Request Delay-Based Pricing for Proactive Caching: A Stackelberg Game Approach

In this paper, we consider the problem of traffic offloading in a two-tier downlink smallcell network with hybrid access. We formulate a Stackelberg game with pre-offloading decision, which includes two steps, to study the problem. The utility of the MBS is designed as a piecewise function, corresponding to the two possible decisions of the MBS. We design a bonus-based incentive mechanism to motivate smallcell base stations (SBSs) serve the MUEs. We prove the existence and uniqueness of the Stackelberg equilibrium. We also consider the incomplete information game, where the SBSs have private information. A Bayesian Stackelberg game with pre-offloading decision is formulated and the existence of Bayesian Stackelberg equilibrium is proved. Our proposed approach achieves much higher utilities than the existing approach does under some circumstances in both cases, which proves the necessity and superiority of our proposed game structure.

Unmanned Aerial Vehicles, popularly known as UAVs, have been used in many applications, from healthcare services to military assignments with diverse capabilities such as data transmission, cellular service provisioning, and computational offloading tasks. UAV's have been recently used to provide Security as a Service (SaaS). SaaS involves technical solutions like anti-virus and anti-spam software, firewalls, using secure operating systems, etc. UAV's are resource-constrained devices, and thus they are connected to the base station (BS) so that they may avail the computational facilities of the BS. The UAV's connect themselves to the base station using cluster heads (intermediary devices). At times several UAVs cooperatively come together to serve a given region and such a group of UAVs is called a swarm of UAVs. In real-world scenarios, many stakeholders come together to form UAV swarm configuration proving services to users. Each stakeholder wants to maximize his gains. In this work, we propose a pricing Stackelberg game among UAVs, Cluster heads, and BS by formulating their behavioral utilities. Using particle swarm optimization on each entity's utility functions, we create an optimal price strategy for each entity to maximize their profit.

UAV-assisted ISAC network physical layer security based on Stackelberg game

Stackelberg game for backhaul resource allocation in the two-tier LTE femtocell networks

In this paper, we consider a Wireless Sensor Network (WSN) with Wireless Energy Transfer (WET) capability, and we focus on the data gathering in a multi-hop scenario. In fact, we assume that any wireless sensor that needs the help of relays to deliver the packet may transfer energy as a kind of reward or payment. We assume that only few sensors have direct reliable channel to the sink Base Station (BS), i.e. sensors that are close the BS. Hence, other sensors should relay on them to transmit their packets to the BS. We assume that the nodes of the WSN are selfish and aim to maximize their utility function, which mainly accounts for their energy consumption. We propose a multi-level multi-leader-follower Stackelberg game framework to analyse the competition between users. Particularly, we characterise the Stackelberg equilibrium (SE) for the three-hop WSN, and we propose a distributed algorithm to achieve the SE. Moreover, we show that the network lifetime is enhanced compared to other multi-hop data transmission in WSN.

This article investigates the secure control strategy for networked switched systems against multiple denial‐of‐service (DoS) attackers by employing a two‐level Stackelberg game approach. Specifically, the sensor‐to‐controller (SC) DoS attacker group, the controller, and the controller‐to‐actuator (CA) DoS attacker group are modeled as three players in a game‐theoretic framework. Based on their respective positions in the network transmission process, a two‐level Stackelberg game is formulated. The sequence of actions is defined as follows: the SC DoS attacker group acts first, followed by the controller, and finally the CA DoS attacker group. The attack strength coefficient is introduced to quantify the contributions of individual attackers within a multiple‐attacker group. The packet loss rates and the controller gains are utilized to construct strategy sets for the attackers and the controller, respectively. Moreover, an algorithm is developed to compute the corresponding two‐level Stackelberg equilibrium based on the convex optimization approach. To handle the open‐loop and asynchronous switching scenarios caused by DoS attacks, sufficient conditions based on dwell‐time (DT) condition are derived to ensure the mean‐square stability. Moreover, considering the nonconvexity and strong nonlinearity of optimizing the switching signal, an improved particle swarm optimization (PSO) algorithm incorporating DT‐constrained decoding method is proposed to enhance the system performance. Finally, a practical example involving a continuous stirred tank reactor is presented to validate the effectiveness and superiority of the proposed methods.

Intel's first ASICs

In this paper, we have combined a game‐theoretic and an information‐theoretic notions to describe the selfish behavior of each user in a two‐user linear deterministic cognitive interference channel (LD‐CIC). The two‐user LD‐CIC is the simple case of the cognitive radio technology in the high SNR regime. This model is a solution to improve the spectral efficiency in software defined network (SDN) concept in 5G. In the two‐user LD‐CIC, the information bits of the primary/licensed transmitter is a‐priori provided at the cognitive/secondary/unlicensed transmitter. So that, the cognitive transmitter can cooperate and utilize the frequency spectrum to send the information bits of the both transmitters. In information‐theoretic approaches, full cooperation is assumed between transmitters for codebook and rate selection in this channel. This may not be a realistic assumption if transmitters are selfish and are willing to maximize their own benefit. In particular, we have defined the Stackelberg equilibrium (SE) region on the capacity region of the two‐user LD‐CIC to capture the behavior of each transmitter when they compete even though one of them is informed of the other transmitter information bits. We have implemented a two‐phase Stackelberg game with the primary and cognitive transmitters acting as the leader in the first phase, and the follower in the second phase, respectively. In this implementation, both transmitters are assumed to be selfish and only interested in optimizing their own pay‐offs. The SE region is characterized as a subset of capacity region in which the transmitters cannot gain more transmission rate by individually deviating from the SE strategy. The achievability of the resultant region has been configured using a randomized Han‐Kobayashi scheme for all the channel gains. Also, we have compared the obtained SE region with the previous equilibrium regions such as Nash equilibrium (NE) region of the linear deterministic interference channel (LD‐IC). The results have shown that the SE points on the sum‐rate of the LD‐CIC capacity region are more than the NE points on the sum rate of the capacity region of LD‐IC, so the SE region of the LD‐CIC is Pareto superior to the NE region of LD‐IC.

Integrated sensing and communication (IS-AC) is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC. In this paper, we investigate the beamforming design problem for multiple-input multiple-output (MIMO) ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio (SINR) constraints of communication users. Particularly, we discuss two cases of ISAC transmit beamforming, i.e., Case-I and Case-II, which do not have and do have the dedicated probing signal, respectively. For these two cases of transmit beamforming design problems, we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors. Then, we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems. Furthermore, we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff. Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario, whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario. It is also shown that the stronger the correlation between radar and communication channels, the greater the performance gain of the system.

Optimal configuration and pricing strategies for electric-heat cloud energy storage: A Stackelberg game approach

This paper utilizes a reconfigurable intelligent surface (RIS) to enhance the anti-jamming performance of wireless communications, due to its powerful capability of constructing smart and reconfigurable radio environment. In order to establish the practical interactions between the base station (BS) and the jammer, a Bayesian Stackelberg game is formulated, where the BS is the leader and the jammer acts as the follower. Specifically, with the help of a RIS-assisted transmitter, the BS attempts to reliably convey information to users with maximum utilities, whereas the smart jammer tries to interfere the signal reception of users with desired energy efficiency (EE) threshold. Since the BS and the jammer are not cooperative parties, the practical assumption that neither side can obtain the other's strategies is adopted in the proposed game, and the angular information based imperfect channel state information (CSI) is also considered. After tackling the practical assumption by using Cauchy-Schwarz inequality and the imperfect angular information by using the discretization method, the closed-form solution of both sides can be obtained via the duality optimization theory, which constitutes the unique Stackelberg equilibrium (SE). Numerical results demonstrate the superiority and validity of our proposed robust schemes over the existing approaches.

Optimal scheduling of integrated demand response-enabled integrated energy systems with uncertain renewable generations: A Stackelberg game approach

For microgrids with photovoltaic (PV) prosumers, the effective energy sharing management (ESM) is important for the operation. In this paper, a Stackelberg game approach for ESM is proposed. First, according to feed-in-tariff of PV energy, a system model of ESM is introduced, which includes the profit model of microgrid operator (MGO) and the utility model of PV prosumers. Moreover, an hour-ahead optimal pricing model of ESM is proposed. The model is designed based on Stackelberg game, where the MGO acts as the leader and all participating prosumers are considered as the followers. With the proof of equilibrium and uniqueness of the Stackelberg equilibrium, the MGO is obligated to coordinate the sharing of PV energy with maximization of the own profit, while the prosumers are autonomous to maximize their utilities with demand response availability. Finally, a billing mechanism is designed to deal with the uncertainty of PV energy and load consumption. By using the collected data from realistic PV-roofed buildings, the effectiveness of the model is verified in terms of the profit of MGO, the utilities of prosumers, and the net energy of the microgrid.

Switching defence for switched systems under malicious attacks: A Stackelberg game approach

Reconfigurable intelligent surface (RIS) assisted air-to-ground wireless powered communication networks (WPCNs) are constructed to promote the energy efficiency of the system, in which unmanned aerial vehicles (UAV) reflects energy towards the energy-constrained hybrid access points (HAP) through RIS. Subsequently, HAP uses the collected energy to communicate with users in blind areas through the RIS-UAV. By optimizing parameters such as charging time ratio, transmit power and phase shifts matrix, the energy efficiency for single and multiuser scenarios are maximized, respectively. The energy efficiency is modeled as a non-convex quadratic programming problem with inequality constraints in the single-user scenario. Then the problem is converted into an equivalent convex problem by using the Taylor expansion and convex approximation method. A joint optimization algorithm of power and phase shifts is proposed to obtain a feasible solution. The energy efficiency is modeled as a fractional programming problem with non-convex inequality constraints in the multi-user scenario, and the feasible solution is obtained by proposing an alternating algorithm. Finally, both two scenarios are compared with the system of traditional amplify-and-forward (AF) relay, respectively. Finally, the simulation results show that the proposed algorithms can provide up with 150% and 160% improvement of the energy efficiency in the single and multi-user scenarios, respectively, compared to the traditional AF relay.