 6.4 Centralized Limited Feedback Precoding Scheme for the MRSU FDR System ๏ผ—๏ผ• 6.5 Iterative Limited Feedback Precoding Scheme for the MRSU FDR System ๏ผ—๏ผ– 6.6 Simulation Results and Discussion ๏ผ—๏ผ– 6.7 Conclusion ๏ผ˜๏ผ’ Chapter 7 Limited Feedback FDR Precoding for the SRMU System ๏ผ˜๏ผ” 7.1 Motivation ๏ผ˜๏ผ” 7.2 System Model ๏ผ˜๏ผ• 7.3 Proposed FDR Precoding Scheme for the SRMU System ๏ผ˜๏ผ— 7.4 Centralized Limited Feedback Precoding Scheme for the SRMU FDR System ๏ผ˜๏ผ™ 7.5 Iteratrive Limited Feedback Precoding Scheme for the SRMU FDR System ๏ผ˜๏ผ™ 7.6 Simulation Results and Discussion ๏ผ™๏ผ‘ 7.7 Conclusion ๏ผ™๏ผ— Chapter 8 Conclusion ๏ผ™๏ผ˜ Bibliography ๏ผ‘๏ผ๏ผDocto
    corecore