# A Finite State Machine-Based Improved Cryptographic Technique
## 4 Results and Analysis of Proposed Work
### Proposed MCTC
The bit error rate (BER) is calculated by encoding and decoding a random bit sequence of 65,536 bits at a rate of 1/2 CTC, sending it via an AWGN channel, and then measuring the number of errors in the decoded version eight times. (i) Effect of the design of MCTC  
CTC analysis suggested MCTC for error correction. Figure 8 shows BER versus SNR scatter plots for each interval. CTC with MCTC has 104 BER at 0.4 dB SNR, 0.2 dB better than CTC with RI. Like the RI, the MCTC randomly interleaves with a dispersion of 0.8. Yet, deterministic FSMs such as the QPPI and SKI FSM use FSM spread to guarantee that permuted bits are no more than a specified distance apart. SKI created both FSMs. A quadratic permutation polynomial generates interleaved bit positions with a broad spread to provide the QPPI error-correcting performance equivalent to the RI. Error correction is achieved by transferring error patterns across decoders. Nevertheless, the SKI length and key affect the spread between interleaved bit positions; thus, a big spread is not always guaranteed. QPPI and SKI feature interleaved bit locations that can take several values, but their patterns are uniformly spaced, making them simple to predict and prone to security breaches. Correlations from the interleaved pattern's regularity lower the BER curve's error floor. (ii) Effect of the number of decoding iterations of CTC decoder  
Figure 8: Effect of FSM on the BER performance of CTC. Figure 7: BER performance of the uncoded MCTC, MCTC with TC, and proposed MCTC and TC. CTC decoding uses iterative decoding to exchange data between the protocol's two decoder modules. Figure 9 shows a BER for the CTC's efficiency during decoder iterations one to eight. Increased decoding frequency improves the BER vs. SNR graphs. The number of rounds increases decoder communication, which helps CTC to fix faults. TC's error-correcting efficiency rises from one to two iterations. The decoders communicated and shared a lot of information throughout training. Hence, the receiver receives relevant input bits to accurately assess the situation. After a few cycles, the decoders may learn the input bits to anticipate. More iterations do not enhance decoder information sharing. Because of this, the BER performance only improved after the ninth decode cycle. Effect of frame length of the CTC  
What followed was a spectacular error-correcting performance [26] from TC findings. Conclusions are drawn for frame lengths greater than 65,536 bits. Yet, frame lengths of around 1000 bits are required for video transmission. However, far shorter ones may be sufficient for uses such as voice transmission. Figure 10 shows how well CTC works for error correction over a variety of frame durations. This process yielded the following sets of digits: 256, 508, 1020, 2048, and 65,536. Increasing the frame length improves the bit error rate performance, as seen in the Figure 10, and this is particularly apparent at higher Signal-to-Noise Ratios. Increasing the frame length allows the CTC to generate more uncorrelated codewords and carry out efficient decoding due to the increased randomness in the interleaved sequence.