臺灣博碩士論文加值系統

5G通訊系統模擬器常被用於評估相關技術效能，其中分成模擬複雜環境 (多使用者、基站) 的系統層級模擬器 (System-Level Simulation, SLS) 與模擬單一通道環境效能的連接層級模擬器 (Link Layer Simulator, LLS)，可透過實體層萃取 (Physical Abstraction) 提供Effective SINR (Signal to Interference plus Noise Ratio)，連結兩種模擬器以提供完整的通訊架構。LLS 藉由 SLS 提供的 SINR、MCS (Modulation Coding Scheme)、TBS (Transport Block size) 等參數產生塊錯誤率 (Block Error Rate, BLER) 回傳給 SLS，讓 SLS 得以獲得通道傳送品質的資訊。
實體層萃取會將不同通道的 SINR值合成一個傳輸的訊號與干擾比值 (即 Effective SINR)，一般稱為 ESM (Effective SINR Mapping)，其中以 MIESM (Mutual Information Effective SINR Mapping) 較具代表性。一般的MIESM會將所有載波效能視為相同，不會考量每條子載波的不同傳輸參數進行對應的調整。本文提出在系統層級模擬器增加傳輸結構 (Frame Structure) 估算，讓模擬器知道此次傳輸實際資料的位置，實體層萃取中的 MIESM 可依據子載波上可傳輸的RE 數量作為加權係數，計算更接近實際傳輸效能的Effective SINR。
本文是基於 5G 低密度同位檢測碼 (Low-Density Parity-Check, LDPC Code) 的架構，以每次傳輸中可用的資源單位作為計算 TBS 的參數，對不同 MCS 的設定進行測試，再分析 LLS 的塊錯誤率變化。測試結果顯示，加權MIESM的結果更貼近 LLS ，其中Mini-slot 因為symbols 的數量較少，考量傳輸結構後對每個子載波symbols 的數量差異比例會更大，最多可以改善71.29 % 塊錯誤率。最後提供 SLS 估算 BLER 的改善方法，並討論 MCS 中目標碼率與實際碼率的差距，讓SLS能更準確估算傳輸架構。

5G communication system simulator is usually used to evaluate the performance of related technologies. The system can have two simulators, including System-Level Simulation (SLS) which can simulate complicated environments (many users and base stations), and Link Layer Simulators (LLS) which can simulate performance in single channel environmental. Besides, the physical abstraction can connect two simulators to efficiently provide a complete communication framework. SLS provides SINR (Signal to Interference plus Noise Ratio), MCS (Modulation Coding Scheme), TBS (Transport Block size) and other parameters for LLS, and LLS can have feedback information about Block Error Rate (BLER). Eventually, SLS will obtain the information of the channel quality which is helpful for determining the current system status.
The physical abstraction combines the SINR values from different subcarrier into an effective signal-to-interference ratio (Effective SINR) with ESM (Effective SINR Mapping). Typically, MIESM (Mutual Information Effective SINR Mapping) is a famous way to calculate Effective SINR. However, traditional MIESM treats all subcarrier conditions/performances as identical without considering the different parameters of subcarriers. This paper provides the frame structure estimation in the SLS. Thus, the simulator can have the location information of the actual data transmitted in each link. Therefore, MIESM in the LLS can adjust Effective SINR with weighted parameter according to the information of subcarrier’s REs (resource elements).
Based on 5G Low-Density Parity-Check (LDPC) codes, REs in each frame structure are available for calculating TBS and the simulations are realized with different MCS settings to evaluate the proposed scheme. The experimental results show that the performances of weighted MIESM are similar to all tests in LLS. Because Mini-slot has a smaller number of symbols, available RE in each subcarrier will be more sensitive. Consequently, the weighted MIESM can improve the results of block error rate up to 71.29%. In the worst case, the error rate only has less than 1% with comparing to the traditional scheme. Finally, this paper provides an improved method for SLS to estimate BLER, and discusses the difference between the target code rate and the actual code rate in MCS to make sure that SLS can precisely calculate the frame structure.

目錄
摘要................................................................i
Abstract ...........................................................ii
目錄 ..........................................................iii
圖目錄 ............................................................v
表目錄 ...........................................................vi
第一章 緒論 ....................................................1
1.1 研究背景介紹 ............................................1
1.2 研究動機 ....................................................2
第二章 通訊系統模擬器 ............................................3
2.1 系統層級模擬器 ............................................3
2.2 連接層級模擬器 ............................................3
2.2.1 LDPC code ............................................4
2.2.2 線性區塊碼 ............................................4
2.2.3 同位檢測矩陣與Quasi Cyclic (QC) LDPC codes ............5
2.2.4 5G LDPC code 編碼標準介紹 ............................7
2.2.5 LDPC code 解碼方式 ...................................10
2.2.6 實體層萃取方式介紹 ...................................14
2.2.6.1 EESM ...........................................14
2.2.6.2 MIESM .......................................15
2.3 5G 頻率資源規劃簡介 .......................................16
2.3.1 資源區塊(Resource Block) ...............................16
2.3.2 資源單位(Resource element) ...........................16
2.3.3 5G control information ...............................16
2.3.4 Transport Block Size ...................................17
2.3.5 Actual code rate .......................................19
第三章 5G 實體層MIESM修正......................................20
3.1 overhead 的估算 ...........................................20
3.1.1 DMRS 的配置 .......................................20
3.1.2 其它overhead 的配置 ...............................22
3.1.3 mini-slot設定 .......................................24
3.2 Symbol數量對BLER的影響 ...............................24
3.3 RBIR的修正 ...............................................25
3.3.1 MIESM的加權方式 ...................................25
3.3.2 基於資源單位的LLS 模擬修正 .......................26
第四章 模擬結果 ...............................................27
4.1 一般 slot ...................................................27
4.2 Mimi-slot ...................................................29
4.3 MIESM修正的分析 .......................................30
4.4實體層萃取的修正方式 (Z_c不同) ...........................31
第五章 結論與未來展望 ...........................................32
參考文獻 .......................................................33

參考文獻
[1]R. P. F. Hoefel and O. Bejarano, “On application of phy layer abstraction techniques for system level simulation and adaptive modulation in ieee 802.11 ac/ax systems,” Journal of Communication and Information Systems, vol. 31, no. 1, 2016.
[2]S. Lien, S. Shieh, Y. Huang, B. Su, Y. Hsu and H. Wei, “5G New Radio: Waveform, Frame Structure, Multiple Access, and Initial Access,” IEEE Communications Magazine, vol. 55, no. 6, pp. 64-71, June 2017
[3]S. Jin, S. Roy and T. R. Henderson, “Efficient PHY Layer Abstraction for Fast Simulations in Complex System Environments,” IEEE Transactions on Communications, vol. 69, no. 8, pp. 5649-5660, Aug. 2021
[4]Stefan Pratschner, Bashar Tahir, Ljiljana Marijanovic, Mariam Mussbah, Kiril Kirev, Ronald Nissel, Stefan Schwarz & Markus Rupp “Versatile Mobile Communications Simulation: the Vienna 5G Link Level Simulator,” J. Wireless Com. Network, 2018.
[5]Robert G. Gallager, “Low-density parity-check codes,” IRE Trans. Inform Theory, vol. 8, no. 1, pp. 21-28, Jan. 1962.
[6]D. J. C. MacKay, “Good error-correcting codes based on very sparse matrices,” in IEEE Transactions on Information Theory, vol. 45, no. 2, pp. 399-431, March 1999.
[7]3GPP38.212 V16.7.0 Sept 2021
[8]T. Richardson and S. Kudekar, “Design of Low-Density Parity Check Codes for 5G New Radio,” IEEE Communications Magazine, vol. 56, no. 3, pp. 28-34, March 2018.
[9]Z. Hanzaz and H. D. Schotten, “Performance evaluation of Link to system interface for Long Term Evolution system,” 2011 7th International Wireless Communications and Mobile Computing Conference, pp. 2168-2173, 2011
[10]Z. Hanzaz and H. D. Schotten, “Analysis of effective SINR mapping models for MIMO OFDM in LTE system,” 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 1509-1515, 2013
[11]S. Lagen, K. Wanuga, H. Elkotby, S. Goyal, N. Patriciello and L. Giupponi, “New Radio Physical Layer Abstraction for System-Level Simulations of 5G Networks,” 2020 IEEE International Conference on Communications (ICC), pp. 1-7, 2020
[12]IEEE 802.16m-08/004r2 IEEE 802.16 Broadband Wireless Access Working Group IEEE 802.16m Evaluation Methodology Document (EMD), July 2008.
[13]W. Anwar, K. Kulkarni, N. Franchi and G. Fettweis, “Physical Layer Abstraction for Ultra-Reliable Communications in 5G Multi-Connectivity Networks,” 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Bologna, Italy, pp. 1-6, 2018
[14]3GPP 38.211 V16.6.0, June 2021
[15]Bae, J., Abotabl, A., Lin, H., Song, K., & Lee, J. “An Overview of Channel Coding for 5G NR Cellular Communications," APSIPA Transactions on Signal and Information Processing, 8, E17, June 2019
[16]3GPP38.214 V16.3.0, Sept 2020
[17]H. Wu, “A Bound on the Actual Code Rate in 5G NR,” 2020 International Conference on Information Networking (ICOIN), pp. 415-419, 2020
[18]3GPP38.912V16.0.0, July 2020
[19]梁哲豪, “5G NR低延遲迷你時槽資源配置及HARQ處理時程的系統層級模擬,” 國立中正大學通訊工程研究所碩士論文,May,2021.(指導教授:潘仁義)
[20]Chin-Kuo Jao, Chun-Yen Wang, Ting-Yu Yeh, Chun-Chia Tsai, Li-Chung Lo, Jen-Hsien Chen, Wei-Chen Pao and Wern-Ho Shee, “WiSE: A System-Level Simulator for 5G Mobile Networks,” IEEE Wireless Communications, vol. 25, no. 2, pp. 4-7, April 2018.