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Over the past decades, unmanned aerial vehicles (UAVs) have been widely used in both military and civilian fields. In these applications, flocking motion is a fundamental but crucial operation of multi-UAV systems. Traditional flocking motion methods usually designed for a specific environment. However, the real environment is mostly unknown and stochastic, which greatly reduces the practicality of these methods. In this paper, deep reinforcement learning (DRL) is used to realize the flocking motion of multi-UAV systems. Considering that the sim-to-real problem restricts the application of DRL to the flocking motion scenario, a digital twin (DT) enabled DRL training framework is proposed to solve this problem. The DRL model can learn from DT and be quickly deployed on the real-world UAV with the help of DT. Under this training framework, this paper proposes an actor-critic DRL algorithm named behavior-coupling deep deterministic policy gradient (BCDDPG) for the flocking motion problem, which is inspired by the flocking behavior of animals. Extensive simulations are conducted to evaluate the performance of BCDDPG. Simulation results show that BCDDPG achieves a higher average reward and performs better in terms of arrival rate and collision rate compared with existing methods.

Unmanned Aerial Vehicle (UAV) swarm has been widely applied in border surveillance, public safety, transportation management and so on. Affected by the complex mission environment and rapidly changing network topology, the network performance decreases drastically especially when an unsuitable contention window size is selected in traditional media access control (MAC) protocol. In this work, we first introduce a node-counts-based UAV swarm MAC (NCU_MAC) protocol to dynamically adjust the contention window size according to the number of neighbor nodes. Next, a four- dimensional Markov Chain model is developed to model the media access process and evaluate the performance of NCU_MAC. The expressions of the collision, transmission probability and saturation throughput are obtained theoretically. Simulation results are presented to validate the effectiveness of the proposed model and show the saturation throughput of the swarm network in the process of cooperative movement.

Transmission power control (TPC) leads to heterogeneous transmission power levels of the nodes in multi-hop wireless ad hoc networks. This eventually results in a quite complicated collision scenario due to hidden and exposed terminal problems, and brings a big challenge for analyzing the saturation throughput of the flows. This paper presents a saturation throughput model for IEEE 802.11 multi-hop ad hoc networks with heterogeneous transmission powers. In the model, one tagged node goes through with three processes, i.e., backoff, freezing and transmission, and each of which is composed of a certain number of continuous fixed length time slots. We put forward a four-dimensional Markov chain model for the behavior of the tagged node in each fixed-length time slot. Under the condition of heterogeneous transmission powers, we consider two types of collisions, i.e., the instantaneous and persistent collisions. Their probabilities are characterized by the one-step transition probability matrix of the Markov chain. The per-flow saturation throughput of the flow is eventually derived through an iterative way. Finally, the accuracy of our model is validated by comparing the analytical values and the simulation results, and the impact of the heterogeneous power levels on the performance of the wireless multi-hop ad hoc networks is effectively analyzed.

Contention-based distributed synchronization (CDS) protocols, which first standardized in the IEEE 802.11 power saving mode (PSM), have been widely used in wireless ad hoc networks. The time required to complete the synchronization progress, i.e., synchronization efficiency, is obviously an important performance metrics for CDS protocols. However, few attempts have been focusing on modeling and analyzing the synchronization efficiency of the CDS protocols. In this letter, we present a 2-D Markov chain model for the CDS scheme of the IEEE 802.11 PSM. The purpose of our model is to determine the relationship between the time required to complete the synchronization process and the value of the contention parameter, i.e., the contention window size. Through modeling, we derive the optimal values of the contention window size to achieve the minimum synchronization time at different network scales. We also validate the accuracy of our model by comparing the analytical results with that obtained by means of simulations.

Radio frequency identification (RFID) has been widely used in various areas, such as logistics, healthcare, manufacture and so on. However, tag collision problem greatly affects the performance of RFID systems by reducing bandwidth utilization and increasing identification delay etc. In this paper, we propose a dynamic query tree anti-collision (DQTA) protocol, which dynamically adjusts the number of subgroups of each collision slot. Based on the number of consecutive colliding bits in tag response k, DQTA splits colliding tags into 2^k subgroups. Dividing colliding tags into more appropriate subgroups, the number of collision slots and transmitted message bits are effectively reduced. Comparing with the most related state-of-art works, the proposed DQTA protocol can identify tags with less time and fewer transmitting message bits.

In wireless ad hoc networks, a suitable MAC protocol can provide better QoS (Quality of Service) guarantees. However, in modern warfare environment, the combat missions change rapidly. A fixed MAC protocol may be not suitable for the highly changeable environments and combat missions. To solve this problem, we propose a neural network-based MAC protocol-selection mechanism to select the optimal MAC protocol for new missions based on the real-time environment information of the battlefield, i.e., the intelligent selection (IS) algorithm. In IS, we prepare the empirical data set with massive mission data, and construct the learning model through making use of the neural network. Experimental results demonstrate that the prediction accuracy of the proposed IS algorithm is over 0.93.

This paper analyzes the limitation of IEEE 802.11 protocol using a single power for node communication. On the basis of IEEE 802.11protocol and the basic power backoff protocol which introduces the idea of power backoff, a CSMATPB protocol with time and space backoff is proposed. The protocol increases the time competition window, while making the power backoff reduce the interference between nodes. Then, the three dimensional Markov chain model is established for this protocol. Through the results of numerical calculation and simulation analysis, it is proved that the protocol mechanism can effectively solve the problem that the lower space reuse rate of IEEE 802.11 protocol and the problem that the basic power backoff protocol discards the packet prematurely. So CSMA-TPB protocol can effectively improve the saturation throughput and energy utilization of the network.

This paper presents DT-MAC, a dynamic TDMA based medium access control (MAC) protocol designed to offer collision-free transmissions while providing QoS guarantees for different services in scalable fully connected ad hoc networks. In DT-MAC, a new time frame structure which consists of synchronization, request, assignment and data slots is put forward. In each frame, the number of slots and their lengths are adaptively adjusted according to the number of nodes and their services in the network. Meanwhile, a distributed frame synchronization method is proposed to provide synchronization guarantee for the nodes and generate a manager node for each frame to dynamically allocate the slots according to the QoS requirements of different services. Besides, by introducing request slot, DT-MAC can make nodes join or leave the network without conflicts. Simulation results show that DT-MAC performs better in providing QoS guarantees and accommodating the change of network scale compared with conventional TDMA-based MAC protocols.

The aeronautical ad hoc network (AANET) is an application of the mobile ad hoc networking technology to aeronautical communications. As the airliners move at a very high speed, one critical issue for improving the performance of AANET is to select reliable route that can address the frequent link breakage problem induced by the unpredicted network topology changes. In this paper, we focus on developing a link availability estimation based reliable routing protocol which considers the unpredicted network topology change problem to improve the performance of AANET. The link availability indicates the probability that a link will be continuously available for a given period of time. We first propose a novel Semi-Markov Smooth mobility model to mimic the behavior of the airliners in the sky. On the basis of the mobility model, we obtain the probability density function of the relative speed of two nodes, and further derive the expectation of the link lifetime. The accuracy of our analysis is validated by comparing the analytical results with that obtained by means of simulations. Moreover, we define the link availability factor and use it as the path selection metric to design a reliable routing protocol for AANET. Simulation results show that a gain in performance can be obtained by our protocol compared with the traditional routing strategy.

In this paper, we focus on improving MACA-P performance in multi-hop ad hoc networks. Based on the analysis of the collision problems of the distributed coordination function (DCF) and MACA-P in multi-hop ad hoc networks, we propose an adaptive collision avoidance scheme (ACAS). ACAS mainly improves MACA-P by adaptively adjusting the control gap of the master transmission based on the conditions of the master transmission. Also, a new hybrid confirmation mechanism is presented, which, together with the adjustment of the control gap, decreases the energy consumption of the nodes. Simulation results show that our scheme can obtain higher overall throughput and lower energy consumption in comparison with the DCF and MACA-P protocols.

This paper proposes TIE-MAC, tolerable interference estimation-based concurrent medium access control protocol for wireless local area network WLAN mesh networks. The goal is to increase spatial reuse, achieve high throughput and reduce average energy consumption through exploiting concurrent transmissions among neighbouring nodes. TIE-MAC confirms that the tolerable interference of the receiver plays a key role in determining the efficiency of concurrent transmission scheduling, and puts forward a novel tolerable interference estimation mechanism, enabling the receivers to precisely estimate their tolerable interference. Meanwhile, a concurrent transmission gap CTG is inserted between the transmission of the RTS/CTS and data packets to offer the nodes in the vicinity of the receiver the chance to schedule possible overlapping transmissions. The size of the CTG is optimised using an exponential smoothing model-based adjustment algorithm. Moreover, sequenced acknowledgements ACKs are introduced in TIE-MAC and used in combination with the tolerable interference estimation mechanism to avoid possible collisions among different concurrent transmissions. Simulation results show that TIE-MAC gains better throughput and energy consumption performance in comparison with existing concurrent transmission protocols as well as the active WLAN mesh standard.

Wireless mesh networks (WMNs) has been actively explored for a few years, and the IEEE 802.11 Task Group “s” has recently approved the active 802.11s standard for Wireless local area network (WLAN) mesh networking. To provide differentiated channel access and quality of service (QoS) guarantees for multimedia flows, IEEE 802.11s standard employs enhanced distributed channel access (EDCA) as the basic medium access control (MAC) protocol. In this study, the authors focus on modelling and analysing the medium access delay differentiation of EDCA under saturation condition in multi-hop WMNs. The authors develop a three-dimensional Markov chain model to evaluate the medium access delay differentiation of EDCA. In this model, the authors fully consider the performance impact of Request to Send (RTS) frame collisions and data frame collisions and then put forward the pseudo states to distinguish the different back-off procedures induced by these collisions. Using this analytical model, the authors derive the average medium access delay for the flows with different priorities. Comparisons with the simulation results show that the analytical model is extremely accurate.