ration of packet transmission. The goal of PHY abstraction or link-to-system mapping is to predict the encoded Block Error Rate (BLER) for a given received channel realization across the OFDM sub-carriers that are used to transmit the channel-coded blocks. In order to predict the performance, the post-processing SINR values at the input to the FEC decoder are considered as input to the PHY abstraction. As the link-level curves are generated assuming a frequency flat channel response at a given SINR, an effective SINR is defined to accurately map the system-level SINR to the link-level curves to determine the resulting BLER. This mapping is known as Effective SINR Mapping (ESM) in the literature. The ESM PHY abstraction compresses the vector of received SINR values to a single effective SINR value, which can then be further mapped to a BLER value. Several ESM approaches to predict instantaneous link-level performance have been studied in the literature. Examples include mean instantaneous capacity, Exponential Effective SINR Mapping (EESM), and Mutual Information (MI) effective SINR mapping. Each of these PHY abstractions uses a different function to map the vector of SINR values to a single CHAPTER 12 Performance of IEEE 802. 16m and 3GPP LTE-Advanced Mapping Function System-Level Link-Level (EESM, MI, etc.) Generate frequency-selective channel BLERAWGN Average SINR of Determine the received SINR each subchannel of each sub-carrier (Link to System Mapping) Link adaptation, Scheduling, ARQ, etc. Throughput, Packet Error Rate, etc. FIGURE 12-3 The link-to-system mapping process [8] number. Given the instantaneous EESM SINR, mean capacity or mutual information effective SINR, the BLER for each MCS is calculated using a suitable mapping function. The general process of link- to-system mapping is illustrated in Figure 12-3. In general, the ESM PHY abstraction methods can be described as follows: effective (12) (12-13) where SINR effective denotes the effective SINR, SINR is the SINR measured at the nth sub-carrier, NF