•  
  •  
 

Al-Bahir Journal for Engineering and Pure Sciences

Abstract

Next generation wireless systems are characterized by very high transmission bit rates which gives rise to severe Intersymbol interference (ISI) and this makes the detection process very challenging. Hence, assessment of performance of near-optimal detectors like Near Maximum Likelihood Detectors (NMLD) over such channels assumes great importance. This paper deals with the detection of data in the presence of Noise and ISI with NMLD. Performance improvement of NMLD, as compared to nonlinear equalization, has been assessed in terms of BER versus SNR curves obtained through computer simulation. A number of different cases of mobile radio channels have been simulated in this work. In current world the lot of congestion leads severe fading and interference in the channel which may give the pause in data streaming and call drop in voice calling. These channels have different number of reflected paths with different power distribution in the respective paths. The aim of this paper is to take a ‘worst case’ model of a mobile radio channel in terms of rapidity of fading and ISI, and then to investigate the performance of detectors in the receivers.

References

  1. Bharathiraja N, Padmaja Pydimarri, Rajeshwari SB, Kallimani Jagadish S, Buttar Ahmed Mateen, Lingaiah T Bheema. Elite oppositional farmland fertility optimization based node localization technique for wireless networks. Wireless Commun Mobile Comput 2022;2022:9. https://doi.org/10.1155/2022/5290028. Article ID 5290028.
  2. Raj R, Jaiswal S, Dixit A. Dimming-based modulation schemes for visible light communication: spectral analysis and ISI mitigation. In: IEEE open journal of the communications society. vol. 2; 2021. p. 1777e98. https://doi.org/10.1109/OJCOMS.2021.3098105.
  3. Anand M, Antonidoss A, Balamanigandan R, et al. Resourceful routing algorithm for mobile Ad-Hoc network to enhance energy utilization. Wireless Pers Commun 2021. https://doi.org/10.1007/s11277-021-08570-5.
  4. Hasan Mohammad Kamrul, Sarwar Hosain Md, Saha Tonusree, Islam Shayla, Paul Liton Chandra, Khatak Satish, et al. Energy efficient data detection with low complexity for an uplink multi-user massive MIMO system. Comput Electr Eng 2022;101:108045. https://doi.org/10.1016/j.compeleceng.2022.108045. ISSN 0045-7906.
  5. Li Y, Cheng X, Zhang N. Deterministic and stochastic simulators for non-isotropic V2V-MIMO wideband channels. China Commun July 2018;15(7):18e29. https://doi.org/10.1109/CC.2018.8424579.
  6. Kamurthi RT, Chopra SR, Gupta A. Higher order QAM schemes in 5G UFMC system. In: 2020 international conference on emerging smart computing and informatics (ESCI); 2020. p. 198e202. https://doi.org/10.1109/ESCI48226.2020.9167619.
  7. Salim Beg M. Recent developments in digital cellular with special reference to GSM. In: Proc. Int. Wireless and telecommunications symp. Selangor, Malaysia: Shah Alam; May 1998. p. 396e9.
  8. Salim Beg M, Muhayiddin Mohd-Nazri. Receiver signal processing for next generation wideband digital cellular systems. In: Proc. Int. Wireless and telecommunications symp. Selangor, Malaysia: Shah Alam; May 1998. p. 396e9.
  9. Israil M, Beg MS. NML detection processes for some outdoor vehicular environments. In: 2009 international multimedia, signal processing and communication technologies; 2009. p. 296e9. https://doi.org/10.1109/MSPCT.2009.5164234.
  10. Bhat M, Salim Beg M. Computer simulation and modeling of high speed data transmission over mobile radio links. J Inst Eng Sept. 1996;77:20e3.
  11. Amiri MM, Gündüz D. Federated learning over wireless fading channels. IEEE Trans Wireless Commun May 2020;19(5):3546e57.https://doi.org/10.1109/TWC.2020.2974748.
  12. Salim Beg M, Tan SC, Hamidi Hazemi. Performance assessment of some adaptive equalizers in mobile radio environments.In: Proc.Int.Symposium.On wireless personal multimedia communications.Thailand,Nov: Bangkok;2000.p.761e6.
  13. Wang Tau,Vimel K,Dubey,Ong Teong.Generation of scattering function for mobile communication channel: a computer simulation approach.Int J Wireless Inf Network1997;3(3).
  14. Choi J, Mo J, Heath RW.Near maximum-likelihood detector and channel estimator for uplink Multiuser massive MIMO systems with one-bit ADCs.IEEE Trans CommunMay 2016;64(5):2005e18.https://doi.org/10.1109/TCOMM. 2016.2545666.
  15. Schreiber Fabio A,Falleni Marcello L.Analysis of data transmission performance over a GSM cellular network.In:IEEE proceedings of the thirtieth annual Hawwaii international on system sciences;1997.
  16. Clark AP,Jayasinghe SG.Channel estimation of land mobile radio systems.In:IEE Proc,vol. 134;July1987.p383e93.
  17. Sexton TA,Pahlavan K.Channel modeling and adaptive equalization of indoor radio channels.IEEE J Sel Area Commun January1989;7:114e21.
  18. Clark AP.Principles of digital data transmission.London:Pentech Press;1983.
  19. Pahlavan K,Howard SJ,Sexton TA.Decision feedback equalization of the indoor radio channel.IEEE Trans Commun 1993;COM-41:164e70.
  20. Tlouyamma J,Velempini M.Investigative analysis of channel selection algorithms in cooperative spectrum sensing in cognitive radio networks.SAIEE Afr Res JMarch2021;112(1):4e14.https://doi.org/10. 23919/SAIEE. 2021. 9340532.

COinS