Smart glasses that support augmented reality (AR) have the potential to become the consumer's primary medium of connecting to the future internet. For the best quality of user experience, AR glasses must have a small form factor and long battery life, while satisfying the data rate and latency requirements of AR applications. To extend the AR glasses' battery life, the computation and processing involved in AR may be offloaded to a companion device, such as a smartphone, through a wireless connection. Sidelink (SL), i.e., the D2D communication interface of 5G NR, is a potential candidate for this wireless link. In this paper, we use system-level simulations to analyze the feasibility of NR SL for supporting AR. Our simulator incorporates the PHY layer structure and MAC layer resource scheduling of 3GPP SL, standard 3GPP channel models, and MCS configurations. Our results suggest that the current SL standard specifications are insufficient for high-end AR use cases with heavy interaction but can support simpler previews and file transfers. We further propose two enhancements to SL resource allocation, which have the potential to offer significant performance improvements for AR applications.

In autonomous mobile ad hoc networks (MANETs) where each user is its own authority, the issue of cooperation enforcement must be solved first to enable networking functionalities such as packet forwarding, which becomes very difficult under noisy and imperfect monitoring. In this paper, we consider cooperation enforcement in autonomous mobile ad hoc networks under noisy and imperfect observation and study the basic packet forwarding among users through the repeated game models with imperfect information. A belief evaluation framework is proposed to obtain cooperation-enforcement packet forwarding strategies only based on each node's private information including its own past actions and imperfect observation of other nodes' information. More importantly, we not only show that the proposed strategy with belief system can maintain the cooperation paradigm but also establish its performance bounds. The simulation results illustrate that the proposed belief evaluation framework can enforce the cooperation with only a small performance degradation compared with the unconditionally cooperative outcomes when noisy and imperfect observation exist.

Dynamic spectrum access has become a promising approach to fully utilize the scarce spectrum resources. In a dynamically changing spectrum environment, it is very important to consider the statistics of different users' spectrum access so as to achieve more efficient spectrum allocation. In this paper, we propose a primary-prioritized Markov approach for dynamic spectrum access through modeling the interactions between the primary and the secondary users as continuous-time Markov chains (CTMC). Based on the CTMC models, to compensate the throughput degradation due to the interference among secondary users, we derive the optimal access probabilities for the secondary users, by which the spectrum access of the secondary users is optimally coordinated, and the spectrum dynamics are clearly captured. Therefore, a good tradeoff can be achieved between the spectrum efficiency and fairness. The simulation results show that the proposed primary-prioritized dynamic spectrum access approach under proportional fairness criterion achieves much higher throughput than the CSMA-based random access approaches and the approach achieving max-min fairness. Moreover, it provides fair spectrum sharing among secondary users with only small performance degradation compared to the approach maximizing the overall average throughput.

In order to fully utilize scarce spectrum resources, dynamic spectrum allocation becomes a promising approach to increase the spectrum efficiency for wireless networks. However, the collusion among selfish network users may seriously deteriorate the efficiency of dynamic spectrum sharing. The network users' behaviors and dynamics need to be taken into consideration for efficient and robust spectrum allocation. In this paper, we model the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. In order to combat user collusion, we propose a pricing-based collusion-resistant dynamic spectrum allocation approach to optimize overall spectrum efficiency, while not only keeping the participating incentives of the selfish users but also combating possible user collusion. The simulation results show that the proposed scheme achieves high efficiency of spectrum usage even with the presence of severe user collusion.

In self-organized mobile ad hoc networks (MANETs) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other or honestly revealing its private information, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by awarding some payment for cooperative behaviors. In this paper, we consider efficient routing in self-organized MANETs and model it as multi-stage dynamic pricing games. A game theoretical framework for dynamic pricing-based routing in MANETs is proposed to maximize the sender/receiveriquests payoff by considering the dynamic nature of MANETs. Meanwhile, the forwarding incentives of the relay nodes can also be maintained by optimally pricing their packet-forwarding services based on the auction rules and introducing the cartel maintenance enforcing mechanism. The simulation results illustrate that the proposed dynamic pricing-based routing approach has significant performance gains over the existing static pricing approaches.

In distributed wireless networks without centralized control, each user is its own authority to maximize its own performance. This distributed characteristic provides the users with the incentives of greedy competitions for the network resources such as bandwidth and transmission time. Such competitions deteriorate the system performance dramatically and result in low non-cooperative performances. Ensuring cooperation among selfish users can improve the performances and thus becomes an important issue for such wireless networks. In this paper, a Cartel Maintenance repeated game framework is proposed to enforce the cooperation among selfish users. The soul of Cartel Maintenance is to construct contracts among independent individuals for cooperative benefits and non-cooperative punishment, so as to limit inefficient competitions. In the proposed framework, a trigger-punishment game rule is designed to encourage the users to follow the cooperative strategy. First, all users agree to cooperate. Then in the following time slot, if users observe the others play cooperatively, cooperation will be played. If some users detect that others may defect based on the observed information, these users will play punishment phases for a certain period of time. This punishment is optimized so that the gain obtained by the deviation users is outweighed by the future punishments. Therefore, no user has the incentives to deviate, and the cooperation among selfish users is enforced. Then, the framework is employed to the multiple random access scenarios in wireless networks with selfish users, where the closed-form optimal solutions of cooperation enforcement are derived. The simulation results show that the proposed scheme can achieve significant performance gains over the non-cooperation scheme by having enough punishment threat to keep the cooperation among users.

In this paper, a distributive non-cooperative game is proposed to perform sub-channel assignment, adaptive modulation, and power control for multi-cell multi-user orthogonal frequency division multiplexing access (OFDMA) networks. Each individual user's goal is to minimize his/her own transmitted power in a distributed manner under the constraints that the desirable rate is achieved and the transmitted power is bounded. The pure non-cooperative game may result in non-convergence or some undesirable Nash Equilibriums with low system and individual performances. To enhance the performances, a virtual referee is introduced to the networks and is in charge of monitoring and improving the outcome of non-cooperative competition for resources among the distributed users. If the game outcome is not desirable, either the required transmission rates should be reduced or some users should be prevented from using some radio resources such as sub-channels, so that the rest of users can share the limited resources more efficiently. Moreover, it can be shown that the introduction of the virtual referee does not increase the complexity of the networks. From the simulation results in a two-cell case, the proposed scheme reduces the transmitted power by 80% and 25% compared with the fixed channel assignment algorithm and the iterative water-filling algorithm in the literature, respectively. The achievable rate can be improved by 10%. In a multi-cell case, the proposed scheme can have up to 40% power reduction compared with the iterative water-filling algorithm when the co-channel interferences are severe.

In cooperative ad-hoc networks, nodes belong to the same authority and pursue the common goals, and will usually unconditionally help each other. Consequently, without necessary countermeasures, such networks are extremely vulnerable to insider attacks, especially under noise and imperfect monitoring. In this paper, we present a game theoretic analysis of securing cooperative ad-hoc networks against insider attacks in the presence of noise and imperfect monitoring. By focusing on the most basic networking function, namely routing and packet forwarding, we model the interactions between good nodes and insider attackers as secure routing and packet forwarding games. The worst case scenarios are studied where initially good nodes do not know who the attackers are while insider attackers know who are good. The optimal defense strategies have been devised in the sense that no other strategies can further increase the good nodes' payoff under attacks. Meanwhile, the optimal attacking strategies and the maximum possible damage that can be caused by attackers have been discussed. Extensive simulation studies have also been conducted to evaluate the effectiveness of the proposed strategies

Dynamic spectrum allocation becomes a promising approach to increase the spectrum efficiency for wireless networks. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double-auction rules. Moreover, a belief system is developed to assist selfish users to dynamically update their strategies adaptive to the network dynamics and substantially decrease the pricing overhead. The simulation results show that our proposed scheme not only approaches optimal outcomes but also has low overhead.

In autonomous mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by rewarding some payment for cooperative behaviors. Here, we model the pricing and routing in autonomous MANETs as multi-stage dynamic games. A dynamic pricing framework is proposed to maximize the sender/receiver's payoff by considering the dynamic nature of MANETs. Meanwhile, the forwarding incentives of the relay nodes can also be maintained by providing the optimal payments based on the auction rules. The simulation results illustrate that the proposed dynamic pricing schemes have significant performance gains over the existing static pricing algorithms.

In order to fully utilize the scarce spectrum resources, with the development of cognitive radio technologies, dynamic spectrum allocation becomes a promising approach to increase the efficiency of spectrum usage. In this paper, we consider the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. A belief-assisted dynamic pricing approach is proposed to optimize overall spectrum efficiency while keeping the participating incentives of the users based on double auction rules. Moreover, considering the budget constraints of the unlicensed users, a dynamic programming approach is further developed to optimize the spectrum allocation over time. The simulation results show that our proposed scheme not only approaches optimal outcomes with low overhead compared to general continuous double auction mechanisms, but also fully exploits the time diversity of spectrum resources when budget constraints exist

In autonomous mobile ad hoc networks (MANET) where each user is its own authority, the issue of cooperation enforcement must be solved first to enable network functioning, such as packet forwarding, which becomes very difficult under noise and imperfect monitoring. In this paper, we focus on cooperation enforcement in autonomous mobile ad hoc networks under noise and imperfect observation and study the basic packet-forwarding function using the repeated game models with imperfect information. A belief-based packet forwarding framework is proposed to obtain cooperation-enforcement strategies solely based on each node's own past actions and its private imperfect observation of other nodes' information. The simulation results illustrate that the proposed belief-based packet forwarding approach can enforce the cooperation with only a small performance degradation compared with the unconditionally cooperative outcomes when noise and imperfect observation exist

In self-organized mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. In this paper, we focus on cooperation enforcement in the self-organized mobile ad hoc networks with noise and imperfect observation and study the basic packet-forwarding function using the repeated game models with imperfect information. A belief-based packet forwarding framework is proposed to obtain cooperation-enforcement strategies solely based on each node's own past actions and its private imperfect observation of other nodes' information. The simulation results illustrate that the proposed belief-based packet forwarding approach can enforce the cooperation with only a small performance degradation compared to the unconditionally cooperative outcomes in the ad hoc networks with noise and imperfect observation.

In self-organized mobile ad hoc networks (MANET) where each user is its own authority, fully cooperative behaviors, such as unconditionally forwarding packets for each other, cannot be directly assumed. The pricing mechanism is one way to provide incentives for the users to act cooperatively by rewarding some payment for cooperative behaviors. In this paper, we model the pricing and routing in self-organized MANETs as multistage dynamic games. A dynamic pricing framework is proposed to maximize the sender/receiver's payoff by considering the dynamic nature of MANETs, meanwhile, keeping the forwarding incentives of the relay nodes by providing the optimal payments based on the auction rules. The simulation results illustrate that the proposed dynamic pricing schemes have significant performance gains over the existing static pricing algorithms.

In this paper, a fair scheme to allocate subcarrier, rate, and power for multiuser orthogonal frequency-division multiple-access systems is proposed. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach considers a new fairness criterion, which is a generalized proportional fairness based on Nash bargaining solutions and coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between two users. Then a multiuser bargaining algorithm is developed based on optimal coalition pairs among users. The simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have a comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than that of the scheme with max-min fairness. Moreover, the proposed iterative fast implementation has the complexity for each iteration of only O(K/sup 2/Nlog/sub 2/N+K/sup 4/), where N is the number of subcarriers and K is the number of users.

In this paper, we consider wireless networks with multiple distributed users. The users transmit their data packets to a communication node via some multi-access protocol. Then the node transmits the packets to a remote destination via a lossy wireless link. The cost for each user's transmission is modelled as a function of its transmission rate (TR). If a user's packet is successfully transmitted to the destination, a profit will be obtained. However, this profit is reduced by the transmission contention among users and the lossy wireless channel. Each user controls its TR to maximize its profit in a distributed manner. If no rule is applied for rate control, each user will select a large TR resulting in having a low performance. In order to improve the system performance, we develop a distributed rate control algorithm using an optimal Cartel maintenance strategy. In this strategy, each user prefers to cooperate for rate control, because deviation from cooperation will be punished by other users for a period of time. From the simulation results, we can see that the proposed distributed scheme can enforce the cooperation among users and achieve much better performance than the noncooperative transmission.

A fair and simple scheme to allocate subcarrier, rate, and power for multiuser OFDMA systems is considered. The problem is to maximize the overall system rate, under each user's maximal power and minimal rate constraints, while considering the fairness among users. The approach proposes the fairness and low complexity implementation based on Nash bargaining solutions and coalitions. First, a two-user algorithm is developed to bargain subcarrier usage between both users. Based on this algorithm, we develop a multiuser bargaining algorithm where optimal coalition pairs among users are constructed. Simulation results show that the proposed algorithms not only provide fair resource allocation among users, but also have comparable overall system rate with the scheme maximizing the total rate without considering fairness. They also have much higher rates than the scheme with max-min fairness. The proposed algorithms have complexity O(NlogN), where N is the number of subcarriers.

In this paper, we use a noncooperative game approach to have distributed subchannel assignment, adaptive modulation, and power control for multi-cell OFDM networks. The goal is to minimize the overall transmitted power under each user's maximal power and minimal rate constraints. Our contribution is to model and solve this complicated problem by a distributed noncooperative game approach: Each user water-fills its power to different subchannels regarding other users' powers as interference. A noncooperative game is constructed for each user to compete with others. A method is constructed as a mediator (judge) for the game. From the simulation results, the proposed scheme reduces the overall transmitted power greatly compared with the fixed channel assignment algorithm and pure water-filling algorithm.

Capacity optimization in a multicell OFDMA system where each cell has multiple users is investigated in this work. The objective is to find an assignment of users to the sets of sub-carrier, their transmission rates for the sub-carrier, and power allocation such that the total system capacity is increased, while users meet a minimum total rate requirement and a power constraint. Since the optimal solution involves an exhaustive search or complex nonlinear integer programming, we develop sub-optimal low complexity algorithms. We propose a two-step scheme: First an initial channel and data rate allocations are determined by two initialization algorithms. Then we refine the assigned rates by an iterative algorithm. From simulation results, the proposed algorithms can efficiently allocate resources to increase the overall system capacity and reduce the allocation outages.

Orthogonal frequency division multiplexing (OFDM) with multiple antennas makes it possible for efficient transmission of high-speed multimedia over wireless channels. This paper proposes an approach for power-efficient video transmission of MPEG-4 fine granularity scalable (FGS) bit-stream over OFDM systems with multiple antennas at both transmitter and receiver. Our proposed approach minimizes the total distortion while satisfying the constraint of transmission power, which is achieved by optimal power allocation and transmission rate control of power efficient assignment of scalable source to spatial subchannels. The performance of our proposed scheme is compared with one using fixed transmission rate or power allocation. Simulation results show significant performance gain of our approach.

Audio broadcasting over wireless networks is a challenging task due to the limited bandwidth of the wireless channel and limited battery resource in the handheld devices. This paper proposes a power-efficient distortion-minimized rate allocation approach, which maintains the power consumption constraint at the mobile hosts and meanwhile minimizes the total distortions for group users in wireless systems. The performance of our proposed scheme is compared with a fixed rate allocation and downlink power controlled scheme in cellular CDMA systems. The simulation results show that our proposed power-efficient distortion-minimized scheme achieves significant performance gains of audio quality compared to the fixed scheme.

Video communication over wireless links using handheld devices is a challenging task due to the time-varying characteristics of the wireless channels and limited battery resources. Rate-distortion (RD) analysis plays a key role in video coding and communication systems, and usually the RD relation does not assume any power constraint. We investigate the relations of rate, distortion and power consumption. Based on those relations, we propose a power-minimized bit-allocation scheme considering the processing power, for source coding and channel coding, jointly with the transmission power. The total bits are allocated between source and channel coders, according to wireless channel conditions and video quality requirements, to minimize the total power consumption for a single user and a group of users in a cell, respectively. Simulation results show that our proposed joint power-control and bit-allocation scheme achieves high power savings compared to the conventional scheme.

Video communication over a wireless link is a very challenging task due to the time-varying characteristics of the wireless channel and limited battery resources in the handheld devices. This paper proposes an end-to-end power-optimized approach for video communication. The power consumed in complexity-reconfigurable source coding, channel-adaptive unequal error protection (UEP), and video transmission is analyzed. Power-minimized rate allocation is presented to achieve the minimal power consumption in the mobile host while maintaining the desired video quality. Simulation results show that our power-optimized scheme achieves significant power saving compared to the existing scheme.

Video communication over wireless link is a challenging task due to the time-varying characteristics of a wireless channel and limited battery resource in the handheld devices. This paper proposes a power-optimized approach for video communication, which simultaneously controls the transmission power, source rate and error protection level to minimize the total power consumption for all users. The performance of the cellular CDMA system using our proposed scheme is compared with the one using a fixed power-control scheme. The simulation results show that our proposed joint power control and source-channel coding scheme achieves significant power saving compared to the fixed scheme.