Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.

Spatial stochastic models have been much used for performance analysis of wireless communication networks. This is due to the fact that the performance of wireless networks depends on the spatial configuration of wireless nodes and the irregularity of node locations in a real wireless network can be captured by a spatial point process. Most works on such spatial stochastic models of wireless networks have adopted homogeneous Poisson point processes as the models of wireless node locations. While this adoption makes the models analytically tractable, it assumes that the wireless nodes are located independently of each other and their spatial correlation is ignored. Recently, the authors have proposed to adopt the Ginibre point process — one of the determinantal point processes — as the deployment models of base stations (BSs) in cellular networks. The determinantal point processes constitute a class of repulsive point processes and have been attracting attention due to their mathematically interesting properties and efficient simulation methods. In this tutorial, we provide a brief guide to the Ginibre point process and its variant, α-Ginibre point process, as the models of BS deployments in cellular networks and show some existing results on the performance analysis of cellular network models with α-Ginibre deployed BSs. The authors hope the readers to use such point processes as a tool for analyzing various problems arising in future cellular networks.

The previous researches on the chaotic CDMA have theoretically derived the chaotic sequences having the minimum asynchronous cross-correlation. To minimize the asynchronous cross-correlation, autocorrelation of each sequence have to be C(τ)≈C×r^τ, r=-2+√3, dumped oscillation with increase of the lag τ. There are several methods to generate such sequences, using a chaotic map, using the Lebesgue spectrum filter (LSF) and so on. In this paper, such lowest cross-correlation found in the chaotic CDMA researches is applied to solution search algorithms for combinatorial optimization problems. In combinatorial optimization, effectiveness of the chaotic search has already been clarified. First, an importance of chaos and autocorrelation with dumped oscillation for combinatorial optimization is shown. Next, in order to realize ideal solution search, the LSF is applied to the Hopfield-Tank neural network, the 2-opt method and the 2-exchange method. Effectiveness of the LSF is clarified even for the large problems for the traveling salesman problems and the quadratic assignment problems.

Network intelligence is a discipline that builds on the capabilities of network systems to act intelligently by the usage of network resources for delivering high-quality services in a changing environment. Wide area network intelligence is a class of network intelligence in wide area network which covers the core and the edge of Internet. In this paper, we propose a system based on machine learning for wide area network intelligence. The whole system consists of a core machine for pre-training and many terminal machines to accomplish faster responses. Each machine is one of dual-hemisphere models which are made of left and right hemispheres. The left hemisphere is used to improve latency by terminal response and the right hemisphere is used to improve communication by data generation. In an application on multimedia service, the proposed model is superior to the latest deep feed forward neural network in the data center with respect to the accuracy, latency and communication. Evaluation shows scalable improvement with regard to the number of terminal machines. Evaluation also shows the cost of improvement is longer learning time.

Geocast communication provides efficient group communication services to distribute information to terminals that exist in some geographical domain. For various services which use geocast communication, ad hoc network is useful as network structure. Ad hoc networks are a kind of self-organing network where terminals communicate directly with each other without network infrastructure. For ad hoc networks, terminal power saving is an important issue, because terminals are driven by the battery powered system. One approach for this issue is reducing the radio transmission range of each terminal, but it degrades reachability of user data for each terminal. In this paper, we propose a design method for radio transmission range using the target problem to improve both terminal power saving and reachability for geocast communication in an ad hoc network. Moreover, we evaluate the proposed method considering both routing protocols and media access control protocols, and clarify the applicability of the proposed method to communication protocols.

Due to rapid increases in the number of users and diversity of devices, temporal fluctuation of traffic on information communication network is becoming large and rapid recently. Especially, sudden traffic changes such as flash crowds often cause serious congestion on the network and result in nearly fatal slow down of date-communication speed. In order to keep communication quality high on the network, routing protocols that are scalable and able to quickly respond to rapid, and often unexpected, traffic fluctuation are highly desired. One of the promising approaches is the distributed routing protocol, which works without referring global information of the whole network but requires only limited informatin of it to realize route selection. These approaches include biologically inspired routing protocols based on the Adaptive Response by Attractor Selection model (ARAS), in which routing tables are updated along with only a scalar value reflecting communication quality measured on each router without evaluating communication quality over the whole network. However, the lack of global knowledge of the current status of the network often makes it difficult to respond promptly to traffic changes on the network that occurs at outside of the local scope of the protocol and causes inefficient use of network resources. In order to solve the essential problem of the local scope, we extend ARAS and propose a routing protocol with active and stochastic route exploration. The proposed protocol can obtain current communication quality of the network beyond its local scope and promptly responds to traffic changes occur on the network by utilizing the route exploration. In order to compensate destabilization of routing itself due to the active and stochastic exploration, we also introduce a short-term memory to the dynamics of the proposed attractor selection model. We conform by numerical simulations that the proposed protocol successfully balances rapid exploration with reliable routing owning to the memory term.

This paper presents an analytical model for network throughput of WLANs, taking into account heterogeneous conditions, namely network nodes transmit different length frames with various offered load individually. The airtime concept, which is often used in multi-hop network analyses, is firstly applied for WLAN analysis. The proposed analytical model can cover the situation that there are saturation and non-saturation nodes in the same network simultaneously, which is the first success in the WLAN analyses. This paper shows the network throughput characteristics of four scenarios. Scenario 1 considers the saturation throughputs for the case that one or two length frames are transmitted at the identical offered load. Scenarios 2 and 3 are prepared for investigating the cases that all network nodes transmit different length frames at the identical offered load and identical length frames at the different offered loads, respectively. The heterogeneous conditions for not only frame length but also offered load are investigated in Scenario 4.

In this paper, we give a formalization of the behavior of the Content-Centric Networking (CCN) protocol with parameterizing content managements. CCN is a communications architecture that is based on the names of contents, rather than on addresses. In the protocol used in CCN, each node sends packets to the nodes that are connected to it, which communicate with further nodes that are connected to them. This kind of behaviors prevents formalizing the CCN protocol as end-to-end communications. In our previous work, we formalized the CCN protocol using the proof assistant Coq. However, in this model, each node in the network can store any number of contents. The storage for each node is usually limited and the node may drop some of the contents due to its filled storage. The model proposed in this paper permits a node to have its own content management method, and still keeps the temporal properties that are also valid in the previous model. To demonstrate difference between these models, we give a specification that is valid in the previous model but invalid in the proposed model, called orthogonality. Since it is generally invalid in CCN, the proposed model is more precise than the previous one.

This paper presents a Multi-channel MAC protocol with channel grouping for multi-channel ad-hoc networks. The proposed protocol has both concepts of the multiple rendezvous and the single control channel protocols, which were proposed as a MAC protocol for multi-channel ad-hoc network without centralized stations. In the proposed protocol, all the channels are divided into some groups and each group has a control channel. Network nodes circulate among the groups and channel negotiations are carried out on a control channel of the group. By applying the channel grouping, it is possible to enhance network throughput without reducing the channel-usage probability. Because there is an optimum group number for obtaining the highest throughput, this paper gives analytical expressions of maximum network throughput for the proposed protocol as a function of system parameters. The effectiveness of the proposed protocol is shown from simulation results. In addition, the validity of the analytical expressions is confirmed from quantitative agreements between analytical predictions and simulation results.

This paper proposes a Watts and Strogatz-model based routing method for wireless sensor network along with link-exchange operation. The proposed routing achieves low data-collection delay because of hub-node existence. By applying the link exchanges, node with low remaining battery level can escape from a hub node. Therefore, the proposed routing method achieves the fair battery-power consumptions among sensor nodes. It is possible for the proposed method to prolong the network lifetime with keeping the small-world properties. Simulation results show the effectiveness of the proposed method.

This paper puts forward the concept of cellular network location with less information which can overcome the weaknesses of the cellular location technology in practical applications. After a systematic introduction of less-information location model, this paper presents a location algorithm based on AGA (Adaptive Genetic Algorithm) and an optimized RBF (Radical Basis Function) neural network. The virtues of this algorithm are that it has high location accuracy, reduces the location measurement parameters and effectively enhances the robustness. The simulation results show that under the condition of less information, the optimized location algorithm can effectively solve the fuzzy points in the location model and satisfy the FCC's (Federal Communications Commission) requirements on location accuracy.

Measurement matrix construction is critically important to signal sampling and reconstruction for compressed sensing. From a practical point of view, deterministic construction of the measurement matrix is better than random construction. In this paper, we propose a novel deterministic method to construct a measurement matrix for compressed sensing, CS-FF (compressed sensing-finite field) algorithm. For this proposed algorithm, the constructed measurement matrix is from the finite field Quasi-cyclic Low Density Parity Check (QC-LDPC) code and thus it has quasi-cyclic structure. Furthermore, we construct three groups of measurement matrices. The first group matrices are the proposed matrix and other matrices including deterministic construction matrices and random construction matrices. The other two group matrices are both constructed by our method. We compare the recovery performance of these matrices. Simulation results demonstrate that the recovery performance of our matrix is superior to that of the other matrices. In addition, simulation results show that the compression ratio is an important parameter to analyse and predict the recovery performance of the proposed measurement matrix. Moreover, these matrices have less storage requirement than that of a random one, and they achieve a better trade-off between complexity and performance. Therefore, from practical perspective, the proposed scheme is hardware friendly and easily implemented, and it is suitable to compressed sensing for its quasi-cyclic structure and good recovery performance.

This paper presents a novel control method based on predictions of a neural network in coordination with a conventional PID control to improve transient characteristics of digitally controlled switching dc-dc converters. Power supplies in communication systems require to achieve a superior operation for electronic equipment installed to them. Especially, it is important to improve transient characteristics in any required conditions since they affect to the operation of power supplies. Therefore, dc-dc converters in power supplies need a superior control method which can suppress transient undershoot and overshoot of output voltage. In the presented method, the neural network is trained to predict the output voltage and is adopted to modify the reference value in the PID control to reduce the difference between the output voltage and its desired one in the transient state. The transient characteristics are gradually improved as the training procedure of the neural network is proceeded repetitively. Furthermore, the timing and duration of neural network control are also investigated and devised since the time delay, which is one of the main issue in digital control methods, affects to the improvement of transient characteristics. The repetitive training and duration adjustment of the neural network are performed simultaneously to obtain more improvement of the transient characteristics. From simulated and experimental results, it is confirmed that the presented method realizes superior transient characteristics compared to the conventional PID control.

To efficiently utilize storage resources, the in-network caching system of Information-Centric Networking has to deal with the popularity of huge content chunks which could cause large memory consumption. This paper presents a Popularity Monitoring based Gain-aware caching scheme, called PMG, which is an integrated design of cache placement and popularity monitoring. In PMG, by taking into account both the chunk popularity and the consumption saving of single cache hit, the cache placement process is transformed into a weighted popularity comparison, while the chunks with high cache gain are placed on the node closer to the content consumer. A Bloom Filter based sliding window algorithm, which is self-adaptive to the dynamic request rate, is proposed to capture the chunks with higher caching gain by Inter-Reference Gap (IRG) detection. Analysis shows that PMG can drastically reduce the memory consumption of popularity monitoring, and the simulation results confirm that our scheme can achieve popularity based cache placement and get better performance in terms of bandwidth saving and cache hit ratio when content popularity changes dynamically.

In data center networks, Quantized Congestion Notification (QCN) has been ratified as the standard congestion management mechanism in the link layer. Since QCN nonlinearly switches between the rate increase and decrease stages, it is very difficult to understand QCN in depth and provide theoretical guidelines on setting the buffer size of the QCN switch. This paper gives an explicit formula for the boundary of buffer occupancy of the QCN switch. Specifically, based on the fluid model of QCN, we first derive the uniformly asymptotic stability condition of the QCN system. Then, under the condition that QCN is uniformly asymptotically stable, we analyze the buffer occupancy of the QCN switch theoretically and show that the classic rule-of-thumb for buffer sizing is not suitable for QCN. Finally, simulations validate the accuracy of our theoretical results.

This paper describes an equivalent circuit analysis of a meta-surface using a double-layered patch-type frequency-selective surface (FSS); the analysis considers the coupling between FSSs. Two types of double-layered structures are examined. One is a stacked structure and the other is an alternated structure. The results calculated using the equivalent circuit are in agreement with the results of the FDTD analysis. In addition, it is clarified that the stacked and alternated structures exhibit the common mode and the differential mode coupling, respectively. Moreover, experiments support analysis results for both stacked and alternated structures.

In this paper, a new MIMO antenna for ultra-wide band (UWB) applications is designed and proposed. The proposed MIMO antenna consists of two single UWB antenna elements, one acts as a magnetic dipole while the other as an electric one, to reduce mutual coupling. In order to reduce further the mutual coupling, a copper stub is used to isolate the two antenna elements. The designed MIMO UWB antenna provides a broad operating bandwidth from 3.1GHz to 10.6GHz, while achieving low mutual coupling and VSWR ≤ 2. Various performance characteristics of the antenna such as radiation patterns, VSWR, and the maximal gain are thoroughly investigated by simulations and experiments.

This paper proposes a multiband automatic tunable antenna system for wide frequency bands of 704-2690MHz for cellular wireless communication systems. The proposed system controls variable capacitors connected between the antenna and a transmitter based on the received power of a probe. Locating the probe near the tip of the antenna enables frequency-a operation. The antenna is a multiband two-arm monopole antenna printed on a 60mm × 10mm area of a 60mm × 100mm FR-4 printed circuit board (PCB). The probe is a small dipole antenna capacitively coupled with the antenna. Fine-tuning based on simple hill-climbing optimization compensates the mismatch due to the surroundings, e.g., a user's hand/head or desk assuming channel-informed rough-tuning beforehand. A prototype consisting of varicap diodes and some other devices demonstrates automatic tunability.

Wireless body area networks (BANs) are attracting much attention due to their suitable for healthcare and medical applications. Unfortunately, electrostatic discharge (ESD) is a major electromagnetic (EM) noise source that can degrade wireless communication performance. In this study, we measure EM noise power in the 2.4GHz and 30MHz bands for indirect ESD testing specified in IEC 61000-4-2 standard, and derived a statistical ESD noise model from the measurement results. The ESD noise power was found to follow a lognormal distribution in both 2.4GHz and 30MHz bands. We use this ESD noise model to conduct bit error rate (BER) simulations in a communication channel with additive white Gaussian noise (AWGN) plus ESD noise at 2.4GHz and 30MHz bands. The result is that the BER performance is virtually the same in both bands, and decreases with the signal to noise power ratio (SNR). It is also shown that an error floor exists in the BER performances at both frequencies, which, if the ESD noise power is larger than the Gaussian noise, cannot be improved by increasing the SNR. Although the ESD noise power at 2.4GHz band is nearly 30dB smaller than that at 30MHz band, the signal attenuation along the human body at 2.4GHz band is much larger compared to 30MHz band. This may yield a similar SNR level at 30MHz and 2.4GHz bands in an ESD-dominated environment, so that the 2.4GHz band does not have an obvious merit for BAN applications. Since there are so many in-band interference sources at 2.4GHz band, the 30MHz band seems more promising for vital data transmission in a BAN scenario even in an ESD-dominated environment.

In this work, a novel formulation of crosstalk (XT) is developed, in which the perturbation/loading effect that the generator circuit exerts on the passive part of the receptor circuit is elucidated. Practical conditions (i.e., weak coupling and matching/mismatching of the generator circuit) under which this effect can be neglected are then discussed and exploited to develop an alternative radiated susceptibility (RS) test procedure, which resorts to crosstalk to induce at the terminations of a cable harness the same disturbance that would be induced by an external uniform plane-wave field. The proposed procedure, here developed with reference to typical RS setups foreseen by Standards of the aerospace sector, assures equivalence with field coupling without a priori knowledge and/or specific assumptions on the units connected to the terminations of the cable harness. Accuracy of the proposed scheme of equivalence is assessed by virtual experiments carried out in a full-wave simulation environment.

In a network with dense deployment of multiple-input multiple-output (MIMO) small cells, coverage overlap between the small cells produces intercell-interference, which degrades system capacity. This paper proposes an intercell-interference management (IIM) scheme that aims to maximize system capacity by using both power control for intercell-interference coordination (ICIC) on the transmitter side and interference cancellation (IC) on the receiver side. The power control determines transmit power levels at the base stations (BSs) by employing a neural network (NN) algorithm over the backhaul. To further improve the signal to interference plus noise ratio (SINR), every user terminal (UT) employs a multiuser detector (MUD) as IC. The MUD detects not only the desired signals, but also some interfering signals to be cancelled from received signals. The receiver structure consists of branch metric generators (BMGs) and MUD. BMGs suppress residual interference and noise in the received signals by whitening matched filters (WMFs), and then generate metrices by using the WMFs' outputs and symbol candidates that the MUD provides. On the basis of the metrices, the MUD detects both the selected interfering signals and the desired signals. In addition, the MUD determines which interfering signals are detected by an SINR based replica selection algorithm. Computer simulations demonstrate that the SINR based replica selection algorithm, which is combined with channel encoders and packet interleavers, can significantly improve the system bit error rate (BER) and that combining IC at the receiver with NN power control at the transmitter can considerably increase the system capacity. Furthermore, it is shown that choosing the detected interfering signals by the replica selection algorithm can obtain system capacity with comparable loss and less computational complexity compared to the conventional greedy algorithm.

In IEEE 802.11 wireless local area networks (WLANs), contention window (CW) in carrier sense multiple access with collision avoidance (CSMA/CA) is one of the most important techniques determining throughput performance. In this paper, we propose a novel CW control scheme to achieve high transmission efficiency in dense user environments. Whereas the standard CSMA/CA mechanism. Employs an adaptive CW control scheme that responds to the number of retransmissions, the proposed scheme uses the optimum CW size, which is shown to be a function of the number of terminal stations. In the proposed scheme, the number of terminal stations are estimated from the probability of packet collision measured at an access point (AP). The optimum CW size is then derived from a theoretical analysis based on a Markov chain model. We evaluate the performance of the proposed scheme with simulation experiments and show that it significantly improves the throughput performance.

In this paper, we propose and analyze the opportunistic amplify-and-forward (AF) relaying scheme using antenna selection in conjunction with different adaptive transmission techniques over Rayleigh fading channels. In this scheme, the best antenna of a source and the best relay are selected for communication between the source and destination. Closed-form expressions for the outage probability and average symbol error rate (SER) are derived to confirm that increasing the number of antennas is the best option as compared with increasing the number of relays. We also obtain closed-form expressions for the average channel capacity under three different adaptive transmission techniques: 1) optimal power and rate adaptation; 2) constant power with optimal rate adaptation; and 3) channel inversion with a fixed rate. The channel capacity performance of the considered adaptive transmission techniques is evaluated and compared with a different number of relays and various antennas configurations for each adaptive technique. Our derived analytical results are verified through extensive Monte Carlo simulations.

When using a wireless capsule endoscope (WCE), it is important to know WCE location. In this paper, we focus on a time of arrival (TOA)-based localization technique, as it has better location estimation performance than other radio frequency-based techniques. However, the propagation speed of signals transmitted from inside of a human body varies depending on which biological tissues they pass through. For this reason, almost all of conventional TOA-based methods have to obtain the relative permittivity of the passed biological tissues or the propagation speed beforehand through another measurement system, i.e., magnetic resonance imaging (MRI) or computational tomography (CT). To avoid such troublesome pre-measurement, we propose a hybrid TOA/received signal strength indicator (RSSI)-based method, which can simultaneously estimate the WCE location and the averaged relative permittivity of the human body. First, we derive the principle of RSSI-based relative permittivity estimation from an finite difference time domain (FDTD) simulation. Second, we combine the TOA-based localization and the proposed RSSI-based relative permittivity estimation, and add them to the particle filter tracking technique. Finally, we perform computer simulations to evaluate the estimation accuracy of the proposed method. The simulation results show that the proposed method can accomplish good localization performance, 1.3mm, without pre-measurement of the human body structure information.

Rain attenuation can drastically impact the service availability of satellite communication, especially in the higher frequency bands above 20 GHz, such as the Ka-band. Several countermeasures, including site and time diversity, have been proposed to maintain satellite link service. In this paper, we evaluate the performance of a power boost beam method, which is an adaptive satellite power control technology based on using rain radar data obtained throughout Japan to forecast the power margin. Boost beam analysis is considered for different beam sizes (50, 100, 150, and 200km) and beam numbers (1-4 beams) for a total of 16 cases. Moreover, we used a constant boost power corresponding to the rainfall rate of 20mm/h. The obtained results show that in comparison to the case with no boost, the effective rain intensity in each boost case was reduced.

This paper proposes a technique for efficient standing multipath mitigation of geostationary earth orbit (GEO) satellites. The performance of traditional filtering methods for GEO multipath errors can be effectively improved by using carrier frequency variation approach. Conventional multipath mitigation methods do not pay much attention to the GEO satellite multipath effects, and they are less effective due to the non-zero average characteristics of GEO multipath errors for short epochs. By varying carrier frequency, the multipath error average becomes approaching zero in short epochs due to the faster multipath carrier phase variation. Therefore, it could enhance the traditional filtering method performance on the multipath signals. By varying the carrier frequency or the carrier phase offset, the average multipath error will approach zero as a result of the frequent multipath carrier phase variations. This method aims to explore the potential for signal pattern design while improving the performance of current satellite navigation systems. The results show that the root mean square error (RMSE) for pseudo-range multipath errors of the proposed approach improves about 0.3m with a frequency variation range of 15MHz.