Partner selection method in cooperative spatial modulation (CSM) system

In this work, to achieve higher capacity, spatial modulation (SM) is utilized in a cooperative scheme in two different models of Cooperative SM, where SM is applied either at the source or the selected partner through an antenna array. A theoretical model of SM capacity is defined based on closed form lower and upper bound of the SM capacity. Based on the theoretical analysis of the channel capacity in both CSM systems the simplest and easier to implement selection criteria have been suggested to select a single partner to maximize CSM capacity. The CSM system in which SM is applied through the partner’s antenna array is providing significant enhancement over the other CSM model and cooperative multiple-input-multiple-output (CO-MIMO) networks based on multiple partners. Moreover, the system with a single randomly selected partner equipped with four antennas, behaves similarly as the best configuration of CO-MIMO based on the cooperation of four partners with the computational complexity linearly increases with the number of available partners to help. All of the theoretical findings are verified through simulation studies.     

Reputation-based network selection mechanism using game theory

Current and future wireless environments are based on the coexistence of multiple networks supported by various access technologies deployed by different operators. As wireless network deployments increase, their usage is also experiencing a significant growth. In this heterogeneous multi-technology multi-application multi-terminal multi-user environment users will be able to freely connect to any of the available access technologies. Network selection mechanisms will be required in order to keep mobile users “always best connected” anywhere and anytime. In such a heterogeneous environment, game theory techniques can be adopted in order to understand and model competitive or cooperative scenarios between rational decision makers. In this work we propose a theoretical framework for combining reputation-based systems, game theory and network selection mechanism. We define a network reputation factor which reflects the network’s previous behaviour in assuring service guarantees to the user. Using the repeated Prisoner’s Dilemma game, we model the user–network interaction as a cooperative game and we show that by defining incentives for cooperation and disincentives against defecting on service guarantees, repeated interaction sustains cooperation.     

An overview of shadowed fading wireless channels in terms of a cascaded approach

Wireless channels suffer from short term fading and shadowing simultaneously. While simple models of short term fading are based on the Nakagami-m distribution, short term fading can also be described as a cascading process allowing the modeling of wireless channels having worse fading than what exists in Nakagami-m channels. Shadowing, on the other hand, has been traditionally modeled as a lognormal process, making the analysis of shadowed fading channels cumbersome. Taking note of the fact that the lognormal density arises out of a multiplicative process, it was shown that shadowing can also be modeled as a cascading process. Utilizing such a vision of shadowing, this work provides an overview of a unified cascaded approach to model wireless channels when short term fading and shadowing are simultaneously present. The degradation in such shadowed fading channels is estimated in terms of error rates and outage probabilities. Results are compared to those of the exact model based on lognormal density as well as random number simulation. Analysis demonstrates that error rates and outage probabilities obtained using the exact model (lognormal model for shadowing) agree very well with those obtained through the composite cascaded model as well as random number simulations.     

Cooperative diversity performance of selection relaying over correlated shadowing

The study of relaying systems has found renewed interest in the context of cooperative diversity for communication channels suffering from fading. In particular, dual-hop relaying with diversity combining of the relayed and direct path at the receiver has practical importance and can be considered as a building block for forming larger communication systems. This paper presents novel analytical expressions and numerical results on cooperative diversity performance using selection relaying over correlated lognormal channels for both SC and MRC techniques at the receiver. In addition, an exact framework for comparing the performance and efficiency of the medium access protocol and relay capabilities (TDMA/half-duplex, SDMA/full-duplex) is proposed. Finally, based on the analysis and novel mathematical expressions for the outage probability, we investigate the impact of the lognormal parameters (including correlation) on the cooperative system performance and its efficiency.     

Continuum modeling of cooperative traffic flow dynamics

This paper presents a continuum approach to model the dynamics of cooperative traffic flow. The cooperation is defined in our model in a way that the equipped vehicle can issue and receive a warning massage when there is downstream congestion. Upon receiving the warning massage, the (up-stream) equipped vehicle will adapt the current desired speed to the speed at the congested area in order to avoid sharp deceleration when approaching the congestion. To model the dynamics of such cooperative systems, a multi-class gas-kinetic theory is extended to capture the adaptation of the desired speed of the equipped vehicle to the speed at the downstream congested traffic. Numerical simulations are carried out to show the influence of the penetration rate of the equipped vehicles on traffic flow stability and capacity in a freeway.     

Splitting algorithm for DMT optimal cooperative MAC protocols in wireless mesh networks

A cooperative protocol for wireless mesh networks is proposed in this paper. The protocol implements both on-demand relaying and a selection of the best relay terminal so only one terminal is relaying the source message when cooperation is needed. Two additional features are also proposed. The best relay is selected with a splitting algorithm. This approach allows fast relay selection within less than three time-slots, on average. Moreover, a pre-selection of relay candidates is performed prior to the splitting algorithm. Only terminals that are able to improve the direct path are pre-selected. So efficient cooperation is now guaranteed. We prove that this approach is optimal in terms of diversity-multiplexing trade-off. The protocol has been designed in the context of Nakagami-m fading channels. Simulation results show that the performance of the splitting algorithm does not depend on channel statistics.     

Joint optimal fair cooperative spectrum sensing and transmission in cognitive radio

Since the sensing power consumption of cooperative spectrum sensing (CSS) will decrease the throughput of secondary users (SU) in cognitive radio (CR), a joint optimal model of fair CSS and transmission is proposed in this paper, which can compensate the sensing overhead of cooperative SUs. The model uses the periodic listen-before-transmission method, where each SU is assigned a portion of channel bandwidth, when the primary user (PU) is estimated to be free by the coordinator. Then, a joint optimization problem of local sensing time, number of cooperative SUs, transmission bandwidth and power is formulated, which can compensate the sensing overhead of cooperative SUs appropriately through choosing suitable compensating parameter. The proposed optimization problem can be solved by the Polyblock algorithm. Simulation results show that compared with the traditional model, the total system throughput of the fairness cooperation model decreases slightly, but the total throughput of the cooperative SUs improves obviously.     

Bandwidth allocation in cooperative wireless networks: Buffer load analysis and fairness evaluation

In modern cooperative wireless networks, the resource allocation is an issue of major significance. The cooperation of source and relay nodes in wireless networks towards improved performance and robustness requires the application of an efficient bandwidth sharing policy. Moreover, user requirements for multimedia content over wireless links necessitate the support of advanced Quality of Service (QoS) features. In this paper, a novel bandwidth allocation technique for cooperative wireless networks is proposed, which is able to satisfy the increased QoS requirements of network users taking into account both traffic priority and packet buffer load. The performance of the proposed scheme is examined by analyzing the impact of buffer load on bandwidth allocation. Moreover, fairness performance in resource sharing is also studied. The results obtained for the cooperative network scenario employed, are validated by simulations. Evidently, the improved performance achieved by the proposed technique indicates that it can be employed for efficient traffic differentiation. The flexible design architecture of the proposed technique indicates its capability to be integrated into Medium Access Control (MAC) protocols for cooperative wireless networks.     

Outlier-aware cooperative spectrum sensing in cognitive radio networks

This paper considers the problem of cooperative spectrum sensing in cognitive radio networks (CRN). Communication in CRNs may be disrupted due to the presence of malicious secondary users (SU) or channel impairments such as shadowing. This paper proposes a spatio-frequency framework that can detect and track malicious users and anomalous measurements in CRNs. The joint problem of spectrum sensing and malicious user identification is posed as an optimization problem that aims to exploit the sparsity inherent to both, spectrum occupancy and malicious user occurrence. Proposed scheme obtains improved performance by utilizing node location information, and can handle missing or inaccurate location information, and noisy SU reports. A distributed block-coordinate descent-based algorithm is proposed that is shown to outperform the state-of-the-art PCA-based approach, and is flexible enough to defeat a variety of attacks encountered in SU networks. An online algorithm, that can handle incorporate multiple SU readings sequentially and adapt to time-varying channels, primary user, and malicious user activity, is also proposed and shown to be consistent. Simulation results demonstrate the efficacy of the proposed algorithms.     

Cooperation and its evolution in growing systems with cultural reproduction

We explore the evolution of cooperation in the framework of the evolutionary game theory using the prisoner’s dilemma as metaphor of the problem. We present a minimal model taking into account the growing process of the systems and individuals with imitation capacity. We consider the topological structure and the evolution of strategies decoupled instead of a coevolutionary dynamic. We show conditions to build up a cooperative system with real topological structures for any natural selection intensity. When the system starts to grow, cooperation is unstable but becomes stable as soon as the system reaches a small core of cooperators whose size increases when the intensity of natural selection decreases. Thus, we reduce the evolution of cooperative systems with cultural reproduction to justify a small initial cooperative structure that we call cooperative seed. Otherwise, given that the system grows principally as cooperator whose cooperators inhabit the most linked parts of the system, the benefit-cost ratio required for cooperation evolve is drastically reduced compared to the found in static networks. In this way, we show that in systems whose individuals have imitation capacity the growing process is essential for the evolution of cooperation.     

Spatial snowdrift game in heterogeneous agent systems with co-evolutionary strategies and updating rules

We propose an evolutionary snowdrift game model for heterogeneous systems with two types of agents, in which the inner-directed agents adopt the memory-based updating rule while the copycat-like ones take the unconditional imitation rule; moreover, each agent can change his type to adopt another updating rule once the number he sequentially loses the game at is beyond his upper limit of tolerance. The cooperative behaviors of such heterogeneous systems are then investigated by Monte Carlo simulations. The numerical results show the equilibrium cooperation frequency and composition as functions of the cost-to-benefit ratio r are both of plateau structures with discontinuous steplike jumps, and the number of plateaux varies non-monotonically with the upper limit of tolerance vTas well as the initial composition of agents fa0.Besides, the quantities of the cooperation frequency and composition are dependent crucially on the system parameters including vT, fa0, and r. One intriguing observation is that when the upper limit of tolerance is small, the cooperation frequency will be abnormally enhanced with the increase of the cost-to-benefit ratio in the range of 0 < r < 1/4. We then probe into the relative cooperation frequencies of either type of agents, which are also of plateau structures dependent on the system parameters. Our results may be helpful to understand the cooperative behaviors of heterogenous agent systems.     

Wireless transmission using cooperation on demand

Mobile users with single antennas can still take advantage of spatial diversity through repetition based cooperative transmission. In this paper, we consider a scheme in which the cooperation is triggered only if the source–destination channel is of an unacceptable quality. Therefore, the destination selects one relay out of a decoding set of relays for cooperation. We analyze the end-to-end outage probability in slow and fast fading environments and we evaluate the usefulness of relaying when the source acts blindly and ignores the decision of the selected relay whether it may cooperate or not. The performance in both environments are evaluated through analysis and simulations in terms of end-to-end outage probability and the number of active relays. Some selected performance results show that some selected computer simulation based results coincide with our analytical results.     

RSSI-based hybrid algorithm for real-time tracking in underground mining by using RFID technology

Knowing the precise and real-time location of underground mining workers is essential for their health and safety in any emergency. However, the standard Global Positioning System (GPS) is insufficient for such indoor environments as it requires new infrastructure based on different technologies and algorithms. Instead, Radio Frequency Identification (RFID)-based real-time indoor localization systems and a hybrid algorithm are developed. The received-signal-strength (RSS) based positioning techniques are investigated and applied in indoor environments. A unique hybrid approach based on fingerprinting is proposed and developed to solve the disadvantages of the existing techniques. Consequently, the accuracy of this one-of-a-kind algorithm is found to be 2.52 m in an office and 3.13 m in an underground mine. We also compared the proposed hybrid algorithm to the Weighted K-Nearest Neighbor (WKNN). WKNN, on the other hand, has an accuracy of 4.01 m in the office and 4.33 m in underground mining environments.     

Deep reinforcement learning based relaying for buffer-aided cooperative communications

The advances in deep reinforcement learning (DRL) have shown a great potential in solving physical layer-related communication problems. This paper investigates DRL for the relay selection in buffer-aided (BA) cooperative networks. The capability of DRL in handling highly-dimensional problems with large state and action spaces paves the way for exploring additional degrees-of-freedom by relaxing the restrictive assumptions around which conventional cooperative networks are usually designed. This direction is examined in our work by advising and analyzing advanced DRL-based BA relaying strategies that can cope with a variety of setups in multifaceted cooperative networks. In particular, we advise novel BA relaying strategies for both parallel-relaying and serial-relaying systems. For parallel-relaying systems, we investigate the added value of merging packets at the relays and of activating the inter-relay links. For serial-relaying (multi-hop) systems, we explore the improvements that can be reaped by merging packets and by allowing for the simultaneous activation of sufficiently-spaced hops. Simulation results demonstrate the capability of DRL-based BA relaying in achieving substantial improvements in the network throughput while the adequate design of the reward/punishment in the learning process ensures fast convergence speeds.     

Cooperative acceleration of task performance: Foraging behavior of interacting multi-robots system

We study the effectiveness of cooperative behavior in a society of interacting agents. After reviewing the problem and defining the concept of swarm intelligence, we examine collective behavior of many-body active clusters through a task to gather pucks in the field. In this study, we used a robot with a simple structure which has a driving system and the simplest interacting means; a light and some sensors. The effectiveness of group behavior was studied under various (homogeneous, localized) puck distributions with real experiment, simulation, and analysis. To evaluate the efficiency of group behavior, we examined the scaling relation between the task completion time and the number of robots, and the relation between the interaction period and the efficiency of group. We found that a cooperation between agents by a simple interaction is very efficient in enhancing the performance of the group compared with independent individuals.     

Memory-based evolutionary game on small-world network with tunable heterogeneity

Most papers about evolutionary games on graph assume agents have no memory. Yet, in the real world, interaction history can also affect an agent’s decision. So we introduce a memory-based agent model and investigate the Prisoner’s Dilemma game on a Heterogeneous Newman-Watts small-world network based on a Genetic Algorithm, focusing on heterogeneity’s role in the emergence of cooperative behaviors. In contrast with previous results, we find that a different heterogeneity parameter domain range imposes an entirely different impact on the cooperation fraction. In the parameter range corresponding to networks with extremely high heterogeneity, the decrease in heterogeneity greatly promotes the proportion of cooperation strategy, while in the remaining parameter range, which relates to relatively homogeneous networks, the variation of heterogeneity barely affects the cooperation fraction. Also our study provides a detailed insight into the microscopic factors that contribute to the performance of cooperation frequency.     

Coevolving agent strategies and network topology for the public goods games

Much of human cooperation remains an evolutionary riddle. Coevolutionary public goods games in structured populations are studied where players can change from an unproductive public goods game to a productive one, by evaluating the productivity of the public goods games. In our model, each individual participates in games organized by its neighborhood plus by itself. Coevolution here refers to an evolutionary process entailing both deletion of existing links and addition of new links between agents that accompanies the evolution of their strategies. Furthermore, we investigate the effects of time scale separation of strategy and structure on cooperation level. This study presents the following: Foremost, we observe that high cooperation levels in public goods interactions are attained by the entangled coevolution of strategy and structure. Presented results also confirm that the resulting networks show many features of real systems, such as cooperative behavior and hierarchical clustering. The heterogeneity of the interaction network is held responsible for the observed promotion of cooperation. We hope our work may offer an explanation for the origin of large-scale cooperative behavior among unrelated individuals.     

From the infrared to the visible range: Spectroscopic studies of ytterbium doped oxyborates

The spectroscopic study of yttrium oxyborates doped with trivalent ytterbium is conducted in the UV-Visible and infrared range. The multiplicity of the ytterbium environments in the studied compounds leads to complex emission spectra in the infrared and excitation spectra in the ultraviolet. Different ²F_5/2 and ²F_7/2 transitions have been pointed out. The emission extends up to 1090 nm for one compound. A correlation was evidenced between position and de-excitation mode of a charge transfer band and ytterbium environment for both oxyborates. Decay time dependence as a function of ytterbium concentration is also reported. For the highest concentration, a blue-green luminescence can be observed under strong IR excitation. Its study revealed two possible mechanisms: erbium ion emission at 550 nm after up-conversion and cooperative luminescence of ytterbium ions.     

Admissible consensus and consensualization of high-order linear time-invariant singular swarm systems

Admissible consensus analysis and consensualizing controller design problems for high-order linear time-invariant singular swarm systems are investigated. Firstly, by projecting the state of a singular swarm system onto a consensus subspace and a complement consensus subspace, a necessary and sufficient condition for admissible consensus is presented in terms of linear matrix inequalities (LMIs). An approach to decrease the calculation complexity is proposed, by which only three LMIs independent of the number of agents need to be checked. Then, by using the changing variable method, sufficient conditions for admissible consensualization are shown. An explicit expression of the consensus function is given, and it is shown that the modes of the consensus function can be arbitrarily placed if each agent is R$R$-controllable and impulse controllable and the interaction topology has a spanning tree. Finally, theoretical results are applied to deal with cooperative control problems of multi-agent supporting systems.