PHY, MAC, and RLC Layer Based Estimation of Optimal Cyclic Prefix Length

Abstract

This work is motivated by growing evidence that the standard Cyclic Prefix (CP) length, adopted in the Long Term Evolution (LTE) physical layer (PHY) specifications, is oversized in propagation environments ranging from indoor to typical urban. Although this ostensibly seems to be addressed by 5G New Radio (NR) numerology, its scalable CP length reduction is proportionally tracked by the OFDM symbol length, which preserves the relative CP overhead of LTE. Furthermore, some simple means to optimize fixed or introduce adaptive CP length arose from either simulations or models taking into account only the bit-oriented PHY transmission performance. On the contrary, in the novel crosslayer analytical model proposed here, the closed-form expression for the optimal CP length is derived such as to minimize the effective average codeblock length, by also considering the error recovery retransmissions through the layers above PHY—the Medium Access Control (MAC) and the Radio Link Control (RLC), in particular. It turns out that, for given protective coding, the optimal CP length is determined by the appropriate rms delay spread of the channel power delay profile part remaining outside the CP span. The optimal CP length values are found to be significantly lower than the corresponding industry-standard ones, which unveils the potential for improving the net throughput.

Optical OFDM Error Floor Estimation by Means of OTDR Enhanced by Front-End Optical Preamplifier

“…We can justifiably assume that, although the common binomial distribution statistically well describes mutually independent bit error occurrences within an L-bits-long data block, in this case, we consider that the appropriate error generating model should still preserve (moderate) mutual dependability among the individual bit error occurrences. This conforms to the statistical model of sampling without replacement, well described by the hypergeometric distribution of errors within an erroneous data block (containing one or more erroneous bits), which provides the following BLER vs. BER relationship [10,11]:…”

“…Moreover, the below tables also contain the BER/BLER entries (indexed by "ABSTR") as the overpesimistic "worst-case scenario" values obtained by applying the well-known BER expression for the M-QAM signal transmission over the additive white Gaussian noise (AWGN) channel, as a function of the ratio of the energy Eb of a bit to noise spectral density N0, is [10]: (21) where Q denotes the Gaussian tail function.…”

“…Our preliminary test results are aimed to just verify the proposed concept, whereas the follow-up high-accuracy tests of this kind can be repeated as many times as needed. The exemplar OTDR setup screen shot and a trace with discovered and qualified events, are presented in Figure 9, followed by Tables 1 and 2 Moreover, the below tables also contain the BER/BLER entries (indexed by "ABSTR") as the overpesimistic "worst-case scenario" values obtained by applying the well-known BER expression for the M-QAM signal transmission over the additive white Gaussian noise (AWGN) channel, as a function of the ratio of the energy E b of a bit to noise spectral density N 0 , is [10]:…”

“…As it is challenging to uniquely relate the OTDR trace events (primarily the reflective ones) to the parameter(s) determining the OFDM BER error floor under high-SNR conditions and therefore dominant time dispersion, which implies that we can apply the m-subcarrier OFDM BER floor model [10], specifically when sampling time is just upon the arrival of the first impulse of the channel impulse response [2].…”

“…Furthermore, as for the contemporary transmission networks including not only fiber links but the microwave ones, too, the bit-oriented transmission performance standards have long ago been replaced with the data block-oriented ones [10], let us now derive the Block Error Ratio (BLER) from BER estimated by (3) [10,11]:…”