% Initial condition of the polynomia x2(). This is fixed value as described in 36.211 7.2 % Initial condition of the polynomia x1().
Psuedo random rgp generator algorithm code#
However, this code has not been verified with any real data. If you try to convert the specification into the programming code whatever language you choose, you will understand the equation / algorithm in much more detailed level than just reading the document. Some of these parameters are from RRC message or DCI, these values shown here will help you understand those RRC / DCI parameters.įollowing is an example of the sequence when n = 119 (120 data point) and the initialization value is 64.ĭisclaimer : This code is just to push myself (probably readers) to look into the algorithm (formula) specified in the specification to the most detailed level. You don't have to memorize nor try to understand these equation itself, just try to figure out what kind of parameters are involved in determining the initialization value for each application. The problem arises specifically in data sampling and. The general problem for which the formula is needed is to assess the probability that a particular sample comes from a proposed distribution. I put down all the initialization value for each and every application listed in the table shown above. The algorithm calculates the exact cumulative distribution of the two-sided Kolmogorov-Smirnov statistic for samples with few observations. The initialization value gets different depending on applications. The second, more important, is to use different initialization value. How do we utilize this single mathematical form to such a many different application ? First trick is to use different 'n' in c(n). (So I recommed you to read through LTE Pseduo Random Sequence page as well since I put more descriptions in the page). This algorithm is exactly same as LTE pseudo random sequence.
Psuedo random rgp generator algorithm trial#
Followings are the list of applications of these sequences.ĥ.7.2 Preamble sequence generation (PRACH)ĥ.5.2 Demodulation reference signal associated with xPUCCHĥ.5.3 Demodulation reference signal associated with xPUSCHĥ.5.5 Phase noise compensation reference signalĦ.7.1 UE-specific reference signals associated with xPDSCHĦ.7.2 UE-specific reference signals associated with xPDCCHĦ.7.6 DL Phase noise compensation reference signalĦ.7.7 Demodulation reference signals associated with ePBCHĦ.8.3 Extended Synchronization Signal (Scrambling a ZadOff-Chu Seq)Īs in LTE, the Pseudo Random Sequence in 5G trial is a kind of Gold Sequence and it is based on a common form as shown below. Sequence Generation algorithm for these two sequence is almost same in both LTE and 5G Pretrial, but these sequence are more widely used in 5G Pretrial specification. The two most famous numerical sequence in both LTE and 5G Pretrial is Zadoff Chu sequence and Pseudo Random sequence.
5G - Pre Trial - Pseudo Random Sequence Home