Journal of Xidian University ›› 2019, Vol. 46 ›› Issue (3): 59-64.doi: 10.19665/j.issn1001-2400.2019.03.010

Previous Articles     Next Articles

Analysis of the performance of the multichannel S-ALOHA by the power ramping scheme

JIAN Xin1,WANG Fang1,SONG Jian1,FANG Wei2,JIANG Xin2,ZENG Xiaoping1,TAN Xiaoheng1   

  1. 1. School of Microelectronics and Communication Engineering, Chongqing Univ., Chongqing 400044, China
    2. Beijing Aeronautical Science & Technology Research Institute, Commercial Aircraft Corporation of China, Beijing 100000, China;
  • Received:2018-09-15 Online:2019-06-20 Published:2019-06-19

Abstract:

Aiming at the problem of the rapid increase in power consumption caused by retransmission under the massive machine type devices concurrent access to the network. Therefore, in this paper, by use of the number of contending devices that transmit the j-th preamble at the i-th random access slot as the state variable, we present a transient performance analysis method (especially the power consumption and access delay model) for the multi-channel S-ALOHA by the power ramping scheme as well as a simplified form under stable access attempts. By taking two kinds of machine type communications traffic models proposed by the 3GPP as examples, numerical simulation is conducted to validate the effectiveness of the proposed performance analysis method as well as its simplified form, to analyze the effects of the number of users, the size of the back-off window, and the maximum number of retransmissions on the performance of the multi-channel S-ALOHA by the power ramping scheme, and to propose an optimization strategy for appropriately extending the back-off window to exchange power consumption with delay. These practices together can provide a good reference for performance analysis and optimization design of the random access channel under the massive machine type devices concurrent access to the netwok.

Key words: massive machine type communication, multichannel S-ALOHA, power ramping schemes, power consumption model, delay analysis

CLC Number: 

  • TN929.5

Baidu
map