| Channel coding parameter recognition technology is to recover the original encoding and parameters from the received sequence through some inverse methods in the absence of prior information,so that decoding can restore the original information sequence.It is widely used in the field of cognitive communication and communication reconnaissance.With the rapid development of communication technology,the transmission power required in the communication process gradually becomes lower,resulting in weaker and weaker signals received.So the demand for the anti-error capability of the channel coding parameter identification technology is also increasing.As a very important channel coding method,convolutional codes are widely used in deep space communication,information countermeasures and other fields.It also plays a significant role in turbo codes.Correctly identifying the parameters of convolutional codes is the key to identify the parameters of turbo codes.Because of excellent anti-noise and anti-fading ability of turbo codes,they usually work in communication systems with poor channel conditions,which requires that the convolutional code parameter identification technology also has strong anti-error ability.Based on these requirements,this thesis analyzes the reasons for the insufficient anti-error ability of the existing estimation algorithms of convolutional codes,and proposes two solutions from different perspectives.Analyzes the anti-error ability the proposed algorithms through numerical simulation,which effectively improve the anti-error capability.The main research contents are briefly described as follows:This thesis first studies the existing estimation algorithms of convolutional codes,and divides these algorithms into two categories according to the difference of the received sequence: using the hard-decision received sequence and using the soft-decesion received sequence.The recognition basis of these algorithms is summarized,and the reasons for the insufficient anti-error ability of the two types of algorithms are analyzed.Then,aiming at the problem that the number of required prior conditions limits the anti-error performance in the algorithm which utilizes the hard-decision received sequence,the estimation algorithms of convolutional codes based on Gauss Jordan Elimination Through Pivoting is studied.Its poor robustness against channel errors is analyzed.Based on this,a convolutional code recognition algorithm based on the minimum misjudgment probability criterion is proposed.The proposed algorithm estimates the parity-check matrix iteratively by going through the memory length,and sets the decision threshold based on the minimum misjudgment probability criterion to end the iterative process.The applicability and robustness against channel errors of the proposed algorithm are verified by numerical simulation analysis.Finally,in view of the problem in the algorithm based on the soft-decesion received sequence that the algorithm does not make use of the soft-decesion received sequence,a maximum cosinoidal cost function method for parameter estimation of convolutional codes is studied.And the reason why the algorithm does not make good use of the soft-decesion received sequenc is analyzed.Based on this,an estimation algorithm for convolutional codes based on the conjugate gradient method is proposed.The proposed algorithm constructs a new cost function based on the exponential function,which has the advantage of steeper changes around the extreme value,and the optimization is accomplished via the conjugate gradient method.The validity of the cost function is verified by theoretical derivation.The influences of the proposed algorithm are analyzed,and the applicability and robustness against channel noise of the proposed method are verified by simulation. |
