Abstract
Multiuser multiple-input multiple-output (MU-MIMO) cognitive radio (CR) systems can achieve higher spectral efficiency by multiplexing multiple users on the same time-frequency resources and allowing concurrent spectrum sharing instead of opportunistic sharing. MU-MIMO techniques have been successfully deployed in 4G cellular systems based on traditional static spectrum access approach, and a vast number of multiuser detection algorithms, such as maximum ratio combining (MRC), minimum mean-squared error (MMSE), and capacity-aware (CA) are presently being tailored toward solving the MIMO processing in cognitive networks, where additional constraints are imposed to protect licensed users’ QoS. The focus in this chapter is on concurrent CR networks based on CA MU-MIMO that maximizes the uplink MIMO channel capacity for each cognitive user while controlling the interference levels to licensed users. Two applications of CA MU-MIMO will be explored: cognitive radio-based wireless sensor networks (CR-WSNs) and cognitive small cells in heterogeneous networks (HetNets).
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References
Mitola J, Maguire GQ (1999) Cognitive radio: making software radios more personal. IEEE Pers Commun 6(6):13–18
Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Select Areas Commun 23(2):201–220
Munster M, Hanzo L (2001) Performance of SDMA multi-user detection techniques for Walsh-Hadamard-spread OFDM schemes. IEEE-VTC 4:2319–2323
Kang M (2004) A comparative study on the performance of MIMO MRC systems with and without cochannel interference. IEEE Trans Commun 52(8):1417–1425
Sulyman I, Hefnawi M (2008) Adaptive MIMO beamforming algorithm based on gradient search of the channel capacity in OFDMSDMA system. IEEE Commun Lett 12(9):642–644
Sulyman I, Hefnawi M (2010a) Performance evaluation of capacity-aware MIMO beamforming schemes in OFDM-SDMA systems. IEEE Trans Commun 58(1)
Sulyman I, Hefnawi M (2010b) Capacity-aware linear MMSE detector for OFDM-SDMA systems. IET Commun 4(9)
Yang LL, Wang LC (2008) Zero-forcing and minimum Mean-Square error multiuser detection in generalized multicarrier DS-CDMA Systems for Cognitive Radio. EURASIP J Wirel Commun Netw:1–13
Zhang R, Liang YC (2008) Exploiting multi-antennas for opportunistic spectrum sharing in cognitive radio networks. IEEE J Sel Top Sign Proces 2(1):88–102
Vu M, Yiu S, Tarokh V (2008) Interference reduction by beamforming in cognitive networks. In: IEEE GLOBECOM Telecom. Conference
Hamdi K, Zhang W, Letaief KB (2009) Opportunistic spectrum sharing in cognitive MIMO wireless networks. IEEE Trans Wirel Commun 8(8):4098–4109
Hefnawi M (2012) SDMA aided cognitive radio networks. In: IEEE 26th Biennial symposium on communications
Hefnawi M (2014) SER performance of large scale OFDM-SDMA based cognitive radio networks. Int J Antennas Propag:1–8
Hefnawi M, Abubaker A (2014) Channel capacity maximization in multiuser large scale MIMO-based cognitive networks. Int J Microwave Opt Technol 9(6):437–444
Bixio L, Oliveri G, Ottonello M et al (2010) Cognitive radios with multiple antennas exploiting spatial opportunities. IEEE Trans Signal Process 58(8):4453–4459
Wang L, Quoc NH, Elkashlan M et al (2017) Massive MIMO in Spectrum sharing networks: achievable rate and power efficiency. IEEE Syst 11(1):20–31
Nguyen VD, Tran LN, Duong TQ et al (2017) An efficient precoder design for multiuser MIMO cognitive radio networks with interference constraints. IEEE Trans Veh Technol 66(5):3991–4004
Deng HJ, Chen SH, KU ML (2017) Multiuser MIMO Precoders with proactive primary interference cancelation and link quality enhancement for cognitive radio relay systems. IEEE Access 5:17701–17712
Marzetta L (2010) Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Tran Wirel Comm 9(11):3590–3600
Rusek F, Persson D, Lau B, Larsson E, Marzetta et al (2013) Scaling up MIMO: opportunities and challenges with very large arrays. IEEE Signal Process Mag 30(1):40–60
Ngo HQ, Larsson EG, Marzetta TL (2013) Energy and spectral efficiency of very large multiuser MIMO systems. IEEE Trans Commun 61(4):1436–1449
Hoydis J, ten Brink S, Debbah M (2013) Massive MIMO in the UL/DL of cellular networks: how many antennas do we need? IEEE J Sel Areas Commun 31(2):160–171
Hefnawi M (2016) Large-scale multi-cluster MIMO approach for cognitive radio sensor networks. IEEE Sensors J 16(11):4418–4424
Coso D, Spagnolini U, Ibars C (2007) Cooperative distributed MIMO channels in wireless sensor networks. IEEE J Sel Areas Commun 25(2):402–414
Cui S, Goldsmith AJ, Bahai A (2004) Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks. IEEE J Sel Areas Commun 22(6):1089–1098
Jayaweera SK (2006) Virtual MIMO-based cooperative communication for energy-constrained wireless sensor networks. IEEE Trans Wirel Commun 5(5):984–989
Yuan Y, He Z (2006) Virtual MIMO-based cross-layer design for wireless sensor networks. Vehicular Technol IEEE Trans 55(3):856–864
Vijay G, Bdira BA, Ibnkahla M (2011) Cognition in wireless sensor networks: a perspective. IEEE Sensor J 11:582–592
Akan OB, Karli OB, Ergul O (2009) Cognitive radio sensor networks. IEEE Netw 23:34–40
Hefnawi M (2017) Channel maximization in wireless backhaul based HetNets. Int J Wirel Mobile Netw 9(3):51–60
Siddique U, Tabassum H, Hossain E, Kim DI (2015) Wireless backhauling of 5G small cells: challenges and solution approaches. IEEE Wirel Commun 22(5):22–31
Gao Z, Dai L, Mi D et al (2015) MmWave massive MIMO based wireless backhaul for 5G ultra-dense network. IEEE Wirel Commun 22(5):13–21
Tabassum H, Hamdi SA, Hossain E (2016) Analysis of massive MIMO-enabled downlink wireless backhauling for full-duplex small cells. IEEE Trans Commun 64(6):2354–2369
Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of the IEEE conference on neural networks
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Hefnawi, M. (2019). Multiuser MIMO Cognitive Radio Systems. In: Rehmani, M., Dhaou, R. (eds) Cognitive Radio, Mobile Communications and Wireless Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-91002-4_11
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DOI: https://doi.org/10.1007/978-3-319-91002-4_11
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