## 3 Application of Multi-Sensor Covert Underwater Communication  
To obtain information from each of the sensors for covert underwater communication using multiple sensors, a spread spectrum method is widely used that can obtain the information of each sensor individually from the receiver side by multiplying the codes that have orthogonal components which are different from each other in the same frequency band. Most single input single output (SISO) communication systems employ the RAKE receiver using the differential phase shift keying (DPSK) method, which is an asynchronous mode, and for multi-sensors, SIC mode [12] is used to apply the RAKE method by eliminating interference from other sensors. This mode has drawbacks that may degrade performance if there is an error propagation effect and channel information is inaccurate. Thus, this section proposes an underwater communication structure for covert multi-sensors using an efficient decoding method and the covert underground acoustic communication technique mentioned in the previous section to overcome the above drawbacks. To do this, an efficient decoding structure is proposed. The configuration of the transmitter and receiver in the multi-sensor covert underwater communication based on the direct sequence spread spectrum is shown in Figure 3. In transmitter model shown in Figure 3a, data sent by the \(k\)-th sensor pass through the (2, 1, 7) convolution coding, which is a soft decision-based channel coding technology that shows excellent performance in underwater channels such as a multi-channel environment, and the interleaver in which cluster errors are changed into scatter errors. The data passing through the channel coding and interleaver are multiplied \(p(T_{c})\), which is PN code for spread spectrum. Then, \(p_{sensor\_k}(T)\), which is a sensor identification code to identify each sensor, is multiplied by the spread spectrum data, and then modulated and transmitted through the modulator. The other sensors also transmit signals in the same manner. The final transmission signals are transmitted after summing all transmission signals from all other sensors. Figure 2: Proposed RAKE receiver. Assuming that the \(k\)-th sensor's transmission signal is \(x_{k}(n)\), \(x_{k}(n)\) can be expressed as presented in Equation (2). \[x_{k}(n)=b_{k}(n)p(T_{c})p_{sensor\__k}(T)\cos(w_{c}n) \tag{2}\]  
\(b_{k}(n)\) refers to data that is intended to be sent by the \(k\)-th sensor, while \(T_{c}\) and \(T\) refer to lengths of PN code \(p(T_{c})\) for spread spectrum and \(p_{sensor\_k}(T)\) for sensor identification. The \(k\)-th sensor's transmission signal \(x_{k}(n)\) after completing the modulation process is sent after summing transmission signals from other sensors. The final transmission signal \(s(n)\) can be expressed with the sum of the data from all other sensors as presented in Equation (3). \[s(n)=\sum_{k=1}^{K}x_{k}(n), \tag{3}\]  
\(K\) refers to the total number of sensors. At the receiver side, as shown in Figure 3b, the transmission signal sent from the transmitter is received at the receiver after being distorted by the underwater channel characteristics. The  
Figure 3: Covert multiple sensor acoustic communication based on a turbo equalized RAKE receiver: (**a**) Transmitter for multiple sensors; (**b**) Covert multiple sensor acoustic communication based on a RAKE receiver. receive signal \(r(K)\) passes through multipath and noise is added so that it can be expressed by Equation (4) below. \[r(n)=\sum\limits_{l=1}^{L}c_{K,l}(n)s(n)+\omega(n) \tag{4}\]  
\(L\) refers to the total number of multipath and \(l\) refers to the \(l\)-th multi-path. \(c_{K,l}(n)\) refers to the channel response coefficient located in the \(k\)-th sensor's \(l\)-th path and \(\omega(n)\) refers to the Gaussian noise.