Nikiforov
Vladimir O.
D.Sc., Prof.
doi: 10.17586/2226-1494-2019-19-5-918-924
ANALYTICAL COMPARISON OF BASE STATION REACH FOR VARIOUS MULTICARRIER SIGNAL SCHEMES.
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Ivanov V.V., Bondareva I.I. Analytical comparison of base station reach for various multicarrier signal schemes. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 5, pp. 918–924 (in Russian). doi: 10.17586/2226-1494-2019-19-5-918-924
Abstract
Subject of Research. The paper considers the problem of choice and comparison of multicarrier schemes in cellular networks. The schemes are compared with Orthogonal Frequency Division Multiplexing which is a current choice for the 5th generation networks. Reviewed schemes are evaluated by their effect for the Internet of Things scenario. We consider the effect of applyingwireless sensor networks as sensors along highways. Also alternative multicarrier schemes are evaluated based on possible improvements in conventional cellular networks. Method. The schemes proposed for implementation were compared by criteria significant for the IoT. The possible improvement of base station reach was evaluated with respect to parameters defined in 5G and New Radio specifications, developed by The Third Generation Partnership Project Consortium. Main Results. Analytical method for improvement evaluation of base station reach while implementing of alternative multicarrier schemes is formulated. Base station reach increase is the result of higher power efficiency occurring at reduction of radiated power out of specified bandwidth (“side lobes”) and the peak to average power ratio. The performed modeling has shown that base station reach increase in case of “Universal Filtered MultiCarrier” scheme implementation in 5G networks is approximately 12%. Practical Relevance. Obtained results can be of practical use in decision-making regarding the implementation relevance of alternative multicarrier schemes in cellular networks after 5G. According to the higher reach it is possible to evaluate the increase in number of subscribers when their area density is fixed and, consequently, the lowering in capital expenditures on network deployment if the number of base stations is decreased.
References
2. Ben Mabrouk M., Chafii M., Louët Y., Bader F. A precod- ing-based PAPR reduction technique for UF-OFDM and filtered-OFDM modulations in 5G systems // Proc. 23th European Wireless Conference. 2017. P. 8011329.
3. Сравнение LPWAN-технологий: XNB от «СТРИЖ» и NB-IoT [Электронный ресурс]. URL: https://strij.tech/ publications/tehnologiya/lpwan-xnb-nbiot.html (дата обращения: 05.06.2019).
4. Тихвинский В.О., Коваль В.А., Бочечка Г.С. Интернет вещей: международная стандартизация // Электросвязь. 2017. № 2. C. 20–25.
5. Farhang-Boroujeny B., Moradi H. OFDM inspired waveforms for 5G IEEE Communications Surveys & Tutorials. 2016. V. 18. N 4. P. 2474–2492. doi: 10.1109/COMST.2016.2565566
6. Liu Y., Chen X., Zhong Z., Ai B., Miao D., Zhao Z., Sun J., Teng Y., Guan H. Waveform design for 5G networks: Analysis and comparison IEEE Access. 2017. V. 5. P. 19282–19292. doi: 10.1109/ACCESS.2017.2664980
7. Mendes L., Michailow N., Matthé M., Gaspar I., Zhang D., Fettweis G. GFDM: providing flexibility for the 5G physical lay- er Opportunities in 5G Networks: A Research and Development Perspective. 2016. P. 325–390.
8. Kim C., Yun Y.H., Kim K., Seol J.-Y. Introduction to QAM- FBMC: From waveform optimization to system design IEEE Communications Magazine. 2016. V. 54. N 11. P. 66–73. doi: 10.1109/MCOM.2016.1600384CM
9. Rani P.N., Rani C.S. UFMC: The 5G modulation technique // Proc. 7th IEEE International Conference on Computational Intelligence and Computing Research (ICCIC). 2016. P. 814–816. doi: 10.1109/ICCIC.2016.7919714
10. Ding Z., Lei X., Karagiannidis G.K., Schober R., Yuan J., Bhargava V.K. A survey on non-orthogonal multiple access for 5G networks: Research challenges and future trends IEEE Journal on Selected Areas in Communications. 2017. V. 35. N 10. P. 2181–2195. doi: 10.1109/JSAC.2017.2725519
11. Anderson J.B. Faster-than-Nyquist signaling for 5G communication Signal Processing for 5G: Algorithms and Implementations. 2016. P. 24–46. doi: 10.1002/9781119116493.ch2
12. Richardson T., Kudekar S. Design of low-density parity check codes for 5G new radio IEEE Communications Magazine. 2018. V. 56. N 3. P. 28–34. doi: 10.1109/MCOM.2018.1700839
13. Kishore K.P., Umar P.R., Naveen V.J. Comprehensive anal- ysis of UFMC with OFDM and FBMC // Indian Journal of Science and Technology. 2017. V. 10. N 17. doi: 10.17485/ijst/2017/v10i17/114337
14. Gerzaguet R., Kténas D., Cassiau N., Doré J.-B. Comparative study of 5G waveform candidates for below 6GHz air interface. [Электронный ресурс]. URL: https://pdfs.semanticscholar. org/cae9/77530de0eb7e48fc93ee0425bc8efa357648.pdf (дата обращения: 24.08.2019).
