Sparse Representation for Wireless Communications: A Compressive Sensing Approach

IEEE Signal Processing Magazine

Volumn 35, Issue 3, 2018, Pages 40-58

  Qin, Zhijin ^a   Fan, Jiancun ^b   Liu, Yuanwei ^c   Gao, Yue ^c   Li, Geoffrey Ye ^d  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b XI'AN JIAOTONG UNIVERSITY   (China)

^c QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

^d GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

5G MOBILE COMMUNICATION SYSTEMS; ENERGY EFFICIENCY; INTERNET OF THINGS; WIRELESS TELECOMMUNICATION SYSTEMS;

COMPRESSIVE SENSING; FIFTH GENERATION (5G); INTERNET OF THINGS (IOT); MODEL SIGNALS; SPARSE REPRESENTATION; SPECTRUM EFFICIENCY; WIRELESS COMMUNICATIONS;

COMPRESSED SENSING;

EID: 85044521828     PISSN: 10535888     EISSN: None     Source Type: Journal    
DOI: 10.1109/MSP.2018.2789521     Document Type: Article

References (75)

1. M. Zibulevsky and M. Elad, "L1-L2 optimization in signal and image processing, " IEEE Signal Process. Mag., vol. 27, no. 3, pp. 76-88, May 2010.
2. A. M. Bruckstein, D. L. Donoho, and M. Elad, "From sparse solutions of systems of equations to sparse modeling of signals and images, " SIAM Rev., vol. 51, no. 1, pp. 34-81, Feb. 2009.
3. E. Candès, "Compressive sampling, " in Proc. Int. Congr. Mathematics, vol. 3, Madrid, Spain, Oct. 2006, pp. 1433-1452.
4. E. J. Candès, J. Romberg, and T. Tao, "Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information, " IEEE Trans. Inf. Theory, vol. 52, no. 2, pp. 489-509, Feb. 2006.
5. Z. Qin, Y. Gao, and C. G. Parini, "Data-assisted low complexity compressive spectrum sensing on real-time signals under sub-Nyquist rate, " IEEE Trans. Wireless Commun., vol. 15, no. 2, pp. 1174-1185, Feb. 2016.
6. Z. Qin, Y. Gao, M. D. Plumbley, and C. G. Parini, "Wideband spectrum sensing on real-time signals at sub-Nyquist sampling rates in single and cooperative multiple nodes, " IEEE Trans. Signal Process., vol. 64, no. 12, pp. 3106-3117, June 2016.
7. W. Chen and I. J. Wassell, "Energy-efficient signal acquisition in wireless sensor networks: A compressive sensing framework, " IET Wireless Sensor Syst., vol. 2, no. 1, pp. 1-8, Mar. 2012.
8. X. Rao and V. K. Lau, "Compressive sensing with prior support quality information and application to massive MIMO channel estimation with temporal correlation, " IEEE Trans. Signal Process., vol. 63, no. 18, pp. 4914-4924, Sept. 2015.
9. E. J. Candès and M. B. Wakin, "An introduction to compressive sampling, " IEEE Signal. Process. Mag., vol. 25, no. 2, pp. 21-30, Mar. 2008.
10. C. R. Berger, Z. Wang, J. Huang, and S. Zhou, "Application of compressive sensing to sparse channel estimation, " IEEE Commun. Mag., vol. 48, no. 11, pp. 164-174, Nov. 2010.
11. S. K. Sharma, E. Lagunas, S. Chatzinotas, and B. Ottersten, "Application of compressive sensing in cognitive radio communications: A survey, " Commun. Surveys Tuts., vol. 18, no. 3, pp. 1838-1860, 2016.
12. D. Romero, D. D. Ariananda, Z. Tian, and G. Leus, "Compressive covariance sensing: Structure-based compressive sensing beyond sparsity, " IEEE Signal Process. Mag., vol. 33, no. 1, pp. 78-93, Jan. 2016.
13. H. S. Chang, Y. Weiss, and W. T. Freeman, "Informative sensing of natural images, " in Proc. IEEE Int. Conf. Image Processing (ICIP), Cairo, Egypt, Nov. 2009, pp. 3025-3028.
14. J. Wright, Y. Ma, J. Mairal, G. Sapiro, T. S. Huang, and S. Yan, "Sparse representation for computer vision and pattern recognition, " Proc. IEEE, vol. 98, no. 6, pp. 1031-1044, June 2010.
15. H. S. Chang, Y. Weiss, and W. T. Freeman. (2009). Informative sensing. CoRR. [Online]. Available: http://arxiv. org/abs/0901. 4275
16. E. Candès and J. Romberg, "Sparsity and incoherence in compressive sampling, " Inverse Problems, vol. 23, no. 3, pp. 969-985, Apr. 2007.
17. J. Tropp, J. Laska, M. Duarte, J. Romberg, and R. Baraniuk, "Beyond Nyquist: Efficient sampling of sparse bandlimited signals, " IEEE Trans. Inf. Theory, vol. 56, no. 1, pp. 520-544, Jan. 2010.
18. E. J. Candès. (2008). The restricted isometry property and its implications for compressed sensing. Comptes Rendus Mathematique. [Online]. 346(9), pp. 589-592. Available: http://www. sciencedirect. com/science/article/pii/S1631073X 08000964
19. J. A. Tropp and A. C. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit, " IEEE Trans. Inf. Theory, vol. 53, no. 12, pp. 4655-4666, Dec. 2007.
20. J. W. Choi, B. Shim, Y. Ding, B. Rao, and D. I. Kim, "Compressed sensing for wireless communications: Useful tips and tricks, " Commun. Surveys Tuts., vol. 19, no. 3, pp. 1527-1550, 2017.
21. B. D. Rao and K. Kreutz-Delgado, "An affine scaling methodology for best basis selection, " IEEE Trans. Signal Process., vol. 47, no. 1, pp. 187-200, Jan. 1999.
22. R. Chartrand, "Exact reconstruction of sparse signals via nonconvex minimization, " IEEE Signal Process. Lett., vol. 14, no. 10, pp. 707-710, Oct. 2007.
23. R. Chartrand and V. Staneva, "Restricted isometry properties and nonconvex compressive sensing, " Inverse Problems, vol. 24, no. 3, May 2008. doi: 10. 1088/0266-5611/24/3/035020.
24. R. Chartrand and W. Yin, "Iteratively reweighted algorithms for compressive sensing, " in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP), Las Vegas, NV, Mar. 2008, pp. 3869-3872.
25. D. Baron, M. F. Duarte, M. B. Wakin, S. Sarvotham, and R. G. Baraniuk, "Distributed compressive sensing, " 2009.
26. Y.-C. Liang, Y. Zeng, E. Peh, and A. T. Hoang, "Sensing-throughput tradeoff for cognitive radio networks, " IEEE Trans. Wireless Commun., vol. 7, no. 4, pp. 1326-1337, Apr. 2008.
27. H. Sun, A. Nallanathan, C.-X. Wang, and Y. Chen, "Wideband spectrum sensing for cognitive radio networks: A survey, " Wireless Commun., vol. 20, no. 2, pp. 74-81, Mar. 2013.
28. Z. Tian and G. Giannakis, "Compressed sensing for wideband cognitive radios, " in Proc. IEEE Int. Conf. Acousics, Speech, and Signal Processing (ICASSP), Honolulu, HI, Apr. 2007, pp. 1357-1360.
29. M. A. Davenport, J. N. Laska, J. R. Treichler, and R. G. Baraniuk, "The pros and cons of compressive sensing for wideband signal acquisition: Noise folding versus dynamic range, " IEEE Trans. Signal Process., vol. 60, no. 9, pp. 4628-4642, Sept. 2012.
30. Y. Wang, Z. Tian, and C. Feng, "Sparsity order estimation and its application in compressive spectrum sensing for cognitive radios, " IEEE Trans. Wireless Commun., vol. 11, no. 6, pp. 2116-2125, June 2012.
31. H. Sun, W.-Y. Chiu, and A. Nallanathan, "Adaptive compressive spectrum sensing for wideband cognitive radios, " IEEE Commun. Lett., vol. 16, no. 11, pp. 1812-1815, Nov. 2012.
32. Y. L. Polo, Y. Wang, A. Pandharipande, and G. Leus, "Compressive wide-band spectrum sensing, " in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), Taipei, Taiwan, Apr. 2009, pp. 2337-2340.
33. M. A. Lexa, M. E. Davies, J. S. Thompson, and J. Nikolic, "Compressive power spectral density estimation, " in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), Prague, Czech Republic, May 2011, pp. 3884-3887.
34. G. Leus and D. D. Ariananda, "Power spectrum blind sampling, " IEEE Signal Process. Lett., vol. 18, no. 8, pp. 443-446, Aug. 2011.
35. D. D. Ariananda and G. Leus, "Compressive wideband power spectrum estimation, " IEEE Trans. Signal Process., vol. 60, no. 9, pp. 4775-4789, Sept. 2012.
36. D. Cohen and Y. C. Eldar, "Sub-Nyquist sampling for power spectrum sensing in cognitive radios: A unified approach, " IEEE Trans. Signal Process., vol. 62, no. 15, pp. 3897-3910, Aug. 2014.
37. F. Zeng, C. Li, and Z. Tian, "Distributed compressive spectrum sensing in cooperative multihop cognitive networks, " IEEE J. Sel. Topics Signal Process., vol. 5, no. 1, pp. 37-48, Feb. 2011.
38. Z. Qin, Y. Gao, and M. D. Plumbley, "Malicious user detection based on lowrank matrix completion in wideband spectrum sensing, " IEEE Trans. Signal Process., vol. 66, no. 1, pp. 5-17, Jan. 2018.
39. Y. Liu and Q. Wan, "Enhanced compressive wideband frequency spectrum sensing for dynamic spectrum access, " EURASIP J. Advances Signal Process., vol. 2012, no. 177, Dec. 2012. doi: 10. 1186/1687-6180-2012-177.
40. Y. C. Eldar, P. Kuppinger, and H. Bolcskei, "Block-sparse signals: Uncertainty relations and efficient recovery, " IEEE Trans. Signal Process., vol. 58, no. 6, pp. 3042-3054, June 2010.
41. D. Romero and G. Leus, "Wideband spectrum sensing from compressed measurements using spectral prior information, " IEEE Trans. Signal Process., vol. 61, no. 24, pp. 6232-6246, Dec. 2013.
42. L. Kong, D. Zhang, Z. He, Q. Xiang, J. Wan, and M. Tao, "Embracing big data with compressive sensing: A green approach in industrial wireless networks, " IEEE Commun. Mag., vol. 54, no. 10, pp. 53-59, Oct. 2016.
43. Z. Qin, Y. Liu, Y. Gao, M. Elkashlan, and A. Nallanathan, "Wireless powered cognitive radio networks with compressive sensing and matrix completion, " IEEE Trans. Commun., vol. 65, no. 4, pp. 1464-1476, Apr. 2017.
44. W. Chen and I. J. Wassell, "Optimized node selection for compressive sleeping wireless sensor networks, " IEEE Trans. Veh. Technol., vol. 65, no. 2, pp. 827-836, Feb. 2016.
45. W. Chen and I. J. Wassell, "Cost-aware activity scheduling for compressive sleeping wireless sensor networks, " IEEE Trans. Signal Process., vol. 64, no. 9, pp. 2314-2323, May 2016.
46. Q. Ling and Z. Tian, "Decentralized sparse signal recovery for compressive sleeping wireless sensor networks, " IEEE Trans. Signal Process., vol. 58, no. 7, pp. 3816-3827, July 2010.
47. C. Caione, D. Brunelli, and L. Benini, "Distributed compressive sampling for lifetime optimization in dense wireless sensor networks, " IEEE Trans. Ind. Informat., vol. 8, no. 1, pp. 30-40, Feb. 2012.
48. T. L. Marzetta, "Noncooperative cellular wireless with unlimited numbers of base station antennas, " IEEE Trans. Wireless Commun., vol. 9, no. 11, pp. 3590-3600, Nov. 2010.
49. A. Liu, F. Zhu, and V. K. Lau, "Closed-loop autonomous pilot and compressive CSIT feedback resource adaptation in multi-user FDD massive MIMO systems, " IEEE Trans. Signal Process., vol. 65, no. 1, pp. 173-183, Jan. 2017.
50. V. K. Lau, S. Cai, and A. Liu, "Closed-loop compressive CSIT estimation in FDD massive MIMO systems with 1 bit feedback, " IEEE Trans. Signal Process., vol. 64, no. 8, pp. 2146-2155, Apr. 2016.
51. A. Alkhateeb, O. El Ayach, G. Leus, and R. W. Heath, "Channel estimation and hybrid precoding for millimeter wave cellular systems, " IEEE J. Sel. Topics Signal. Process., vol. 8, no. 5, pp. 831-846, 2014.
52. Z. Marzi, D. Ramasamy, and U. Madhow, "Compressive channel estimation and tracking for large arrays in mm-wave picocells, " IEEE J. Sel. Topics Signal. Process., vol. 10, no. 3, pp. 514-527, 2016.
53. J. Song, J. Choi, and D. J. Love, "Common codebook millimeter wave beam design: Designing beams for both sounding and communication with uniform planar arrays, " IEEE Trans. Commun., vol. 65, no. 4, pp. 1859-1872, 2017.
54. G. Wang, S. A. Naeimi, and G. Ascheid, "Low complexity channel estimation based on DFT for short range communication, " in Proc. IEEE Int. Conf. Communication (ICC), 2017, pp. 1-7.
55. W. Shen, L. Dai, Y. Shi, X. Zhu, and Z. Wang, "Compressive sensing-based differential channel feedback for massive MIMO, " Electr. Lett., vol. 51, no. 22, pp. 1824-1826, Oct. 2015.
56. Y. Han, J. Lee, and D. J. Love, "Compressed sensing-aided downlink channel training for FDD massive MIMO systems, " IEEE Trans. Commun., vol. 65, no. 7, pp. 2852-2862, July 2017.
57. L. Lu, G. Li, A. Swindlehurst, A. Ashikhmin, and R. Zhang, "An overview of massive MIMO: Benefits and challenges, " IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, pp. 742-758, Oct. 2014.
58. C. C. Tseng, J. Y. Wu, and T. S. Lee, "Enhanced compressive downlink CSI recovery for FDD massive MIMO systems using weighted block-minimization, " IEEE Trans. Commun., vol. 64, no. 3, pp. 1055-1067, Mar. 2016.
59. M. S. Sim, J. Park, C.-B. Chae, and R. W. Heath, "Compressed channel feedback for correlated massive MIMO systems, " J. Commun. Netw., vol. 18, no. 1, pp. 95-104, Feb. 2016.
60. W. Shen, L. Dai, Y. Shi, B. Shim, and Z. Wang, "Joint channel training and feedback for FDD massive MIMO systems, " IEEE Trans. Veh. Technol., vol. 65, no. 10, pp. 8762-8767, Oct. 2016.
61. X.-L. Huang, J. Wu, Y. Wen, F. Hu, Y. Wang, and T. Jiang, "Rate-adaptive feedback with Bayesian compressive sensing in multiuser MIMO beamforming systems, " IEEE Trans. Wireless Commun., vol. 15, no. 7, pp. 4839-4851, July 2016.
62. P.-H. Kuo, H. Kung, and P.-A. Ting, "Compressive sensing based channel feedback protocols for spatially-correlated massive antenna arrays, " in Proc. Wireless Communication Network Conf. (WCNC), Paris, France, Apr. 2012, pp. 492-497.
63. K. Venugopal, N. Gonzlez-Prelcic, and R. W. Heath, "Optimality of frequency flat precoding in frequency selective millimeter wave channels, " IEEE Wireless Commun. Lett., vol. 6, no. 3, pp. 330-333, June 2017.
64. J. Mirza, B. Ali, S. S. Naqvi, and S. Saleem, "Hybrid precoding via successive refinement for millimeter wave MIMO communication systems, " IEEE Commun. Lett., vol. 21, no. 5, May 2017.
65. Z. Gao, L. Dai, Z. Wang, S. Chen, and L. Hanzo, "Compressive-sensing-based multiuser detector for the large-scale SM-MIMO uplink, " IEEE Trans. Veh. Technol., vol. 65, no. 10, pp. 8725-8730, Oct. 2016.
66. Y. Nan, L. Zhang, and X. Sun, "Efficient downlink channel estimation scheme based on block-structured compressive sensing for TDD massive MU-MIMO systems, " IEEE Wireless Commun. Lett., vol. 4, no. 4, pp. 345-348, Aug. 2015.
67. A. B. Ramirez, R. E. Carrillo, G. Arce, K. E. Barner, and B. Sadler, "An overview of robust compressive sensing of sparse signals in impulsive noise, " in Proc. European Signal Processing Conf. (EUSIPCO), Aug. 2015, pp. 2859-2863.
68. Y. Shi, J. Zhang, and K. B. Letaief, "Group sparse beamforming green cloud-RAN, " IEEE Trans. Wireless Commun., vol. 13, no. 5, pp. 2809-2823, May 2014.
69. B. Dai and W. Yu, "Sparse beamforming and user-centric clustering for downlink cloud radio access network, " IEEE Access, vol. 2, pp. 1326-1339, Oct. 2014.
70. X. Xu, X. Rao, and V. K. N. Lau, "Active user detection and channel estimation in uplink CRAN systems, " in Proc. IEEE Int. Conf. Communication (ICC), London, June 2015, pp. 2727-2732.
71. R. Baraniuk, "Compressive sensing [Lecture Notes], " IEEE Signal Process. Mag., vol. 24, no. 4, pp. 118-121, July 2007.
72. B. Bah and J. Tanner, "Improved bounds on restricted isometry constants for gaussian matrices, " SIAM J. Matrix Anal. Appl., vol. 31, no. 5, pp. 2882-2898, 2010.
73. Y. Gao and Z. Qin, "Implementation of compressive sensing with real-time signals over TV white space spectrum in cognitive radio, " in Proc. IEEE Vehicle Technology Conf. (VTC-Fall), Montréal, Canada, Sept. 2016, pp. 1-5.
74. B. Sun and H. Feng, "Efficient compressed sensing for wireless neural recording: A deep learning approach, " IEEE Signal Process. Lett., vol. 24, no. 6, pp. 863-867, June 2017.
75. C. Dwork, F. McSherry, K. Nissim, and A. Smith, "Calibrating noise to sensitivity in private data analysis, " in Proc. Theory Cryptography, Springer, 2006, pp. 265-284.