a few prerequisites. The symmetric capacity is defined as the highest possible rate that can be achieved when all of the input symbols to the channel are equiprobable. The mutual information of a binary-input discrete memoryless channel (symmetric capacity) with input alphabet X = {0,1} is defined as follows [29]: 2W(y|x) The symmetric capacity is equal to the Shannon capacity when the channel W is a symmet- ric channel. The Bhattacharyya parameter Z(W) is the upper bound on the probability of a maximum likelihood decision error when transmitting 0 or 1 over the channel W. Thus the Bhattacharyya parameter Z(W) is a channel reliability measure. The Bhattacharyya parame- ter can be calculated as follows: The relationship between I(W) and Z(W) for any binary-input, discrete, memoryless channel W can be described as follows: which means I(W) = or I(W) 0, and only if Z(W) Z(W) = 1, respectively. Polar codes are the first type of forward error correction codes achieving the symmetric capacity for arbitrary binary-input discrete memoryless channel under low-complexity encoding and low-complexity successive cancelation (SC) decoding with order of O(N log N) for infinite length codes. Polar codes are founded based on several concepts including channel polarization, code construction, polar encoding, which is a special case of the normal encoding process (i.e., more structural) and its decoding concept [29]. New Radio Access Physical Layer Aspects (Part 2) 517 Channel polarization is the first phase of polar coding where N distinct channels are synthesized such that each of these channels is either completely noisy or completely noiseless, that is, strictly valid for infinite code length N. The measure of how much a channel is noisy in the context of the polar codes was first determined by the symmetric capacity or the Bhattacharyya parameter of the channel; however, BER was used later as a common measure. Code construction phase involves selecting channels in which the information bits are transmit- ted. In other words, c