[1] |
TULLBERG H, POPOVSKI P, LI Z, et al. The METIS 5G system concept: Meeting the 5G requirements[J]. IEEE Communications Magazine, 2016, 54(12): 132-139.
|
[2] |
DING Z, DAI L, POOR H V. MIMO-NOMA design for small packet transmission in the Internet of things[J]. IEEE Access, 2016, 4: 1393-1405.
|
[3] |
LIU Y, QIN Z, ELKASHLAN M, et al. Non-orthogonal multiple access for 5G and beyond[J]. arXiv Preprint 2018, arXiv:1808.00277.
|
[4] |
HONG J P, CHOI W, RAO B D. Sparsity controlled random multiple access with compressed sensing[J]. IEEE Transactions on Wireless Communications, 2015, 14(2): 998-1010.
|
[5] |
DONOHO D L. Compressed sensing[J]. IEEE Transactions on information theory, 2006, 52(4): 1289-1306.
|
[6] |
ZHU H, GIANNAKIS G B. Exploiting sparse user activity in multiuser detection[J]. IEEE Transactions on Communications, 2011, 59(2): 454-465.
|
[7] |
KNOOP B, MONSEES F, BOCKELMANN C, et al. Sparsity-aware successive interference cancellation with practical constraints[C]// 17th International ITG Workshop on Smart Antennas. StuTTGART, GERMANY:VDE, 2013: 1-8.
|
[8] |
GOMAA A, AL-DHAHIR N. A sparsity-aware approach for NBI estimation in MIMO-OFDM[J]. IEEE Transactions on Wireless Communications, 2011, 10(6): 1854-1862.
|
[9] |
KNOOP B, SCHMALE S, PETERS-DROLSHAGEN D, et al. Activity and channel estimation in multi-user wireless sensor networks[C]// 20th International ITG Workshop on Smart Antennas. Munich, Germany: VDE, 2016: 1-5.
|
[10] |
HANNAK G, MAYER M, JUNG A, et al. Joint channel estimation and activity detection for multiuser communication systems[C]//2015 IEEE International Conference on Communication Workshop. London: IEEE, 2015: 2086-2091.
|
[11] |
RANGAN S. Generalized approximate message passing for estimation with random linear mixing[C]//2011 IEEE International Symposium on Information Theory Proceedings. IEEE, 2011: 2168-2172.
|
[12] |
ZOU Q, ZHANG H, WEN C K, et al. Concise derivation for generalized approximate message passing using expectation propagation[J]. IEEE Signal Processing Letters, 2018, 25(12): 1835-1839.
|
[13] |
MINKA T P. Expectation propagation for approximate Bayesian inference[C]//Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence. Pittsburgh: Morgan Kaufmann Publishers Inc., 2001: 362-369.
|
[14] |
RASMUSSEN CE, WILLIAMS K I. Gaussian Process for Machine Learning[M]. The MIT Press, 2006.
|
[15] |
VILA J, SCHNITER P, RANGAN S, et al. Adaptive damping and mean removal for the generalized approximate message passing algorithm[C]//2015 IEEE International Conference on Acoustics, Speech and Signal Processing. Brisbane, Australia: IEEE, 2015: 2021-2025.
|
[16] |
CALTAGIRONE F, ZDEBOROV L, KRZAKALA F. On convergence of approximate message passing[C]//2014 IEEE International Symposium on Information Theory. Honolulu, USA:IEEE, 2014: 1812-1816.
|
[17] |
SCHNITER P, RANGAN S. Compressive phase retrieval via generalized approximate message passing[J]. IEEE Transactions on Signal Processing, 2015, 63(4): 1043-1055.
|
[18] |
BEYME S, LEUNG C. Efficient computation of DFT of Zadoff-Chu sequences[J]. Electronics letters, 2009, 45(9): 461-463.
|
[1] |
TULLBERG H, POPOVSKI P, LI Z, et al. The METIS 5G system concept: Meeting the 5G requirements[J]. IEEE Communications Magazine, 2016, 54(12): 132-139.
|
[2] |
DING Z, DAI L, POOR H V. MIMO-NOMA design for small packet transmission in the Internet of things[J]. IEEE Access, 2016, 4: 1393-1405.
|
[3] |
LIU Y, QIN Z, ELKASHLAN M, et al. Non-orthogonal multiple access for 5G and beyond[J]. arXiv Preprint 2018, arXiv:1808.00277.
|
[4] |
HONG J P, CHOI W, RAO B D. Sparsity controlled random multiple access with compressed sensing[J]. IEEE Transactions on Wireless Communications, 2015, 14(2): 998-1010.
|
[5] |
DONOHO D L. Compressed sensing[J]. IEEE Transactions on information theory, 2006, 52(4): 1289-1306.
|
[6] |
ZHU H, GIANNAKIS G B. Exploiting sparse user activity in multiuser detection[J]. IEEE Transactions on Communications, 2011, 59(2): 454-465.
|
[7] |
KNOOP B, MONSEES F, BOCKELMANN C, et al. Sparsity-aware successive interference cancellation with practical constraints[C]// 17th International ITG Workshop on Smart Antennas. StuTTGART, GERMANY:VDE, 2013: 1-8.
|
[8] |
GOMAA A, AL-DHAHIR N. A sparsity-aware approach for NBI estimation in MIMO-OFDM[J]. IEEE Transactions on Wireless Communications, 2011, 10(6): 1854-1862.
|
[9] |
KNOOP B, SCHMALE S, PETERS-DROLSHAGEN D, et al. Activity and channel estimation in multi-user wireless sensor networks[C]// 20th International ITG Workshop on Smart Antennas. Munich, Germany: VDE, 2016: 1-5.
|
[10] |
HANNAK G, MAYER M, JUNG A, et al. Joint channel estimation and activity detection for multiuser communication systems[C]//2015 IEEE International Conference on Communication Workshop. London: IEEE, 2015: 2086-2091.
|
[11] |
RANGAN S. Generalized approximate message passing for estimation with random linear mixing[C]//2011 IEEE International Symposium on Information Theory Proceedings. IEEE, 2011: 2168-2172.
|
[12] |
ZOU Q, ZHANG H, WEN C K, et al. Concise derivation for generalized approximate message passing using expectation propagation[J]. IEEE Signal Processing Letters, 2018, 25(12): 1835-1839.
|
[13] |
MINKA T P. Expectation propagation for approximate Bayesian inference[C]//Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence. Pittsburgh: Morgan Kaufmann Publishers Inc., 2001: 362-369.
|
[14] |
RASMUSSEN CE, WILLIAMS K I. Gaussian Process for Machine Learning[M]. The MIT Press, 2006.
|
[15] |
VILA J, SCHNITER P, RANGAN S, et al. Adaptive damping and mean removal for the generalized approximate message passing algorithm[C]//2015 IEEE International Conference on Acoustics, Speech and Signal Processing. Brisbane, Australia: IEEE, 2015: 2021-2025.
|
[16] |
CALTAGIRONE F, ZDEBOROV L, KRZAKALA F. On convergence of approximate message passing[C]//2014 IEEE International Symposium on Information Theory. Honolulu, USA:IEEE, 2014: 1812-1816.
|
[17] |
SCHNITER P, RANGAN S. Compressive phase retrieval via generalized approximate message passing[J]. IEEE Transactions on Signal Processing, 2015, 63(4): 1043-1055.
|
[18] |
BEYME S, LEUNG C. Efficient computation of DFT of Zadoff-Chu sequences[J]. Electronics letters, 2009, 45(9): 461-463.
|