# Deep Learning-Based Spread-Spectrum FGSM for Underwater Communication
## 1 Introduction  
Underwater acoustic communication (UWAC) has become one of the critical research fields due to its proliferation of new scientific, industrial, and naval applications [1; 2; 3]. However, the limitation of the available bandwidth, poor physical link quality, availability of a sustainable energy source for the battery feed sensor nodes, high latency, and attenuation of the acoustic waves by water still represent the main drawbacks of the wireless communication in the ocean's environment [3; 4; 5]. Although optical communication, electromagnetic communication, and magnetic induction communication can be employed for the oceanic environment, acoustic communication is considered to be the widest in use since it achieves long communication distances of tens of kilometers for the low data transmissionrate and several tens of meters for the high data transmission rate [6, 7]. Therefore, multiple-input multiple-output (MIMO) technologies have been introduced as a communication key technology offering an increased capacity and diversity gain of UWAC [8]. However, decoding complexity, power constraint and inter-channel interference (ICI) are the main problems that limit the practical implementation of MIMO technologies in underwater communication [9, 10]. A combination between MIMO technologies and code division multiple access (CDMA) was introduced in [11] to avoid the ICI and improve the UWA communication's spectral efficiency, but in conventional MIMO systems, the power and decoding complexity leads to a small number of radio-frequency chains compared to the available transmit antennas. These problems are more severe in rich underwater multipath channels due to the high cochannel interference problem [11]. Switching diversity and spatial modulation (SM) has been proposed as an attractive solution for exploiting the inherent antenna redundancy problem [12]. The classical switching diversity approach is suitable for known channel cases at the transmitter side, so antenna switching is used to improve the system performance by selecting the antennas corresponding to the best channels and create diversity switching [9]. In SM, additional information is transmitted by the active antenna index instead of creating diversity [13, 14]. Recently, space modulation techniques (SMTs) have been developed in academia. Unlike conventional modulation techniques, SMTs use new methods to obtain a high data rate. Therefore, SMTs have been developed as one of the hopeful solutions of the next fifth-generation (5G) wireless mobile networks due to its benefits in terms of energy efficiency (EE), spectrum efficiency (SE), and low system complexity. SM is considered as the main SMT where one or more antennas can be selected for information bits transmission, and the index of the transmitter antennas is utilized as an information-bearing unit to provide higher data rate compared with the conventional single-input-multiple-output (SIMO) systems and avoid the MIMO conventional problems, such as ICI, high decoding complexity, and inter-antennas synchronization. Researchers provided different SMTs schemes to improve the performance of SM [13, 14] by emitting the constellated data symbols using multiples antenna [15, 16, 17], or separating the real and imaginary parts of the constellated data symbol and then transmitting them via one or more transmit antennas [18, 19, 20]. Some others tried inserting additional dimensions represented by another type of signal constellation to be used as an index and information-bearing [3, 12, 21]. Orthogonal channels support multiple users into the same time and frequency by using orthogonal codes in direct-sequence code division multiple access (DS-CDMA) scheme. In order to achieve better performance, coded-aided direct sequence spread spectrum (DSSS) [22] and practical low-rate turbo-Hadamard coding techniques [23] were proposed. Motivated by those characteristics, the spread spectrum (SS) was combined with other techniques to achieve a high data rate as in [24, 25].