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 has been successfully received, a PHY abstraction is illustrated in the following diagram. Figure 5. RBIR PHY Abstraction Procedure The detailed procedure of RBIR PHY abstraction as shown in Figure 5 is: Assume K interference events happen during a subframe of L OFDM symbols corresponding to a MPDU of PL bytes, each starts from Tk and lasts Lk OFDM symbols, for k=1…K. For each interference over [Tk , Tk+1), k=1…K: 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=Tk*. Equalizer is MRC if Nss=1, or MMSE if Nss>1. SINR is only calculated over 1 OFDM symbol for each interference event. In the case that Tk is not aligned with the OFDM symbols boundary of the signal to be decoded, use the first OFDM symbol after Tk for SINR calculation. That is, Map N×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. After iterated over all events, Calculate the PER Determine if this subframe is successfully received. Appendix 2 – Traffic model descriptions
Thus, the HTTP Server web traffic generation is that, at first, to create an HTML page using the HTML page statistics, with either MTU size is 1500 bytes or 576bytes, and then to download the main and the embedded objects using either HTTP/1.0-burst transport or HTTP/1.1- persistent transport. 2: Parameters for HTTP traffic model Component Distribution Parameters PDF File size (S) Truncated Logonormal Mean = 10710 bytes SD = 25032 bytes Min = 100 bytes Max = 2 Mbytes (before truncation) if x > max or x < min, discard and generate a new value for x Embedded Object size (SE) Truncated Logonormal Mean = 7758 bytes SD = 126168 bytes Min = 50 bytes Max = 2 Mbytes (before truncation) if x > max or x < min, discard and generate a new value for x Number of embedded objects per page (Nd) Truncated Pareto Mean = 5.64 Max. = 53 (before truncation) Subtract k from the generated random value to obtain Nd if x > max, discard and regenerate a new value for x Reading time (Dpc) Exponential Mean = 30 sec Parsing time (Tp) Exponential Mean = 0.13 sec In addition to the HTTP request packet from HTTP Client to HTTP Server, the reciprocal TCP Ack to the HTTP traffic, from HTTP Client to HTTP Server is generated as follows: Step 1: 40 Byte TCP Ack, interval is equal to 1ms delay from HTTP traffic frame reception at the HTTP Client Traffic Class Identifier for HTTP is HTTP Evaluation Metrics
Appendix 3 – RBIR and AWGN PER Tables The embedded spreadsheet contains the RBIR and AWGN PER tables. The results under the Mean column shall be used for all simulations and calibration. Appendix 4 – Packet Reception and Preamble Detection Procedure The original discussion of the following text can be found in [25].