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Distributed MIMO Systems Based on Quantize-Map-and-Forward (QMF) Relaying
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 Title & Authors
Distributed MIMO Systems Based on Quantize-Map-and-Forward (QMF) Relaying
Hong, Bi; Choi, Wan;
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 Abstract
Exploiting multiple antennas at mobile devices is difficult due to limited size and power. In this paper, a distributed MIMO protocol achieving the capacity of conventinal MIMO systems is proposed and analyzed. For exploiting distributed MIMO features, Quantize-Map-and-Forward (QMF) scheme shows improved performance than Amplify-and-Forward (AF) scheme. Also, the protocol based on multiple access channel (MAC) is proposed to improve the multiplexing gain. We showed that sufficient condition of the number of slave nodes to achieve the gain of a MAC based protocol. Because the base station can support multiple clusters operating in distributed MIMO, the total cellular capacity can be extremely enhanced in proportional to the number of clusters.
 Keywords
Distributed Multiple-Input Multiple-Output (MIMO);quantize-map-and-forward (QMF);compress-and-forward (CF);spatial reuse;user relaying;
 Language
Korean
 Cited by
1.
On the Characteristics of MSE-Optimal Symmetric Scalar Quantizers for the Generalized Gamma, Bucklew-Gallagher, and Hui-Neuhoff Sources,이재건;나상신;

한국통신학회논문지, 2015. vol.40. 7, pp.1217-1233 crossref(new window)
 References
1.
Cisco, Visual Networking Index: Global Mobile Data Forecast Update 2013-2018. Feb. 5, 2014.

2.
G. J. Foschini, "Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas," AT&T Bell Labs. Tech. J., vol. 1, no. 2, pp. 41-59, 1996.

3.
E. Telatar, "Capacity of multi-antenna Gaussian channels," Europ. Trans. Telecommun., vol. 10, no. 6, pp. 585-596, Nov. 1999. crossref(new window)

4.
C.-N. Chuah , D. N. C. Tse, J. M. Kahn, and R. A. Valenzuela "Capacity scaling in MIMO wireless systems under correlated fading," IEEE Trans. Inf. Theory, vol. 48, no. 3, pp. 637-650, 2002. crossref(new window)

5.
H. Shin and J. H. Lee "Capacity of multiple-antenna fading channels: Spatial fading correlation, double scattering, and keyhole," IEEE Trans. Inform. Theory, vol. 49, no. 10, pp. 2636-2647, 2003. crossref(new window)

6.
A. Ozgur, O. Leveque, and D. N. C. Tse, "Hierarchical cooperation achieves optimal capacity scaling in ad hoc networks," IEEE Trans. Inf. Theory, vol. 53, no. 10, pp. 3549-3572, Oct. 2007. crossref(new window)

7.
F. Quitin, M. M. U. Rahman, R. Mudumbai, and U. Madhow, "A scalable architecture for distributed transmit beamforming with commodity radios: Design and proof of concept," IEEE Trans. Wirel. Commun., vol. 12, no. 3, pp. 1418-1428, Mar. 2013. crossref(new window)

8.
R. Mudumbai, D. R. Brown III, U. Madhow, and H. V. Poor, "Distributed Transmit Beamforming: Challenges and Recent Progress," IEEE Commun. Mag., vol. 47, no. 2, pp. 102-110, Feb. 2009.

9.
S. Pawar, A. S. Avestimehr, and D. N. C. Tse, "Diversity-multiplexing tradeoff of the half-duplex relay channel," in Proc. Allerton Conf. Commun., Control Comput., Monticello, IL, Sept. 2008.

10.
A. S. Avestimehr, S. N. Diggavi and D. Tse, "Wireless network information flow: A deterministic approach," IEEE Trans. Inf. Theory, vol. 57, no. 4, pp. 1872-1905, Apr. 2011. crossref(new window)

11.
A. Ozgur and S N. Diggavi, "Approximately achieving Gaussian relay network capacity with lattice codes," in Proc. IEEE ISIT, pp. 669-673, Austin, Texas, Jun. 2010.