# Low-Complexity Channel Codes for Reliable Molecular Communication via Diffusion
## 3 Results and Discussion  
### Simulation Results  
Due to the fact that in-body MC technology is still in its infancy, analysis of MC systems typically has to be made resorting to numerical evaluation using end-to-end MC channel models. Note that this type of numerical evaluation is very important not only to understand the possible behavior of a scheme, but also as it allows us to capture the potential achievable gains between different solutions. Therefore, in this section we perform a thorough assessment of the proposed scheme using an end-to-end MC simulator that integrates a diffusion-based MC channel model. The purpose of this simulation is to test different modulations and bit encoding solutions combined with TCH channel codes. We will be comparing the performance of some previously studied codes for MC against the TCH codes which we propose here as a potential alternative for MC scenarios. For the channel correcting codes, we choose to test the Hamming Codes (HC) because they are basic and easy to implement, and the ISI-mtg codes from [14] because they were designed specifically for an MC environment. Finally, we test the TCH codes for different codes lengths. To guarantee a fair comparison between these codes, similar sets of code rates were used comprising both lower codes rates, and higher codes rates. We remind that lower coding rates may obtain better performances but decrease the information bit rate. Higher coding rates can improve the bit rate sacrificing some BER performance. For the uncoded scenario and for the HC we used threshold hard decision. For the TCH codes and for the ISI-mtg codes, LLR soft decisions were employed. Both these bit decisions are detailed in Section 2.4. The main parameters used in the simulations are described in Table 1. The symbol duration can have a critical impact on the behavior of the system. To evaluate the impact of this parameter we will consider different values for the scaling factor \(\tau\) which is used for defining the symbol duration, as shown in Table 1. Tests will be performed for a small symbol duration because it is when there are more errors, becoming very noticeable how channel codes help to correct them. The simulations were performed using NRZ and Manchester pulses, at different symbol durations, with two distinct types of modulation: OOK and BCSK. In the case of OOK modulation, we have \(x[k]\in\{0,1\}\), whereas in the BCSK we use \(x[k]\in\{-1,1\}\). For the BCSK we assume the existence of a molecules destructor that can reduce the concentration of the carrier molecule. It is important to emphasize that while the channel model may not be the most adequate for this particular scenario, the proposed scheme does not depend on a specific channel and does not require channel knowledge. Therefore, using this channel model still enables an evaluation of the system behavior. The results will be presented as the relation between the BER and \(N_{mloc}/\sigma_{n}^{2}\) (per information bit) in dB, where \(\sigma_{n}^{2}\) denotes the variance of the environmental noise. In Figures 5(a) and 5(a), we present the results for when NRZ pulses were tested, whereas in Figures 5(b) and 5(b), we present the results for when Manchester pulses were tested. Both Figures 5 and 5 were simulated using BCSK modulation. When Manchester codes \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Deterministic model & Point transmitter to a spherical absorbing \\  & receiver \\ \hline Statistical model & Gaussian approximating Poisson \\ \hline Paired \(tx-rx\) link distance (\(d_{0}\)) & 10 (\(\upmu\)m) \\ \hline Diffusion Coefficient (\(D\)) & 79.4 (\(\upmu\)m\({}^{2}\)/s) \\ \hline Transmitter radius and receiver radius (\(a_{tx},a_{rx}\)) & 5 (\(\upmu\)m) \\ \hline Symbol duration (\(T_{s}\)) & \(\tau\frac{(d_{0})^{2}}{6D}\) (s) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Simulation parameters. were used, the tested channel coding methods had an overall better performance.