TY - GEN
T1 - Structured matching pursuit for reconstruction of dynamic sparse channels
AU - Zhu, Xudong
AU - Dai, Linglong
AU - Gui, Guan
AU - Dai, Wei
AU - Wang, Zhaoceng
AU - Adachi, Fumiyuki
N1 - Funding Information:
This work was supported by Beijing Natural Science Foundation (Grant No. 4142027), grant-in-aid for the Japan Society for the Promotion of Science (JSPS) fellows (Grant No. 2402366), and National Natural Science Foundation of China (Grant Nos. 61271266 and 61411130156)
Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - In this paper, by exploiting the special features of temporal correlations of dynamic sparse channels that path delays change slowly over time but path gains evolve faster, we propose the structured matching pursuit (SMP) algorithm to realize the reconstruction of dynamic sparse channels. Specifically, the SMP algorithm divides the path delays of dynamic sparse channels into two different parts to be considered separately, i.e., the common channel taps and the dynamic channel taps. Based on this separation, the proposed SMP algorithm simultaneously detects the common channel taps of dynamic sparse channels in all time slots at first, and then tracks the dynamic channel taps in each single time slot individually. Theoretical analysis of the proposed SMP algorithm provides a guarantee that the common channel taps can be successfully detected with a high probability, and the reconstruction distortion of dynamic sparse channels is linearly upper bounded by the noise power. Simulation results demonstrate that the proposed SMP algorithm has excellent reconstruction performance with competitive computational complexity compared with conventional reconstruction algorithms.
AB - In this paper, by exploiting the special features of temporal correlations of dynamic sparse channels that path delays change slowly over time but path gains evolve faster, we propose the structured matching pursuit (SMP) algorithm to realize the reconstruction of dynamic sparse channels. Specifically, the SMP algorithm divides the path delays of dynamic sparse channels into two different parts to be considered separately, i.e., the common channel taps and the dynamic channel taps. Based on this separation, the proposed SMP algorithm simultaneously detects the common channel taps of dynamic sparse channels in all time slots at first, and then tracks the dynamic channel taps in each single time slot individually. Theoretical analysis of the proposed SMP algorithm provides a guarantee that the common channel taps can be successfully detected with a high probability, and the reconstruction distortion of dynamic sparse channels is linearly upper bounded by the noise power. Simulation results demonstrate that the proposed SMP algorithm has excellent reconstruction performance with competitive computational complexity compared with conventional reconstruction algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84964900937&partnerID=8YFLogxK
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U2 - 10.1109/GLOCOM.2014.7416980
DO - 10.1109/GLOCOM.2014.7416980
M3 - Conference contribution
AN - SCOPUS:84964900937
T3 - 2015 IEEE Global Communications Conference, GLOBECOM 2015
BT - 2015 IEEE Global Communications Conference, GLOBECOM 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th IEEE Global Communications Conference, GLOBECOM 2015
Y2 - 6 December 2015 through 10 December 2015
ER -