274 research outputs found

    Maximum-rate Transmission with Improved Diversity Gain for Interference Networks

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    Interference alignment (IA) was shown effective for interference management to improve transmission rate in terms of the degree of freedom (DoF) gain. On the other hand, orthogonal space-time block codes (STBCs) were widely used in point-to-point multi-antenna channels to enhance transmission reliability in terms of the diversity gain. In this paper, we connect these two ideas, i.e., IA and space-time block coding, to improve the designs of alignment precoders for multi-user networks. Specifically, we consider the use of Alamouti codes for IA because of its rate-one transmission and achievability of full diversity in point-to-point systems. The Alamouti codes protect the desired link by introducing orthogonality between the two symbols in one Alamouti codeword, and create alignment at the interfering receiver. We show that the proposed alignment methods can maintain the maximum DoF gain and improve the ergodic mutual information in the long-term regime, while increasing the diversity gain to 2 in the short-term regime. The presented examples of interference networks have two antennas at each node and include the two-user X channel, the interferring multi-access channel (IMAC), and the interferring broadcast channel (IBC).Comment: submitted to IEEE Transactions on Information Theor

    Uplink Multiuser MIMO Detection Scheme with Reduced Computational Complexity

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    The wireless communication systems with multiple antennas have recently received significant attention due to their higher capacity and better immunity to fading channels as compared to single antenna systems. A fast antenna selection scheme has been introduced for the uplink multiuser multiple-input multiple-output (MIMO) detection to achieve diversity gains, but the computational complexity of the fast antenna selection scheme in multiuser systems is very high due to repetitive pseudo-inversion computations. In this paper, a new uplink multiuser detection scheme is proposed adopting a switch-and-examine combining (SEC) scheme and the Cholesky decomposition to solve the computational complexity problem. K users are considered that each users is equipped with two transmit antennas for Alamouti space-time block code (STBC) over wireless Rayleigh fading channels. Simulation results show that the computational complexity of the proposed scheme is much lower than the systems with exhaustive and fast antenna selection, while the proposed scheme does not experience the degradations of bit error rate (BER) performances

    A quaternion-based approach to interference alignment with Alamouti coding

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    Based on the representation of Alamouti space-time codewords as quaternions, this paper proposes a scheme that combines interference alignment (IA) with Alamouti signals. The proposed formulation allows for a separation of the space-time block coding (to gain spatial diversity) and the IA precoding (to reduce or ideally suppress interference). Although this separation is not necessarily optimal, the splitting of alignment precoding and Alamouti encoding is particularly convenient because it enables the independent optimization of the IA solution using quaternionic versions of standard alternating optimization techniques such as the maximum signal-to-interference-plus-noise algorithm. Some numerical simulations are included to compare the performance of the proposed quaternion IA+Alamouti algorithm with standard IA algorithms in the complex domain as well as with interference cancellation schemes at the receiver side.This work has been supported by the Ministerio de Economรญa, Industria y Competitividad (MINECO) of Spain, under grants TEC2013-47141-C4-R (RACHEL), TEC2016-75067-C4-4-R (CARMEN), and FPI grant BES-2014-06978

    Physical-Layer Transmission Cooperative Strategies for Heterogeneous Networks

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    The deployment of small cells within the boundaries of a macro-cell is considered to be an effective solution to cope with the current trend of higher data rates and improved system capacity. In the current heterogeneous configuration with the mass deployment of small cells, it is preferred that these two cell types coexist over the same spectrum, because acquiring additional spectrum licenses for small cells is difficult and expensive. However, the coexistence leads to cross-tier/inter-system interference. In this context, this contribution investigates interference alignment (IA) methods in order to mitigate the interference of macro-cell base station towards the small cell user terminals. More specifically, we design a diversity-oriented interference alignment scheme with space-frequency block codes (SFBC). The main motivation for joint interference alignment with SFBC is to allow the coexistence of two systems under minor inter-system information exchange. The small cells just need to know what space-frequency block code is used by the macro-cell system and no inter-system channels need to be exchanged, contrarily to other schemes recently proposed. Numerical results show that the proposed method achieves a performance close to the case where full-cooperation between the tiers is allowed

    ๋‹ค์ค‘์ž…์ถœ๋ ฅ ๊ฐ„์„ญ ์ฑ„๋„์—์„œ ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ ๊ธฐ๋ฐ˜ ๊ฐ„์„ญ ์ •๋ ฌ ํ›„ ์ œ๊ฑฐ ๊ธฐ๋ฒ•

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2015. 2. ๋…ธ์ข…์„ .๋ณธ ๋…ผ๋ฌธ์€ ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ์™€ ํ˜‘๋™ ํ†ต์‹ , ๊ทธ๋ฆฌ๊ณ  ๊ฐ„์„ญ ์ •๋ ฌ์— ๊ด€ํ•œ ๋‹ค์Œ ์„ธ ๊ฐ€์ง€ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ํฌํ•จํ•˜๊ณ  ์žˆ๋‹ค. ์ฒซ์งธ, ๋‹ค์ค‘์ž…์ถœ๋ ฅ ๊ฐ„์„ญ ์ฑ„๋„์—์„œ ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ๋ฅผ ํ™œ์šฉํ•˜๋Š” ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ๋‹ค์› ์ ‘์† ์ฑ„๋„์—์„œ์˜ ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ ๊ธฐ๋ฐ˜ ๊ฐ„์„ญ ์ œ๊ฑฐ ๊ธฐ๋ฒ•์ด K-์‚ฌ์šฉ์ž ๊ฐ„์„ญ ์ฑ„๋„์—์„œ๋„ ํ™œ์šฉ ๊ฐ€๋Šฅํ•œ ๊ฒƒ์„ ๋ณด์ธ๋‹ค. ์ˆ˜์‹  ๋‹จ์—์„œ ์•Œ๋ผ๋ฌดํ‹ฐ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐ„์„ญ ์‹ ํ˜ธ๋ฅผ ์ œ๊ฑฐํ•จ์œผ๋กœ์จ ์‹ฌ๋ณผ ๋‹จ์œ„ ๋ณตํ˜ธ๊ฐ€ ๊ฐ€๋Šฅํ•˜๊ณ  ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜ 2๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ๊ฐ„์„ญ ์ •๋ ฌ ๊ธฐ๋ฒ•๊ณผ ๋‹ฌ๋ฆฌ ์†ก์‹  ๋‹จ์—์„œ ์ฑ„๋„ ์ƒํƒœ ์ •๋ณด๋ฅผ ํ•„์š”๋กœ ํ•˜์ง€ ์•Š๋Š”๋‹ค๋Š” ์ด์ ์ด ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ ๊ธฐ๋ฐ˜ ๊ฐ„์„ญ ์ œ๊ฑฐ ๊ธฐ๋ฒ•์ด ๊ฐ„์„ญ ์ •๋ ฌ ๊ธฐ๋ฒ•๊ณผ ๊ฐ™์€ ์ž์œ ๋„๋ฅผ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ˆ˜์‹  ๋‹จ์—์„œ ๋งŽ์€ ์ˆ˜์˜ ์•ˆํ…Œ๋‚˜๋ฅผ ์ด์šฉํ•ด์•ผ๋งŒ ํ•œ๋‹ค. ์ˆ˜์‹  ์•ˆํ…Œ๋‚˜์˜ ์ˆ˜๋ฅผ ์ค„์ด๊ธฐ ์œ„ํ•œ ๋…ธ๋ ฅ์˜ ์ผํ™˜์œผ๋กœ, 3-์‚ฌ์šฉ์ž ๊ฐ„์„ญ ์ฑ„๋„์—์„œ์˜ ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ ๊ธฐ๋ฐ˜ ๊ฐ„์„ญ ์ •๋ ฌ ํ›„ ์ œ๊ฑฐ ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ ์†ก์‹  ๋‹จ์—์„œ ๋ถ€๋ถ„์  ์ฑ„๋„ ์ƒํƒœ ์ •๋ณด๋ฅผ ํ•„์š”๋กœ ํ•˜๋Š” ๋Œ€์‹ ์— ์ ์€ ์ˆ˜์‹  ์•ˆํ…Œ๋‚˜๋ฅผ ์ด์šฉํ•˜์—ฌ ๊ฐ„์„ญ ์ œ๊ฑฐ ๊ธฐ๋ฒ•๊ณผ ๊ฐ™์€ ์ž์œ ๋„ ๋ฐ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜๋ฅผ ์–ป๋Š”๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ œ์•ˆ๋œ ๋‘ ๊ฐ€์ง€ ๊ธฐ๋ฒ•์— ๋Œ€ํ•ด ์Œ ์˜ค๋ฅ˜ ํ™•๋ฅ ์„ ๋ถ„์„ํ•˜์—ฌ ๊ธฐ์กด์˜ ๊ฐ„์„ญ ์ •๋ ฌ ๊ธฐ๋ฒ•๋ณด๋‹ค ์šฐ์ˆ˜ํ•œ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์ฆ๋ช…ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์˜ ๋‘ ๋ฒˆ์งธ ๊ฒฐ๊ณผ๋กœ, ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ ์–‘๋ฐฉํ–ฅ ์ค‘๊ณ„ ๊ธฐ๋ฒ• ๋‘ ๊ฐ€์ง€๋ฅผ ์ œ์‹œํ•œ๋‹ค. ์ฒซ ๋ฒˆ์งธ ๊ธฐ๋ฒ•์€ K-์‚ฌ์šฉ์ž ๊ฐ„์„ญ ์ฑ„๋„์—์„œ์˜ ์•Œ๋ผ๋ฌดํ‹ฐ ๋ถ€ํ˜ธ ๊ธฐ๋ฐ˜ ๊ฐ„์„ญ ์ œ๊ฑฐ ๊ธฐ๋ฒ•์„ ์–‘๋ฐฉํ–ฅ ์ค‘๊ณ„ ์ฑ„๋„์— ํ™œ์šฉํ•œ ๊ฒƒ์ด๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์‹ฌ๋ณผ ๋‹จ์œ„ ๋ณตํ˜ธ๊ฐ€ ๊ฐ€๋Šฅํ•  ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ด๋“์„ ์–ป๋Š”๋‹ค. ๋”์šฑ ๋งŽ์€ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ด๋“์„ ๋‹ฌ์„ฑํ•˜๊ธฐ ์œ„ํ•ด ๋‘ ๋ฒˆ์งธ ์–‘๋ฐฉํ–ฅ ์ค‘๊ณ„ ๊ธฐ๋ฒ•์—์„œ๋Š” ๋น”ํ˜•์„ฑ ํ–‰๋ ฌ์„ ์ด์šฉํ•˜์—ฌ ์ค‘๊ณ„๊ธฐ์— ์‹ ํ˜ธ๋ฅผ ์ •๋ ฌ์‹œํ‚จ๋‹ค. ์ปดํ“จํ„ฐ ๋ชจ์˜์‹คํ—˜์„ ์‹ค์‹œํ•˜์—ฌ ๋‘ ๊ธฐ๋ฒ•์— ๋Œ€ํ•œ ๋น„๊ต๋ฅผ ํ†ตํ•ด, ์ œ์•ˆ๋œ ๋‘ ๋ฒˆ์งธ ๊ธฐ๋ฒ•์˜ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ด๋“์ด ์ฒซ ๋ฒˆ์งธ ๊ธฐ๋ฒ•๋ณด๋‹ค ์šฐ์ˆ˜ํ•˜๋‹ค๋Š” ๊ฒฐ๋ก ์„ ๋„์ถœํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์—ฌ๋Ÿฌ ๊ฐœ์˜ ์ค‘๊ณ„๊ธฐ๋ฅผ ๊ฐ–๋Š” ์—ฐํŒ์ • ํ›„ ์ „๋‹ฌ ํ˜‘๋™ ํ†ต์‹ ๋ง์—์„œ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๋ฐฉ์‹์„ ์ œ์•ˆํ•˜๊ณ , ์ด์˜ ์„ฑ๋Šฅ์„ ๋ถ„์„ํ•œ๋‹ค. ์ œ์•ˆ๋œ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์€ ๊ฐ€์žฅ ํฐ end-to-end ์‹ ํ˜ธ ๋Œ€ ์žก์Œ๋น„๋ฅผ ๊ฐ–๋Š” ์ค‘๊ณ„๊ธฐ๋ฅผ ์„ ํƒํ•˜์—ฌ ์ „์†ก์— ์ฐธ์—ฌ์‹œํ‚จ๋‹ค. ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๊ธฐ๋ฒ•์˜ ์Œ ์˜ค๋ฅ˜ ํ™•๋ฅ ๊ณผ ๋น„ํŠธ ์˜ค๋ฅ˜ ํ™•๋ฅ ์„ ๋ถ„์„ํ•˜๊ณ , ์ด๋ฅผ ๋ชจ๋“  ์ค‘๊ณ„๊ธฐ๊ฐ€ ์ „์†ก์— ์ฐธ์—ฌํ•˜๋Š” ๊ธฐ์กด ๋ฐฉ์‹์˜ ์„ฑ๋Šฅ๊ณผ ๋น„๊ตํ•œ๋‹ค. Fox H-ํ•จ์ˆ˜์˜ ๊ทนํ•œ๊ฐ’์œผ๋กœ๋ถ€ํ„ฐ ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๋ฐฉ์‹๊ณผ ๊ธฐ์กด ๋ฐฉ์‹์˜ ๋‹ค์ด๋ฒ„์‹œํ‹ฐ ์ฐจ์ˆ˜๋ฅผ ๊ตฌํ•œ๋‹ค. ๋‘ ์‹œ์Šคํ…œ์— ๋Œ€ํ•œ ๋น„๊ต๋ฅผ ํ†ตํ•ด, ์ค‘๊ณ„๊ธฐ ์„ ํƒ ๋ฐฉ์‹์€ ๋น„ํ‹ฐ ์˜ค๋ฅ˜ ํ™•๋ฅ ์ด๋‚˜ ์ „์†ก๋ฅ  ์ธก๋ฉด์—์„œ ๊ธฐ์กด์˜ ๋ฐฉ์‹๋ณด๋‹ค ์šฐ์ˆ˜ํ•œ ์„ฑ๋Šฅ์„ ๊ฐ€์ง์„ ํ™•์ธํ•œ๋‹ค.This dissertation contains the following three contributions to the interesting research topics on Alamouti code, interference alignment (IA), and cooperative communications. First, the methods on how to apply Alamouti code to MIMO interference channels are proposed. The IC method based on Alamouti codes for the multi-access scenario can be used for the K-user interference channel, which enables the receivers to perform symbol-by-symbol decoding by cancelling interfering signals by utilizing Alamouti structure and achieve diversity order of two. Moreover it does not require channel state information at the transmitters (CSIT) unlike the IA scheme. However, it requires more receive antennas than the IA scheme to achieve the same degrees of freedom (DoF). In order to reduce the number of receive antennas, especially for the three-user MIMO interference channel, an IAC scheme based on Alamouti codes is proposed, which keeps the same DoF as that of the IC scheme, but it requires partial CSIT. It is analytically shown that the IC and IAC schemes enable symbol-by-symbol decoding and achieve diversity order of two, while the conventional IA scheme achieves diversity order of one. In the second part of this dissertation, we propose two schemes for a TWRC based on Alamouti codes. Our IC method based on Alamouti codes for the K-user interference channel can be used for the TWRC, which enables the nodes to perform symbol-by-symbol decoding and achieve diversity order of two. In order to achieve more diversity gain, we propose a new two-way relaying scheme based on Alamouti codes which utilizes beamforming matrices to align signals at the relay node. From the simulation results, it is shown that the proposed scheme achieves diversity order of four. Finally, we analyze the best relay selection scheme for the SDF cooperative networks with multiple relays. The term best relay selectionimplies that the relay having the largest end-to-end signal-to-noise ratio is selected to transmit in the second phase transmission. The upper and lower bounds on the average pairwise error probability (PEP) are analyzed and compared with the conventional multiple-relay transmission scheme, where all the relays participate in the second phase transmission. Using the upper and lower bounds on the PEP and the asymptotes of the Fox's H-function, the diversity orders of the best relay selection and conventional relay schemes for the SDF cooperative networks are derived. It is shown that both schemes have the same full diversity order.Abstract i Contents v List of Tables viii List of Figures ix 1. Introduction 1 1.1. Background .......................................... 1 1.2. Overview of the Dissertation ........................ 5 1.3. Terms and Notations ................................. 7 2. Preliminaries 10 2.1. MIMO Communications ................................ 11 2.2. Space-Time Coding and Selection Diversity .......... 12 2.3. Cooperative Communications ......................... 16 2.3.1. Amplify-and-Forward Protocol ..................... 18 2.3.2. Decode-and-Forward Protocol ...................... 20 2.4. Interference Alignment ............................. 21 3. Interference Alignment-and-Cancellation Scheme Based on Alamouti Codes for the Three-User Interference Channel 25 3.1. Introduction ....................................... 25 3.2. Interference Cancellation Scheme Based on Alamouti Codes 28 3.2.1. Proof of Theorem 3.1 for K = 2 ................... 29 3.2.2. Proof of Theorem 3.1 for K โ‰ฅ 3 .................. 34 3.3. Interference Alignment-and-Cancellation Scheme for the Three-User MIMO Interference Channel .................... 36 3.3.1. Transmission and Reception Schemes ............... 37 3.3.2. Diversity Analysis ............................... 40 3.3.2.1. Proof of Theorem 3.2 for Receiver 1 when M = 1 . 41 3.3.2.2. Proof of Theorem 3.2 for Receivers 2 and 3 when M = 1 ............................................ 47 3.3.2.3. Proof of Theorem 3.2 for M โ‰ฅ 2 ................ 50 3.3.3. Extension to K-User MIMO Interference Channel .... 52 3.4. Simulation Results ................................. 53 3.5. Conclusions ........................................ 55 4. Two-Way Relaying Schemes with Alamouti Codes 57 4.1. Introduction ....................................... 57 4.2. Two-Way Relaying Scheme I Based on Alamouti Codes .. 58 4.3. Two-Way Relaying Scheme II Based on Alamouti Codes . 60 4.4. Simulation Results ................................. 62 4.5. Conclusion ......................................... 62 5. Analysis of Soft-Decision-and-Forward Cooperative Networks with Multiple Relays 64 5.1. Introduction ....................................... 64 5.2. Soft-Decision-and-Forward Protocol ................. 67 5.3. SDF Protocol with the Conventional Multiple-Relay Transmission ............................................ 72 5.3.1. System Model ..................................... 72 5.3.2. PEP and Diversity Order for the Conventional Scheme .................................................. 75 5.4. SDF Protocol with the Best Relay Selection ......... 77 5.4.1. System Model ..................................... 78 5.4.2. PEP and Diversity Order for the Best Relay Scheme 79 5.5. Simulation Results ................................. 81 5.6. Conclusion ......................................... 84 6. Conclusion 85 Bibliography 88 ์ดˆ๋ก 98Docto
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