where is the post processing SINR at the subcarrier, is the number of subcarriers in a SINRn n-th N coded block and is a mapping function. Φ For PHY and integrated system simulation, the mapping function is based on received bit mutual information rate (RBIR) assuming coded-modulation. For M-QAM, the mapping function is defined as where is a zero-mean complex Gaussian random variable with variance 1, i.e., The U U~CN(0,1). lookup tables of functions for different modulations are attached in appendix 3 with an SNR Φ granularity of 0.02dB (note that high granularity is needed to accurately capture the steepness of the curve). A lookup table of AWGN PER vs. SNR for each MCS and each coding scheme (BCC, LDPC) is collected with the SNR granularity of 0.1dB for 2 reference packet lengths for BCC and 1 reference packet length for LDPC. The AWGN PER lookup tables are attached in Appendix 3. To determine if a PPDU of spatial streams over tones has been successfully received, a Nss N PHY abstraction is illustrated in the following diagram. Figure 5. RBIR based PHY Abstraction Procedure The detailed procedure of RBIR based PHY abstraction as shown in is: Figure 5 Generate (both desired and interfering) channels. Calculate the equalizer-output SINR per spatial stream for the tone/t-th OFDM symbol, n-th SINR(iss,n,t), iss=1…Nss, n=1…N, t=T0…T0+T. Equalizer is MRC if or MMSE if Nss=1, Nss>1. Definition of and are TBD. T0 T Map SINRs to RBIR. N×T×Nss 1 Reverse map RBIR to effective SNR. 1 1 Estimate PER for based on AWGN PER lookup table. In case of BCC, = 32bytes if 400bytes; or 1458bytes otherwise. PL0 PL< In case of LDPC, = 1458bytes. PL0 Determine if this PPDU is successfully received. Appendix 2 Traffic model descriptions –
where SINRn is the post processing SINR at the n-th subcarrier, N is the number of subcarriers in a coded block and Φ is a mapping function. For PHY and integrated system simulation, the mapping function is based on received bit mutual information rate (RBIR) assuming coded-modulation. For M-QAM, the mapping function is defined as where U is a zero-mean complex Gaussian random variable with variance 1, i.e., U~CN(0,1). The lookup tables of Φ functions for different modulations are attached in appendix 3 with an SNR granularity of 0.02dB (note that high granularity is needed to accurately capture the steepness of the curve). A lookup table of AWGN PER vs. SNR for each MCS and each coding scheme (BCC, LDPC) is collected with the SNR granularity of 0.1dB for 2 reference packet lengths for BCC and 1 reference packet length for LDPC. The AWGN PER lookup tables are attached in Appendix 3. To determine if a PPDU of Nss spatial streams over N tones has been successfully received, a PHY abstraction is illustrated in the following diagram. Figure 5. RBIR based PHY Abstraction Procedure The detailed procedure of RBIR based PHY abstraction as shown in Figure 5 is: Generate (both desired and interfering) channels. Calculate the equalizer-output SINR per spatial stream for the n-th tone/t-th OFDM symbol, SINR(iss,n,t), iss=1…Nss, n=1…N, t=T0…T0+T. Equalizer is MRC if Nss=1, or MMSE if Nss>1. Definition of T0 and T are TBD. Map N×T×Nss SINRs to 1 RBIR. Reverse map 1 RBIR to 1 effective SNR. Estimate PER for based on AWGN PER lookup table. In case of BCC, PL0 = 32bytes if PL< 400bytes; or 1458bytes otherwise. In case of LDPC, PL0 = 1458bytes. Determine if this PPDU is successfully received. Appendix 2 – Traffic model descriptions
11-14-1285-00-00ax-energy-efficiency-redline-to-evaluation-methodology.docx