臺灣博碩士論文加值系統

合作式通訊在近年受到更多研究關注，在新一代的行動通訊網路中，合作通訊有機會為整體帶來更高的資源使用效率。合作式中繼通訊的研究中，由中繼器所產生的多段式傳輸是主要的研究內容。從無線通訊技術發展至今，中繼器一直負責延伸訊號覆蓋率的任務，從一開始的功率放大前傳，到最新的電信規格使用解碼前傳。有別於上述的中繼器規格採用單一中繼器或串聯前傳，並排前傳的模式提供了令一個結合中繼器網路與時空碼的機會。多個中繼器使用時空編碼方式傳輸稱為分散式時空碼。近年來，時空碼的研究多在多天線上的運用，分散式時空碼利用座落不同座標的中繼器來做空間多樣性利用。也由於座標的分散性質，中繼器、發訊端、接收端三者之間的通道資訊必須在接收端完整蒐集。因此，我們提出採用濾波前傳中繼器，設計濾波器來組織領航訊符，使通道資訊座落於信號空間的正交位置。接收端則可在後端計算出各連結的通道資訊來解碼分散式時空碼。經設計過後的濾波器在效果上等同於分時、分頻以及分碼多工的型態來協助通道估測。為了檢驗實驗結果，推導了多重中繼器下分段通道估測的最小平方差誤差理論值，其結果與實驗數據吻合。為評估效能，推導了在多重中繼器下分段通道估測的Bayesian Cramér-Rao下限，可作為其他濾波前傳的分段通道檢估技術的評估指標，所提出的分段估測技術結合最小平方通道估測的結果也相當接近此下限。

Cooperative communication, which has attracted the attention of researchers in recent years, enables the efficient use of resources in mobile communication systems.
The research of cooperative communication begin with relay generated multi-link transmission.
From the simplest amplify-and-forward to the most complicated decode-and-forward, relay serves a role of extending the coverage ratio for wireless signal in a practical manner.
Deploying a single relay or series connected relays is popular because of its simplicity.
Conversely, employing parallel relays and space time coding is referred to as distributed space time coding (D-STC) can obtain the advantage of spatial diversity.
In this research a disintegrated channel estimation technique is proposed to accomplish the spatial diversity that is supported by cooperative relays.
The relaying strategy that is considered in this research is a filter-and-forward (FF) relaying method with superimposed training sequences to estimate backhaul and access channels separately.
To reduce inter-relay interference, a generalized filtering technique is proposed and investigated.
Unlike the interference suppression method that is commonly employed in conventional FF relay networks, a generalized filter multiplexes the superimposed training sequences from different relays to the destination by time-division multiplexing (TDM), frequency-division multiplexing (FDM) and code-division multiplexing (CDM) methods.
The theoretical mean square errors (MSEs) of disintegrated channel estimation is derived and match to the simulation results.
The Bayesian Cramer-Rao lower bounds (BCRBs) are derived as the estimation performance benchmark.
The improvements offered by the proposed technique are verified by comprehensive computer simulation in conjunction with calculations of the derived BCRBs and the MSEs.

1 Introduction 1
1.1 Motivations 1
1.2 Cooperative Communication 2
1.3 Relay Modes in the Cellular System 3
1.3.1 Non-transparent Relay 3
1.3.2 Transparent Relay 4
1.3.3 Decentralized Cooperation 5
1.4 Relay Protocols in Transmission Layers 5
1.4.1 Amplify-and-Forward Relay 5
1.4.2 Decode-and-Forward Relay 6
1.4.3 Filter-and-Forward Relay 6
1.5 Relay Protocols in Forward Directions 7
1.5.1 One-Way Relay 7
1.5.2 Two-Way Relay 7
1.6 Multi-Relay 8
1.6.1 Multi-hop 8
1.6.2 Multiple access 8
1.7 Discussion on Relay Channel Estimation 8
1.8 Organization of this Dissertation 10

2 Distributed Space Time Block Coding 11
2.1 Literature Review 11
2.2 Signal Model 14
2.2.1 Channel Model 14
2.2.2 Signal Model 15
2.3 Problem Formulation 18

3 Disintegrated Channel Estimation 21
3.1 Disintegrated Channel Estimation Technique 21
3.1.1 Superimposed Pilot with TDM 23
3.1.2 Superimposed Pilot with FDM 25
3.1.3 Superimposed Pilot with CDM 27
3.2 MSE 28
3.2.1 MSE Derivations of the Proposed CDM LS Channel Estimation 28
3.2.2 MSE Derivations of the Proposed TDM LS Channel Estimation 32
3.2.3 MSE Derivations of the Proposed FDM LS Channel Estimation 34
3.2.4 Summaries of the derived MSE 36

4 Performance of Disintegrated Channel Estimation 37
4.1 BCRB 37
4.1.1 Derivations 37
4.1.2 Demonstration 41
4.2 Simulations of Scaled Relay Networks 41
4.2.1 Performance in MSE 42
4.2.2 Performance in SER 45
4.2.3 Discussions 47
4.3 Simulations of Overscaled Relay Networks 49
4.3.1 Discussions 54

5 Conclusions 57

[1] C. S. Patel and G. L. Stüber, “Channel estimation for amplify and forward relay based cooperation diversity systems,” IEEE Trans. Wireless Commun., vol. 6, pp. 2348–2356, June 2007.
[2] J. N. CLaneman, D. N. C. Tse, and G.W.Wornell, “Cooperative diversity in wireless networks: Efficient
protocols and outage behavior,” IEEE Trans. Inf. Theory, vol. 50, p. 3062â˘A ¸S3080, Nov. 2004.
[3] A. Sendonaris, E. Erkip, and B. Aazhang, “User cooperation diversity, part ii: System description,”
IEEE Trans. Commun., vol. 51, pp. 1939–1948, Nov. 2003.
[4] O. Muñoz-Medina, J. Vidal, and A. Agustín, “Linear transceiver design in nonregenerative relays with
channel state information,” IEEE Trans. Signal Process., vol. 55, pp. 2593–2604, June 2007.
[5] Y.W. Liang, A. Ikhlef,W. Gerstacker, and R. Schober, “Cooperative filter-and-forward beamforming for
frequency-selective channels with equalization,” IEEE Trans. Wireless Commun., vol. 10, pp. 228–239,
Jan. 2011.
[6] Y. W. Liang, A. Ikhlef, W. Gerstacker, and R. Schober, “Two-way filter-and-forward beamforming for
frequency-selective channels,” IEEE Trans. Wireless Commun., vol. 10, pp. 4172–4183, Jan. 2011.
[7] H. Chen, A. B. Gershman, and S. Shahbazpanahi, “Filter-and-forward distributed beamforming in relay
networks with frequency selective fading,” IEEE Trans. Signal Process., vol. 58, pp. 1251–1262, Mar. 2010.
[8] G. Kramer, M. Gastpar, and P. Gupta, “Cooperative strategies and capacity theorems for relay networks,”
IEEE Trans. Inf. Theory, vol. 51, pp. 3037–3063, Sept. 2005.
[9] S. Simoens, O. Muñoz-Medina, J. Vidal, and A. D. Coso, “Compress-and-forward cooperative mimo relaying with full channel state information,” IEEE Trans. Signal Process., vol. 58, pp. 781–791, Feb. 2010.
[10] X.Wu and L. L. Xie, “On the optimal compressions in the compress-and-forward relay schemes,” IEEE
Trans. Inf. Theory, vol. 59, pp. 2613–2628, May 2013.
[11] T. Cui, F. Gao, T. Ho, and A. Nallanathan, “Distributed spaceâ˘A ¸Stime coding for two-way wireless
relay networks,” IEEE Trans. Signal Process., vol. 57, pp. 658–671, Feb. 2009.
[12] S. J. Alabed, J. M. Paredes, and A. B. Gershman, “Distributed spaceâ˘A ¸Stime coding for two-way wireless
relay networks,” IEEE Trans. Wireless Commun., vol. 11, pp. 1260–1265, Apr. 2012.
[13] J. Kim, J. Hwang, K. J. Lee, and I. Lee, “Blockwise amplify-and-forward relaying strategies for
multipoint-to-multipoint mimo networks,” IEEE Trans. Wirel. Commun., vol. 10, pp. 2028–2033, July 2011.
[14] F. Khan, Y. Chen, and M. Alouini, “Novel receivers for af relaying with distributed stbc using cascaded
and disintegrated channel estimation,” IEEE Trans. Wirel. Commun., vol. 58, pp. 1370–1379, Apr. 2012.
[15] T. Q. Duong, G. C. Alexandropoulos, H. Zepernick, and T. A. Tsiftsis, “Orthogonal space-time block
codes with csi-assisted amplify-and-forward relaying in correlated nakagami-m fading channels,” IEEE
Trans. Vehic. Technol., vol. 60, pp. 882–889, Mar. 2011.
[16] Z. Li, X. G. Xia, and M. H. Lee, “A simple orthogonal space-time coding scheme for asynchronous
cooperative systems for frequency selective fading channels,” IEEE Trans. Commun., vol. 58, pp. 2219–
2224, Aug. 2010.
[17] A. Sendonaris, E. Erkip, and B. Aazhang, “User cooperation diversity, part i: System description,” IEEE
Trans. Commun., vol. 51, pp. 1927–1938, Nov. 2003.
[18] J. N. Laneman and G. W. Wornell, “Distributed space-time-coded protocols for exploiting cooperative
diversity in wireless networks,” IEEE Trans. Inf. Theory, vol. 49, pp. 2415–2425, Oct. 2003.
[19] X. Li, C. Xing, Y.-C. Wu, and S. C. Chan, “Timing estimation and resynchronization for amplify-andforward
communication systems,” IEEE Trans. Signal Process., vol. 58, pp. 2218–2229, Apr. 2010.
[20] Q. Huang, M. Ghogho, J.Wei, and P. Ciblat, “Practical timing and frequency synchronization for ofdmbased
cooperative systems,” IEEE Trans. Signal Process., vol. 58, pp. 3706–3716, July 2010.
[21] Y. Yao and X. Dong, “Multiple cfo mitigation in amplify-and-forward cooperative ofdm transmission,”
IEEE Trans. Commun., vol. 60, pp. 3844–3854, Dec. 2012.
[22] A. A. Nasir, H. Mehrpouyan, S. Durrani, S. D. Blostein, R. A. Kennedy, and B. Ottersten, “Transceiver
design for distributed stbc based af cooperative networks in the presence of timing and frequency offsets,”
IEEE Trans. Signal Process., vol. 61, pp. 3143–3158, June 2013.
[23] S. Alamouti, “A simple transmit diversity technique for wireless communications,” IEEE Journ. Sel.
Are. Commun., vol. 16, pp. 1451–1458, Oct. 1998.
[24] F. Gao, T. Cui, and A. Nallanathan, “On channel estimation and optimal training design for amplify and
forward relay networks,” IEEE Trans. Wirel. Commun., vol. 7, pp. 1907–1916, May 2008.
[25] A. S. Lalos, A. A. Rontogiannis, and K. Berberidis, “Frequency domain channel estimation for cooperative
communication networks,” IEEE Trans. Signal Process., vol. 58, pp. 3400–3405, June 2010.
[26] T. Kong and Y. Hua, “Optimal design of source and relay pilots for mimo relay channel estimation,”
IEEE Trans. Signal Process., vol. 59, pp. 4438–4446, Sept. 2011.
[27] M. G. Song, K. Dongsik, and G. H. Im, “Recursive channel estimation method for ofdm-based cooperative
systems,” IEEE Commun. Lett., vol. 14, pp. 1029–1031, Nov. 2010.
[28] J. Z. J. Ma, P. Orlik and G. Y. Li, “Pilot matrix design for estimating cascaded channels in two-hop
mimo amplify-and-forward relay systems,” IEEE Trans. Wirel. Commun., vol. 10, pp. 1956–1965, June 2011.
[29] S. K. Jo, J. M. Choi, J. S. Baek, and J. S. Seo, “Channel estimation with optimal power controls in
amplify-and-forward relay networks,” IEEE Wirel. Commun. Lett., vol. 2, pp. 10–13, Feb. 2013.
[30] C. Zhang, J. Zhang, W. D. Wang, and G. Wei, “Distributed space-time decoding with two-pilot channel
estimation for wireless relay networks using blue approach,” in Proc. IEEE Personal, Indoor, Mobile
and Radio Commun. Conf. (PIMRC), (Tokyo, Japan), pp. 13–16, Sept. 2009.
[31] O. Amin, B. Gedik, and M. Uysal, “Channel estimation for amplify-and-forward relaying: Cascaded
against disintegrated estimators,” IET Commun., vol. 4, pp. 1207–1216, Oct. 2010.
[32] X. Tang and Y. Hua, “Optimal design of non-regenerative mimo wireless relays,” IEEE Trans. Wirel.
Commun., vol. 6, pp. 1398–1407, Apr. 2007.
[33] Y. Rong, X. Tang, and Y. Hua, “A unified framework for optimizing linear non-regenerative multicarrier
mimo relay communication systems,” IEEE Trans. Signal Process., vol. 57, pp. 2837–2851, Dec. 2009.
[34] Y. Li, W. Wang, J. Kong, and M. Peng, “Subcarrier pairing for amplify-and-forward and decode-andforward
ofdm relay links,” IEEE Commun. Lett., vol. 13, pp. 209–211, Apr. 2009.
[35] J.-C. Lin, “Least-squares channel estimation for mobile ofdm communication on time-varying
frequency-selective fading channels,” IEEE Trans. Vehic. Technol., vol. 57, pp. 3538–3550, Nov. 2008.
[36] J.-C. Lin, “Least-squares channel estimation assisted by self-interference cancellation for mobile prpofdm applications,” IET Commun., vol. 3, pp. 1907–1918, Dec 2009.
[37] J.-C. Lin, “Channel estimation assisted by postfixed pseudo-noise sequences padded with zero samples
for mobile orthogonal-frequency-division-multiplexing communications,” IET Commun., vol. 3, pp. 564–570, Apr 2009.
[38] J.-C. Lin, H.-K. Chang, M.-L. Ku, and H. V. Poor, “Impact of imperfect source-to-relay csi in amplifyand-
forward relay networks,” IEEE Trans. Vehic. Technol. to appear.
[39] F. Gao, B. Jiang, and X. D. Zhang, “Superimposed training based channel estimation for ofdm modulated
amplify-and-forward relay networks,” IEEE Trans. Commun., vol. 59, pp. 2029–2039, Nov. 2011.
[40] K. P. Chou and J. C. Lin, “Disintegrated channel estimation in scalable filter-and-forward relay network
with iri coordination,” in Proc. 2015 Wireless Telecommunications Symposium (WTS), (New York, USA), pp. 1–6, Apr. 2015.
[41] K. P. Chou, J. C. Lin, and H. V. Poor, “Disintegrated channel estimation in filter-and-forward relay networks,” IEEE Trans. Commun., vol. 64, pp. 2835–2847, July 2016.
[42] A. S. Ibrahim, W. S. A. K. Sadek, and K. J. R. Liu, “Cooperative communications with relay-selection:
When to cooperate and whom to cooperate with?,” IEEE Trans. Wirel. Commun., vol. 7, pp. 2814–2827, July 2008.
[43] F. Gao, R. Zhang, and Y. C. Liang, “Optimal channel estimation and training design for two-way relay
networks,” IEEE Trans. Commun., vol. 51, pp. 3024–3033, Oct. 2009.
[44] Z. Li, X. G. Xia, and B. Li, “Achieving full diversity and fast ml decoding via simple analog network
coding for asynchronous two-way relay networks,” IEEE Trans. Commun., vol. 57, pp. 3672–3681, Dec. 2009.
[45] H. Mheidat, M. Uysal, and N. Al-Dhahir, “Equalization techniques for distributed space-time block
codes with amplify-and-forward relaying,” IEEE Trans. Signal Process., vol. 55, pp. 1839–1852, May
2007.
[46] G. T. 36.216, “Evolved universal terrestrial radio access (e-utra): Physical layer for relaying operation,”
tech. rep., http://www.3gpp.org.
[47] C. F. C. L. G. H. Golub, Matrix Computaions, vol. 1 of The Art of Computer Programming. The Johns Hopkins University Press.
[48] S. M. Kay, Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory. Prentice Hall,
1993.
[49] G. T. 36.10, “Base station (bs) radio transmission and reception,” tech. rep., 2013.
[50] R. I.-R. M.2135, “Guidelines for evaluation of radio interface technologies for imt-advanced,” tech. rep., 2008.
[51] S. Haykin, Communication Systems. Wiley, 4th ed., 2001.