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PHY Abstraction for HEW Evaluation Methodology

PHY Abstraction for HEW Evaluation Methodology . Date: 2013-09-11. Authors:. Introduction. The objective of PHY abstraction is to accurately predict link layer performance in computationally easy way This contribution compares two PHY abstraction methods:

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PHY Abstraction for HEW Evaluation Methodology

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  1. PHY Abstraction for HEW Evaluation Methodology • Date:2013-09-11 Authors: Dongguk Lim, LG Electronics

  2. Introduction • The objective of PHY abstraction is to accurately predict link layer performance in computationally easy way • This contribution compares two PHY abstraction methods: • Mutual Information based approach (MMIB) • Constrained Capacity based approach (CC) Dongguk Lim, LG Electronics

  3. System model • Effective SINR (SINReff) can be calculated as follows • where SINRn is the post processing SINR at the n-th subcarrier, N is the number of symbols for a coded block or the number of data subcarriers used in an OFDM system, and Φ is Effective SINR Mapping (ESM) function • Since the same SINReff provides the same Packet Error Rate (PER) performance for a given coding block size and MCS level, we can use AWGN performance curve as a reference curve Dongguk Lim, LG Electronics

  4. SINRn Calculation (Example) • For SISO case, • y= hx+n • where y is a received signal • h is channel response at each subcarrier • x is a transmitted signal • n is a noise • Then, SINRn can be calculated as • where ɛxis a signal strength • σn2is noise variance Dongguk Lim, LG Electronics

  5. Code Block Size • Different code block sizes provide different PER performances • Ideally, we need to have AWGN curves for all possible code block sizes • Practically, we consider the following approach for simplicity • Produce reference curves for several code block sizes • Do interpolation for other code block sizes Dongguk Lim, LG Electronics

  6. Two ESM functions • Mutual Information based approach (MMIB) [1] • Constrained Capacity based approach (CC) [2] Dongguk Lim, LG Electronics

  7. Mutual Information based approach (MMIB) (1/3) • Each bit experiences a different ‘equivalent’ bit-channel • Due to the asymmetry of the modulation map • Mutual information of the equivalent channel is • where m is the number of bits per constellation, and I(bi,LLR(bi)) is the mutual information between input bit to the QAM mapper and output LLR for i-th bit in the modulation map MMIB: Mean Mutual Information per coded Bit Dongguk Lim, LG Electronics

  8. Mutual Information based approach (MMIB) (2/3) • Mean mutual information through N sub-carriers over the codeword • Since mutual information I(bi,LLR(bi))is a function of constellation and SINR, mean mutual information is Dongguk Lim, LG Electronics

  9. Mutual Information based approach (MMIB) (3/3) • Effective SINR mapping (ESM) function is derived for each modulation as follows (details in [1]) Dongguk Lim, LG Electronics

  10. Constrained Capacity based approach (CC) • Simply use capacity formula for ESM function • where Mis the maximum number of bits for all constellation • CC is less complex than MMIB since there is a closed form solution of Φ inverse Dongguk Lim, LG Electronics

  11. Performance Comparison: QPSK Dongguk Lim, LG Electronics

  12. Performance Comparison: 16QAM Dongguk Lim, LG Electronics

  13. Conclusion • This contribution provided introduction on PHY Abstraction • We compared two methods and observed that • MMIB provides accurate prediction of link performance • CC requires less computational complexity, but shows some inaccuracy • For accurate prediction of link performance, MMIB should be adopted as one of  PHY abstraction methods Dongguk Lim, LG Electronics

  14. Reference • [1] IEEE 802.16m-08/004r5, “IEEE 802.16m Evaluation Methodology Document (EMD)” • [2] IEEE 802.11-13/0757r1, “Evaluation Methodology and Simulation Scenarios” Dongguk Lim, LG Electronics

  15. Dongguk Lim, LG Electronics Appendix MMIB Performance Verification

  16. SimulationParameters • Basic parameters • To eliminate the channel impairment effect such as ICI, ISI, channel estimation error, we used the perfect channel estimation and increased CP length in simulation • Effect of channel impairments are for further study Dongguk Lim, LG Electronics

  17. MMIB MCS0 Dongguk Lim, LG Electronics

  18. MMIB MCS1 Dongguk Lim, LG Electronics

  19. MMIB MCS2 Dongguk Lim, LG Electronics

  20. MMIB MCS3 Dongguk Lim, LG Electronics

  21. MMIB MCS4 Dongguk Lim, LG Electronics

  22. MMIB MCS5 Dongguk Lim, LG Electronics

  23. MMIB MCS6 Dongguk Lim, LG Electronics

  24. MMIB MCS7 Dongguk Lim, LG Electronics

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