Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 2
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

The high-speed of train (HST) in combination with the high carrier frequency of HST systems leads to the severe inter carrier interference (ICI) in the HST orthogonal frequency division multiplexing (HST-OFDM) systems. To avoid the complexity in OFDM receiver design for ICI eliminations, the OFDM system parameters such as symbol duration, signal bandwidth, and the number of subcarriers should be chosen appropriately. This paper aims to propose a process of HSTOFDM system performance investigation to determine these parameters in order to enhance spectral efficiency and meet a given quality-of-service (QoS) level. The signal-to-interferenceplus- noise ratio (SINR) has been used as a figure of merit to analyze the system performance instead of signal-to-noise ratio (SNR) as most of recent research studies. Firstly, using the nonstationary geometry-based stochastic HST channel model, the SINR of each subcarrier has been derived for different speeds of the train, signal bandwidths, and number of subcarriers. Consequently, the system capacity has been formulated as the sum of all the single channel capacity from each sub-carrier. The constraints on designing HST-OFDM system parameters have been thoughtfully analyzed using the obtained expressions of SINR and capacity. Finally, by analyzing the numerical results, the system parameters can be found for the design of HSTOFDM systems under different speeds of train. The proposed process can be used to provide hints to predict performance of HST communication systems before doing further high cost implementations as hardware designs.
Go to article

Bibliography

[1] V. Vahidi and E. Saberinia, “OFDM high speed train communication systems in 5G cellular networks,” in 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2018, pp. 1–6.
[2] Y. Fu, C. Wang, A. Ghazal, e. M. Aggoune, and M. M. Alwakeel, “Performance investigation of spatial modulation systems under nonstationary wideband high-speed train channel models,” IEEE Transactions on Wireless Communications, vol. 15, no. 9, pp. 6163–6174, 2016.
[3] V. Vahidi and E. Saberinia, “Channel estimation for wideband doubly selective UAS channels.” Miami, FL, USA: IEEE, 2017, pp. 1175– 1180.
[4] V. Vahidi, A. P. Yazdanpanah, E. Saberinia, and E. E. Regentova, “Channel estimation, equalisation, and evaluation for high-mobility airborne hyperspectral data transmission,” IET Communications, vol. 10, pp. 2656–2662, 2016.
[5] A. Sanz-G´omara, J. A. Mar´ın-Garc´ıa, and J. I. Alonso, “Performance evaluation of MIMO architectures with moving relays in high-speed railways,” in 2018 48th European Microwave Conference (EuMC), 2018, pp. 716–719.
[6] M. N., R. M.I., K. S., and P. R., OFDM: Principles and Challenges. In: Tarokh V. (eds) New Directions in Wireless Communications Research. Springer, Boston, MA, 2009.
[7] J. Rodriguez-Pineiro, P. Suarez-Casal, M. Lerch, S. Caban, J. A. Garcia- Naya, L. Castedo, and M. Rupp, “LTE downlink performance in high speed trains.” Glasgow: IEEE, 2015, pp. 1–5.
[8] Zhichao Sheng, Yong Fang, and Chen Wang, “A BEM method of channel estimation for OFDM systems in high-speed train environment,” in 2013 International Workshop on High Mobility Wireless Communications (HMWC), 2013, pp. 6–9.
[9] B. Gong, L. Gui, Q. Qin, and X. Ren, “Compressive sensing-based detector design for SM-OFDM massive MIMO high speed train systems,” IEEE Transactions on Broadcasting, vol. 63, no. 4, pp. 714–726, 2017.
[10] Z. Sheng, H. D. Tuan, and Y. Fang, “Power allocation for OFDM system in a high-speed train environment,” in 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2015, pp. 650–655.
[11] X. Ren, M. Tao, and W. Chen, “Compressed channel estimation with position-based ICI elimination for high-mobility SIMO-OFDM systems,” IEEE Transactions on Vehicular Technology, vol. 65, no. 8, pp. 6204–6216, 2016.
[12] Y. Xin, Z. Liang, Y. Bai, C. Zhai, and W. Li, “Capacity enhancement using cooperative distributed antenna system in downlink high-speed train environments,” in 2019 11th International Conference on Wireless Communications and Signal Processing (WCSP), 2019, pp. 1–5.
[13] I. Zakia, “Capacity of HAP-MIMO channels for high-speed train communications,” in 2017 3rd International Conference on Wireless and Telematics (ICWT), 2017, pp. 26–30.
[14] N. Lin, X. Huang, and X. Ma, “Analysis of the uplink capacity in the high-speed train wireless communication with full-duplex mobile relay,” in 2016 IEEE 83rd Vehicular Technology Conference (VTC Spring), 2016, pp. 1–5.
[15] M. K. Bhatt, B. S. Sedani, K. R. Parmar, and M. P. Shah, “Ergodic UL/DL capacity analysis of co-located and distributed antenna configuration for high speed train with massive MIMO system,” in 2017 International Conference on Inventive Computing and Informatics (ICICI), 2017, pp. 458–461.
[16] T. Zhou, C. Tao, L. Liu, J. Qiu, and R. Sun, “High-speed railway channel measurements and characterizations: a review,” Journal of Modern Transportation, vol. 20, no. 4, pp. 199–205, 2012. [Online]. Available: https://doi.org/10.1007/BF03325799
[17] F. Kaltenberger, A. Byiringiro, G. Arvanitakis, R. Ghaddab, D. Nussbaum, R. Knopp, M. Bernineau, Y. Cocheril, H. Philippe, and E. Simon, “Broadband wireless channel measurements for high speed trains,” in 2015 IEEE International Conference on Communications (ICC), 2015, pp. 2620–2625.
[18] Y. Bi, J. Zhang, Q. Zhu, W. Zhang, L. Tian, and P. Zhang, “A novel non-stationary high-speed train (HST) channel modeling and simulation method,” IEEE Transactions on Vehicular Technology, vol. 68, no. 1, pp. 82–92, 2019.
[19] A. Ghazal, C. Wang, H. Haas, M. Beach, X. Lu, D. Yuan, and X. Ge, “A non-stationary MIMO channel model for high-speed train communication systems,” in 2012 IEEE 75th Vehicular Technology Conference (VTC Spring), 2012, pp. 1–5.
[20] A. Ghazal, C. Wang, B. Ai, D. Yuan, and H. Haas, “A nonstationary wideband MIMO channel model for high-mobility intelligent transportation systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 2, pp. 885–897, 2015.
[21] L. Liu, C. Tao, J. Qiu, H. Chen, L. Yu, W. Dong, and Y. Yuan, “Position-based modeling for wireless channel on high-speed railway under a viaduct at 2.35 GHz,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 4, pp. 834–845, 2012.
[22] Y. M. Aval, S. K. Wilson, and M. Stojanovic, “On the achievable rate of a class of acoustic channels and practical power allocation strategies for OFDM systems,” IEEE Journal of Oceanic Engineering, vol. 40, no. 4, pp. 785–795, 2015.
[23] “Guidelines for evaluation of radio interface technologies for ITU,” Geneva, Switzerland, Tech. Rep. Tech. Rep. ITU-R M.2135-1, 2009.
Go to article

Authors and Affiliations

Do Viet Ha
1
Trinh Thi Huong
1
Nguyen Thanh Hai
1

  1. Faculty of Electrical and Electronic Engineering, University of Transport and Communications (UTC), Hanoi, Vietnam
Download PDF Download RIS Download Bibtex

Abstract

Orthogonal frequency division multiple access (OFDMA) in Long Term Evolution (LTE) can effectively eliminate intra-cell interferences between the subcarriers in a single serving cell. But, there is more critical issue that, OFDMA cannot accomplish to decrease the inter-cell interference. In our proposed method, we aimed to increase signal to interference plus noise ratio (SINR) by dividing the cells as cell center and cell edge. While decreasing the interference between cells, we also aimed to increase overall system throughput. For this reason, we proposed a dynamic resource allocation technique that is called Experience-Based Dynamic Soft Frequency Reuse (EBDSFR). We compared our proposed scheme with different resource allocation schemes that are Dynamic Inter-cellular Bandwidth Fair Sharing FFR (FFRDIBFS) and Dynamic Inter-cellular Bandwidth Fair Sharing Reuse-3 (Reuse3DIBFS). Simulation results indicate that, proposed EBDSFR benefits from overall cell throughput and obtains higher user fairness than the reference schemes.

Go to article

Authors and Affiliations

Mert Yağcıoğlu
Oğuz Bayat

This page uses 'cookies'. Learn more