A game-theoretic analysis is applied to the evaluation of capacity and stability of a wireless ad hoc network in which each source node independently chooses a route to the destination node so as to enhance throughput. First, the throughput of individual multihop transmission with rate adaptation is evaluated. Observations from this evaluation indicate that the optimal number of hops in terms of the achievable end-to-end throughput depends on the received signal-to-noise ratio. Next, the decentralized adaptive route selection problem in which each source node competes for resources over arbitrary topologies is defined as a game. Numerical results reveal that in some cases this game has no Nash equilibria; i.e., each rational source node cannot determine a unique route. The occurrence of such cases depends on both the transmit power and spatial arrangement of the nodes. Then, the obtained network throughput under the equilibrium conditions is compared to the capacity under centralized scheduling. Numerical results reveal that when the transmit power is low, decentralized adaptive route selection may attain throughput near the capacity.

Ternary content addressable memory (TCAM) is popular LSI for use in high-throughput forwarding engines on routers. However, the unique structure applied in TCAM consume huge amounts of power, therefore it restricts the ability to handle large lookup table capacity in IP routers. In this paper, we propose a commodity-memory based hardware architecture for the forwarding information base (FIB) application that solves the substantial problems of power and density. The proposed architecture is examined by a fabricated test chip with 40 nm embedded DRAM (eDRAM) technology, and the effect of power reduction verified is greatly lower than conventional TCAM based and the energy metric achieve 0.01 fJ/bit/search. The power consumption is almost 0.5 W at 250 Msps and 8M entries.

Motivated by the design of fault-tolerant multiprocessor interconnection networks, this paper considers the following problem: Given a positive integer t and a graph H, construct a graph G from H by adding a minimum number Δ(t, H) of edges such that even after deleting any t edges from G the remaining graph contains H as a subgraph. We estimate Δ(t, H) for the hypercube and torus, which are well-known as important interconnection networks for multiprocessor systems. If we denote the hypercube and the square torus on N vertices by QN and DN respectively, we show, among others, that Δ(t, QN) = O(tN log(log N/t + log 2e)) for any t and N (t 2), and Δ(1, DN) = N/2 for N even.

In this paper, we introduce the concept of a multi-operator mobile relay node (RN) for cellular networks on buses or trains. The installation of RNs improves spectral efficiency because an antenna with a higher gain than that of user equipment (UE) can be installed in an RN. However, installing different RNs for different operators is not efficient because of the large amount of space needed to install multiple RNs in a bus. Thus, sharing one RN among multiple operators is a more practical approach. When we use a multi-operator mobile RN, the required amount of resource for each operator varies independently as the RN moves. Consequently, we propose a system of shared-spectrum allocation among operators for RN-UEs communication. Shared bandwidth can be allocated to operators according to link quality in order to achieve effective utilization of radio resources. However, to introduce shared-spectrum allocation, fairness among the operators and the total efficiency of the system should be taken into consideration. Using computer simulations, we evaluate shared-spectrum allocation based on the Nash bargaining solution (NBS). The results, in terms of both fairness and efficiency, indicate that total throughput can be improved by approximately 20% compared with the situation where multiple operators install different RNs individually.

In densely deployed wireless local area network (WLAN) environments, the arbitrary deployment of WLAN access points (APs) can cause serious cell overlaps among APs. In such situations, the ability to realize adaptable coverage using transmission power control (TPC) is effective for improving the area spectral efficiency. Meanwhile, it should be guaranteed that no coverage holes occur and that connectivity between APs and wireless stations (STAs) is maintained. In this paper, the self-organization of coverage domains of APs using TPC is proposed. The proposed technique reduces the incidence of coverage overlaps without generating area coverage holes. To detect coverage holes, STAs and/or APs are used as sensors that inform each AP of whether or not the points at which they exist are covered by the APs. However, there is a problem with this approach in that when the density of STAs is not sufficiently large, the occurrence of area coverage holes is inevitable because the points at which the sensors do not exist are not guaranteed to be covered by APs. This paper overcomes the problem by focusing APs that belong to network's outer boundary (boundary APs) and prohibiting the APs from operating at low transmission power levels, the idea being that the coverage domains of such APs always include the region covered by only those APs. The boundary APs are determined by performing Delaunay triangulation of the set of points at which all APs exist. Simulation results confirm the effectiveness of the proposed TPC scheme in terms of its ability to reduce the total overlap area while avoiding the occurrence of area coverage holes.

In this study, a contextual multi-armed bandit (CMAB)-based decentralized channel exploration framework disentangling a channel utility function (i.e., reward) with respect to contending neighboring access points (APs) is proposed. The proposed framework enables APs to evaluate observed rewards compositionally for contending APs, allowing both robustness against reward fluctuation due to neighboring APs' varying channels and assessment of even unexplored channels. To realize this framework, we propose contention-driven feature extraction (CDFE), which extracts the adjacency relation among APs under contention and forms the basis for expressing reward functions in disentangled form, that is, a linear combination of parameters associated with neighboring APs under contention). This allows the CMAB to be leveraged with a joint linear upper confidence bound (JLinUCB) exploration and to delve into the effectiveness of the proposed framework. Moreover, we address the problem of non-convergence — the channel exploration cycle — by proposing a penalized JLinUCB (P-JLinUCB) based on the key idea of introducing a discount parameter to the reward for exploiting a different channel before and after the learning round. Numerical evaluations confirm that the proposed method allows APs to assess the channel quality robustly against reward fluctuations by CDFE and achieves better convergence properties by P-JLinUCB.

Sharing perceptual data (e.g., camera and LiDAR data) with other vehicles enhances the traffic safety of autonomous vehicles because it helps vehicles locate other vehicles and pedestrians in their blind spots. Such safety applications require high throughput and short delay, which cannot be achieved by conventional microwave vehicular communication systems. Therefore, millimeter-wave (mmWave) communications are considered to be a key technology for sharing perceptual data because of their wide bandwidth. One of the challenges of data sharing in mmWave communications is broadcasting because narrow-beam directional antennas are used to obtain high gain. Because many vehicles should share their perceptual data to others within a short time frame in order to enlarge the areas that can be perceived based on shared perceptual data, an efficient scheduling for concurrent transmission that improves spatial reuse is required for perceptual data sharing. This paper proposes a data sharing algorithm that employs a graph-based concurrent transmission scheduling. The proposed algorithm realizes concurrent transmission to improve spatial reuse by designing a rule that is utilized to determine if the two pairs of transmitters and receivers interfere with each other by considering the radio propagation characteristics of narrow-beam antennas. A prioritization method that considers the geographical information in perceptual data is also designed to enlarge perceivable areas in situations where data sharing time is limited and not all data can be shared. Simulation results demonstrate that the proposed algorithm doubles the area of the cooperatively perceivable region compared with a conventional algorithm that does not consider mmWave communications because the proposed algorithm achieves high-throughput transmission by improving spatial reuse. The prioritization also enlarges the perceivable region by a maximum of 20%.

The present paper introduces a prototype design and experimental results for a multi-user MIMO linear precoding system. A base station and two mobile stations are implemented by taking full advantage of the software-defined radio. The base station consists of general purpose signal analyzers and signal generators controlled by a personal computer. Universal software radio peripherals are used as mobile stations. Linear spatial precoding and a simple two-way channel estimation technique are adopted in this experimental system. In-lab and field transmission experiments are carried out, and the bit error rate performance is evaluated. The impact of the channel estimation error under average channel gain discrepancy between two mobile stations is analyzed through computer simulations. Channel estimation error is shown to have a greater influence on the mobile station with the greater average channel gain.

Network traffic keeps increasing due to the increasing popularity of video streaming services. Routers and switches in wire-line networks require guaranteed line rates as high as 20 Gbp/s as well as advanced quality of service (QoS). Hybrid SRAM and DRAM architecture previously presented with the benefit of high-speed and high-density, but it requires complex memory management. As a result, it has hardly supported large numbers of queue, which is an effective approach to satisfying the QoS requirements. This paper proposes an intelligent memory management unit (MMU) which is based on the hybrid architecture, where over 16k multi queues are integrated. The performance examined by the system board is zero-packet loss under the seamless traffic with 60–1.5 kByte packet-length (deterministic manner). Noticeable feature in this paper's architecture is eliminating the need for any premium memories but only low-cost commodity SRAMs and DRAMs are used. The intelligent MMU employs the head buffer architecture, which is suitable for supporting a large numbers of FIFO queues. An experimental board based on this architecture is embedded into a Router system to evaluate the performance. Using 16k queues at 20 Gbps, zero-packet loss is examined with 64-Byte to 1,500-Byte packet-length.

In existing systems of mobile routers, the frequency band is shared in uplinks from wireless terminals to mobile routers, and carrier sense multiple access with collision avoidance (CSMA/CA) is generally used as the medium access control protocol. To use the frequency band effectively, adaptive control is one promising approach. In this paper, a decentralized access control protocol in which mobile routers adaptively select the minimum contention window size is proposed. However, because of their mobility, which is one of the main difference between mobile routers and fixed access points, individual local area networks (LANs) consisting of the mobile routers and wireless terminals randomly interact with each other, and such random interactions can cause instability. To analyze the stability of the proposed control, evolutionary game theory is introduced because a system with random interactions between numerous decision-making entities can be analyzed by using evolutionary game theory. Using evolutionary game theory, the condition for existence of a convergence point is obtained. In addition, to implement the decentralized access control, a learning rule is proposed. In the proposed learning rule, each mobile router selects a strategy based on the result of past trials. From the simulation result, it is confirmed that the decentralized access control converges to a point closed to the stable state derived through evolutionary game theory.

The spectral efficiency of cooperative relaying in interference-limited environments in which a given channel is spatially reused is investigated. Cooperative relaying is a promising technique that uses neighboring stations to forward the data toward the destination in order to achieve spatial diversity gain. It has been reported that by introducing cooperative relaying into communication between an isolated source-destination pair, the error rate or spectral efficiency is generally improved. However, it is not intuitively clear whether cooperative relaying can improve the performance in interference-limited environments because the simultaneous transmission of multiple stations increases the number of interference signals. Assuming the most fundamental cooperative relaying arrangement, which consists of only one relay station, numerical results reveal that cooperative relaying is not always superior to non-cooperative single-hop and two-hop transmissions in terms of spectral efficiency.

This paper proposes a concept for a new technical field called wireless distributed network (WDN) as a strategic technical field to enable flexible networking and radio resource management (RRM) to cope with dynamic variation of spatially distributed traffic demands. As the core technical subject areas for the WDN, this paper identifies distributed networking for flexible network creation, cooperative transmission and reception for flexible link creation, and dynamic spectrum access for flexible radio resource management, and explains their technical features and challenges for constructing the WDN. This paper also discusses some already being studied application fields as well as potential future directions of the WDN applications.

In a spectrum sharing system, lower-priority users are allowed to spatially reuse the spectrum allocated to higher-priority users as long as they do not disrupt communications of the latter. Therefore, to improve spectrum utilization, an important requirement for the former users is to manage the interference and ensure that the latter users can maintain reliable communications. In the present paper, a game theoretic framework of joint channel selection and power allocation for spectrum sharing in distributed cognitive radio networks is proposed. First, a utility function that captures the cooperative behavior to manage the interference and the satisfaction level to improve the throughput of the lower-priority users is defined. Next, based on the defined utility function, the proposed framework can be formulated as a potential game; thus, it is guaranteed to converge to a Nash equilibrium when the best response dynamic is performed. Simulation results show the convergence of the proposed potential game and reveal that performance improvements in terms of network throughput of the lower-priority users and outage probability of the higher-priority users can be achieved by the introduction of an adaptive coefficient adjustment scheme in the proposed utility function at the expense of the convergence to the Nash equilibrium.

Long-distance wireless local area networks (WLANs) are the key enablers of wide-area and low-cost access networks in rural areas. In a WLAN, the long propagation delay between an access point (AP) and stations (STAs) significantly degrades the throughput and creates a throughput imbalance because the delay causes unexpected frame collisions. This paper summarizes the problems caused in the medium access control (MAC) mechanism of the WLAN by a long propagation delay. We propose a MAC protocol for solving the delay-induced throughput degradation and the throughput imbalance between the uplink and the downlink in WLANs to address these problems. In the protocol, the AP extends NAV duration of CTS frame to protect an ACK frame and transmits its data frame to avoid delay induced frame collisions by piggybacking on the ACK frame transmission. We also provide a throughput model for the proposed protocol based on the Bianchi model. A numerical analysis using the proposed throughput model and simulation evaluation demonstrate that the proposed protocol increases the system throughput by 150% compared with that obtained using the conventional method, and the uplink throughput can be increased to the same level as the downlink throughput.

Broadcast services for wireless local area networks (WLANs) are being standardized in the IEEE 802.11 task group bc. Envisaging the upcoming coexistence of broadcast access points (APs) with densely-deployed legacy APs, this paper addresses a learning-based spatial reuse with only partial receiver-awareness. This partial awareness means that the broadcast APs can leverage few acknowledgment frames (ACKs) from recipient stations (STAs). This is in view of the specific concerns of broadcast communications. In broadcast communications for a very large number of STAs, ACK implosions occur unless some STAs are stopped from responding with ACKs. Given this, the main contribution of this paper is to demonstrate the feasibility to improve the robustness of learning-based spatial reuse to hidden interferers only with the partial receiver-awareness while discarding any re-training of broadcast APs. The core idea is to leverage robust adversarial reinforcement learning (RARL), where before a hidden interferer is installed, a broadcast AP learns a rate adaptation policy in a competition with a proxy interferer that provides jamming signals intelligently. Therein, the recipient STAs experience interference and the partial STAs provide a feedback overestimating the effect of interference, allowing the broadcast AP to select a data rate to avoid frame losses in a broad range of recipient STAs. Simulations demonstrate the suppression of the throughput degradation under a sudden installation of a hidden interferer, indicating the feasibility of acquiring robustness to the hidden interferer.

Ternary Content Addressable Memory (TCAM) is a special type of memory used in routers to achieve high-speed packet forwarding and classification. Packet forwarding is done by referring to the rules written in the routing table, whereas packet classification is performed by referring to the rules in the Access Control List (ACL). TCAM uses more transistors than Random Access Memory (RAM), resulting in high power consumption and high production cost. Therefore, it is necessary to reduce the entries written in the TCAM to reduce the transistor count. In this paper, we propose a new TCAM architecture by using Range Matching Devices (RMD) integrated within the TCAM's control logic with an optimized prefix expansion algorithm. The proposed method reduces the number of entries required to express ACL rules, especially when specifying port ranges. With less than 10 RMDs, the total number of lines required to write port ranges in the TCAM can be reduced to approximately 50%.

Decentralized channel assignment schemes are proposed to obtain low system-wide spatial overlap regions in wireless local area networks (WLANs). The important point of channel assignment in WLANs is selecting channels with fewer contending stations rather than mitigating interference power due to its medium access control mechanism. This paper designs two potential game-based channel selection schemes, basically each access point (AP) selects a channel with smaller spatial overlaps with other APs. Owing to the property of potential games, each decentralized channel assignment is guaranteed to converge to a Nash equilibrium. In order that each AP selects a channel with smaller overlaps, two metrics are proposed: general overlap-based scheme yields the largest overlap reduction if a sufficient number of stations (STAs) to detect overlaps are available; whereas decomposed overlap-based scheme need not require such STAs, while the performance would be degraded due to the shadowing effect. In addition, the system-wide overlap area is analytically shown to be upper bounded by the negative potential functions, which derives the condition that local overlap reduction by each AP leads to system-wide overlap reduction. The simulation results confirm that the proposed schemes perform better reductions in the system-wide overlap area compared to the conventional interference power-based scheme under the spatially correlated shadowing effect. The experimental results demonstrate that the channel assignment dynamics converge to stable equilibria even in a real environment, particularly when uncontrollable APs exist.

Differential games are considered an extension of optimal control problems, which are used to formulate centralized control problems in smart grids. Optimal control theory is used to study systems consisting of one agent with one objective, whereas differential games are used to formulate systems consisting of multiple agents with multiple objectives. Therefore, a differential-game-theoretic approach is appropriate for formulating decentralized demand-side energy management systems where there are multiple decision-making entities interacting with each other. Moreover, in many smart grid applications, we need to obtain information for control via communication systems. To formulate the influence of communication availability, differential game theory is also promising because the availability of communication is considered as part of an information structure (i.e., feedback or open-loop) in differential games. The feedback information structure is adopted when information for control can be obtained, whereas the open-loop information structure is applied when the information cannot be obtained because of communication failure. This paper proposes a comprehensive framework for evaluating the performance of demand-side actors in a demand-side management system using each control scheme according to both communication availability and sampling frequency. Numerical analysis shows that the proposed comprehensive framework allows for an analysis of trade-off for decentralized and centralized control schemes.

In this paper, a priority control problem between uplink and downlink flows in IEEE 802.11 wireless LANs is considered. The minimum contention window size (CWmin) has a nonnegative integer value. CWmin control scheme is one of the solutions for priority control to achieve the fairness between links. However, it has the problem that CWmin control scheme cannot achieve precise priority control when the CWmin values become small. As the solution of this problem, this paper proposes a new CWmin control method called a virtual continuous CWmin control (VCCC) scheme. The key concept of this method is that it involves the use of small and large CWmin values probabilistically. The proposed scheme realizes the expected value of CWmin as a nonnegative real number and solves the precise priority control problem. Moreover, we proposed a theoretical analysis model for the proposed VCCC scheme. Computer simulation results show that the proposed scheme improves the throughput performance and achieves fairness between the uplink and the downlink flows in an infrastructure mode of the IEEE 802.11 based wireless LAN. Throughput of the proposed scheme is 31% higher than that of a conventional scheme when the number of wireless stations is 18. The difference between the theoretical analysis results and computer simulation results of the throughput is within 1% when the number of STAs is less than 10.

The present paper focuses on the application of the base station cooperation (BSC) technique in fractional frequency reuse (FFR) networks. Fractional frequency reuse is considered to be a promising scheme for avoiding the inter-cell interference problem in OFDMA cellular systems, such as WiMAX, in which the edge mobile stations (MSs) of adjacent cells use different subchannels for separate transmission. However, the problem of FFR is that the cell edge spectral efficiency (SE) is much lower than that of the cell center. The BSC technique, in which adjacent BSs perform cooperative transmission for one cell edge MS with the same channel, may improve the cell edge SE. However, since more BSs transmit signals for one cell edge MS, the use of BSC can also increase the inter-cell interference, which might degrade the network performance. In this paper, with a focus on this tradeoff, we propose an adaptive BSC scheme in which BSC is only performed for the cell edge MSs that can achieve a significant capacity increase with only a slight increase in inter-cell interference. Moreover, a channel reallocation scheme is proposed in order to further improve the performance of the adaptive BSC scheme. The simulation results reveal that, compared to the conventional FFR scheme, the proposed schemes are effective for improving the performance of FFR networks.