# Secrecy Rate of Resource-Constrained Mobile Relay Model under Two-Way Wiretap Channel
## 4 Discussion  
In this section, we compare our proposed scheme and algorithms with state-of-the-art methods from the literature.  
Unlike [1; 2; 3; 4; 5], which illustrate a four-terminal relay-eavesdropper network, there is no direct link between the source (Alice) and legitimate destination (Bob) in our system model due to the long distance between them and limited transmit power at Alice; therefore, the channel model and subsequent signal analysis are quite different from those in [1; 2; 3; 4; 5]. Moreover, in contrast to [2; 3; 4] with the relay's location variation restricted in a line, the relay in our scheme moves around in a two-dimensional (2D) space, which is more complicated. In particular, unlike [3], where the relay assists the wire tapper rather than the destination, the mobile relay in our scheme helps the destination and suppresses the eavesdropper.  
Our scheme presents moving trajectories, as shown in Figures 5 and 6, which are not present in [7; 8; 9; 10]. This is because [7; 8; 9; 10] focus on fixed relay scenarios, in which relays are not able to move. Additionally, in contrast to [7], we obtain a competitive secrecy rate versus number of iterations. However, unlike [7], the secrecy rate of the fixed relay case in our scheme is near 0, which is depicted in Figure 4. This is because the eavesdropper in our paper is very close to the relay.  
Ref. [11; 12; 13] aim to develop unmanned aerial vehicle(UAV)-based relay systems. They indeed provide flexible moving relays to implement air-to-ground or air-to-air wireless communication, while our ground mobile vehicle-based relay system is designed to solve the ground secure transmission problem, especially the indoor complicated pitch case. However, there are some identical issues both in UAV and in our ground mobile vehicle scheme, such as joint trajectory and communication design, which is generally formulated as mixed integer non-convex optimization problem, and this kind of problem is usually nontrivial to solve due to the integer constraints and other nonlinear parts. Contrary to expectations, we all utilize successive convex optimization techniques to solve the intractable optimization problem. Nevertheless, there are other different aspects among [11; 12; 13] and our scheme. Firstly, there is no eavesdropper in [11; 13]; thus, it is not the maximum secrecy rate but the minimum communication delay in [11] and the maximum throughput in [13]. Secondly, multi-user communication scheduling and association in [13] are regarded as  
Figure 6: Selected path for mobile relay with M = 15 when noise power \(\sigma_{\epsilon}^{2}=-90\) dBm.  
the integer constraints, while in our scheme, the integer constraints are the graph mobility model. Thirdly, Ref. [12] introduces an additional UAV-based jammer to ensure secure communication against eavesdropping. In comparison with [12], no jamming is added in our scheme, which leads to a notably different system model from that in [12]. Finally, unlike [11; 12; 13] employing the block coordinate descent method, we propose an iterative algorithm described as Algorithm 2 with Algorithm 1 embed in it, which is capable of obtaining a local optimal solution with much lower complexity.  
A future research goal is to derive the secrecy rate bounds of the resource-constrained two-way mobile relay system. Additionally, finding the global optimal solution is a consequent work plan, and the secrecy rate with cache-aided at the mobile relay may also be worth investigation.