In Japan’s private 5G, identical channels are often reused by different licensees, so adjacent cells are prone to mutual interference. The common remedy, large separation based on siteagnostic models, suppresses spatial reuse and wastes spectrum. We propose a lightweight estimator that fuses simple propagation with 3D city-model data to explicitly account for blockage at low cost. The method classifies LOS/NLOS from building footprints and heights, applies a two-ray/FSPL blend in LOS, and adds knife-edge diffraction plus proximity reflection in NLOS. Across outdoor trials, it reduces the measured-over-estimate ratio (OVRT) while keeping RMSE/MAE/STD comparable to conventional models, indicating safer coordination with smaller guard margins.

For the application of wireless networks to unmanned aerial vehicles, which are expected to be utilized in next-generation mobile communications, it is essential to have a precise understanding of the radio environment in order to ensure highly reliable communication connections. In this study, we expand the radio environment maps, traditionally used for understanding wireless environments, into 3D space. To achieve this, we performed kriging-based interpolation of observed values using line-of-sight judgment from 3D maps. We then evaluated and validated the accuracy and effectiveness of this method.

Low-power wide area networks (LPWANs) are wireless communication systems that enable long-distance communication with low power consumption, and have attracted attention as a wireless infrastructure for Internet of Things (IoT) systems. However, the long-distance nature of LPWANs can cause the hidden node problem, which results in a lower packet delivery ratio (PDR). To address the hidden node problem, this paper proposes a channel assignment method. First, we derive an approximate formula for PDR under the impact of hidden nodes, and then propose an optimal channel assignment method based on simulated annealing, using the derived formula. Simulation results confirm that the proposed method can mitigate the degradation of PDR and increase the capacity of LPWAN networks.

This study investigates hidden and exposed nodes in a low power wide area network (LPWAN) with the energy detection based carrier sense. Energy detection based carrier sense can drastically improve the performance of LPWANs, which is a type of wireless local network. However, hidden node problems are inherent in wireless local networks with carrier sense, and the upsurge of LPWANs with carrier sense results in exposed node problems. To evaluate the hidden and exposed nodes in the LPWAN, we define evaluation model that includes Own LPWAN and Interference LPWAN. Based on the model, hidden and exposed nodes in the LPWAN are evaluated for different distance between both LPWANs and different path loss exponent between end devices and gateway. The evaluation results show that exposed nodes are not expected to occur in the LPWAN when the gateway is located at the appropriate location where many of the end devices are located in the line-of-sight environment.

This study investigates a scheme for the performance improvement of Sub-GHz band low power wide area networks (LPWANs) using an energy detection based carrier sense. The energy detection based carrier sense in the LPWAN has been theoretically analyzed. Although the carrier sense can improve several characteristics of the end devices, the energy consumption of the carrier sense is almost the same as that of the signal reception and cannot be ignored. In addition, the energy detection based carrier sense requires a long carrier sense period compared with the peak detection based carrier sense, which may further increase the energy consumption. Therefore, the performance improvement and energy consumption at the end devices must be jointly considered. Under these considerations, we propose an execution scheme of the energy detection based carrier sense at the end devices to improve the performance of poor conditioned end devices, that is, a large propagation loss to the gateway.

Smart factories operating autonomously through a cyber-physical system (CPS) need to recognize the location-dependent wireless environment accurately for highly reliable communications and highly accurate information aggregation from automated guided vehicle and sensors. Recognizing the wireless environment is also essential for designing wireless power transfer to sensors simultaneously with data transmission. One of the methods for recognizing the wireless environment is a radio environment map (REM), which visualizes the statistical results of measured received power and communication quality by linking them to location information. This method requires node’s location information that is difficult to accurately locate indoors in a practical environment. In this paper, we propose a method to construct a REM with nodes whose locations are estimated by using a position estimation method. Measurement nodes recognize the wireless environment while autonomously estimating their position. We measured the received power of private 5G, a type of private network, in a smart factory and constructed a REM using a position estimation method based on bluetooth low energy beacons. Using the proposed method, a radio propagation environment could be inferred with an accuracy of about $5[\mathrm{~dB}]$ in root mean squared error (RMSE).

This paper proposes a novel model for radio propagation graph representation learning in multi-hop path representation. A concept of radio propagation graph representation learning has been proposed to express the radio propagation process using graph data structure, thereby improving the prediction accuracy with small computation time. In the existing work, a direct path representation model based on feedforward neural network (FFNN) has been proposed; however, it achieves poor prediction accuracy at points far from a transmitter due to the lack of consideration of reflection, i.e., multi-hop path. Therefore, this paper proposes a novel learning method to apply the existing concept to multi-hop path cases. Through the performance evaluation using Long Term Evolution signal data in a 2120 MHz band measured in an urban area, we demonstrate that the proposed model outperforms the existing representation model in terms of prediction accuracy and achieves shorter computation time compared with the ray tracing application.

The evolution of sensor networks is indispensable in modern society, with environmental sensing technologies playing a critical role. Packet communication, commonly used in many systems, is not suited for efficient transmission of environmental information due to the excessive data volume of headers. This paper focuses on the physical wireless parameter conversion sensor networks (PhyC-SN), examining how this innovative approach addresses the issues of packet communication and significantly reduces energy consumption. PhyC-SN allows for simultaneous environmental recognition through the frequency distribution of received signals by switching the carrier frequencies according to sensor information. However, PhyC-SN cannot generate heatmaps that depict the spatial distribution of sensor information. Thus, this study proposes a new method that combines Mobile Data Gathering Stations (MDGS) with PhyC-SN to enable the generation of heatmaps. By leveraging dynamic position control of MDGS and aggregation of sensor data, this combination allows for precise environmental recognition linked with sensor location information. This integration facilitates the construction of an energy-efficient sensor network, offering a sustainable technology solution.

This paper proposes a multi-hop communications system that utilizes digital beamforming to efficiently collect data packets from sensor nodes (SNs) via the intermittent receiver-driven data transmission (IRDT) protocol. By leveraging beamforming, this system enables more SNs to directly communicate with a concentrator, increasing the number of idle SNs in the network available as potential receivers and thus preventing the data packet convergence on specific SNs. Furthermore, the resulting non-concentrated distribution of data packets allows beamforming to effectively limit the number of SNs with data packets, significantly reducing the probability of packet collisions. Simulation results demonstrate that our proposed system significantly improves the packet delivery ratio.

Low Power Wide Area Networks (LPWANs), including Long-Range Wide Area Network (LoRaWAN), that enable long-distance communication with low-power consumption have been attracting attention along with the development of the Internet-of-Things (IoT). Carrier Sensing (CS) is mandated before packet transmission in some regions and countries. However, the hidden node problem becomes more serious as the communication area becomes larger. Packet-Level Index Modulation (PLIM) assigns indexes to the frequency channel and time slot of packet transmission to increase throughput. This paper proposes a PLIM-based method to enable the GateWay (GW) to obtain the sensing relationships among nodes without explicit signaling. The obtained information can be used for node clustering and resource allocation to alleviate the hidden terminal problem. Computer simulation results show that the proposed method improves Packet Delivery Rate (PDR) by up to 13% compared to the conventional method using PLIM. And can achieve a similar PDR performance as the situation where the inter-node distance is ideally known.

Low-power wide area networks (LPWANs), such as long-range wide area networks, are increasingly adopted as a communication standard for wireless sensor networks. LPWAN has been adopted for systems that periodically collect data from sensors, such as in environmental monitoring. However, continuous packet collisions may occur in periodic traffic systems owing to the adoption of a simple random-access scheme in LPWAN. In addition, the use of low-cost nodes results in clock drift, rendering the synchronization of nodes in the system challenging. Thus, this study proposes a wireless resource allocation scheme to avoid continuous packet collisions under the adverse effect of such clock drift. In the proposed scheme, the gateway determines the transmission offset and frequency channel for each node utilizing the periodic traffic feature and clock drift. Based on computer simulation results, the proposed scheme can improve the packet delivery rate by over 20% compared with benchmark methods.

In recent years, long-range wide-area network (LoRaWAN) has attracted considerable attention due to its ability to realize massive machine-type communication (MTC); however, its throughput is limited by the duty cycle (DC). Packet-level index modulation (PLIM) can increase throughput by utilizing a data packet’s frequency channel and transmission timing as the information-bearing index. In PLIM, a node selects a specific transmission resource (frequency channel and timing) within a frame and transmits a packet. If the node cannot transmit the packet at the specific transmission resource, it discards the packet. This packet discard results in throughput degradation of each node. Thus, this paper proposes an index mapping scheme that divides a frame into multiple subframes to provide each node with multiple transmission opportunities. A node performs channel activity detection (CAD) at the selected transmission resource within a subframe; if the node cannot transmit a packet, it moves to the next subframe. The proposed scheme adaptively maps the information bit sequence onto a transmission resource within each subframe based on the wireless environment and communication quality. Computer simulation results show that the proposed scheme improves throughput by increasing the transmission opportunities and reducing the packet discard rate under the constraint of DC.

This paper investigates an efficient system for collecting packets from a large number of sensor nodes (SNs) using the intermittent receiver-driven data transmission (IRDT) protocol. In our proposed system, we deploy a packet aggregation station such as gateway (GW) equipped with digital beamforming, which employs beam sweeping during downlink beacon transmission to mitigate collisions of send request (SREQ) packets from SNs. Furthermore, we utilize multiple digital reception beams in parallel, allowing for the simultaneous decoding of multiple packets in uplink transmission and thereby improving the packet delivery ratio (PDR). Numerical results validate the effectiveness of our proposal.

With the fast growth of Internet-of-things (IoT) and machine-to-machine (M2M) communications technology, low- power wide area networks (LPWAN) such as long-range wide area network (LoRaWAN) are attracting attention. One of the main applications of LPWAN is information collected from a large number of sensor nodes, where network traffic is generally dominated by periodic uplink (UL) traffic. In LPWAN, each sensor node transmits packets at arbitrary timing, which causes packet collisions and degrades the system communication quality. Especially in the case of periodic UL, continuous packet collisions may occur. Therefore, this paper proposes a centralized radio resource allocation scheme that avoids packet collisions of periodic traffic in LPWANs, taking into account the characteristics of the periodical traffic. The computer simulation results show that the proposed scheme can improve the average packet delivery ratio (PDR) by 18% and the age-of-information (AoI) performance compared to the ALOHA protocol.

This paper proposes a novel graph-learning-based radio propagation model, referred to as propagation graph representation learning. Recent advancements in deep learning have succeeded in developing site-specific path loss prediction; however, predicting shadowing without on-site measurement data is still a critical challenge. Propagation graph representation learning aims to express the site-specific propagation process. In the envisioned graph, nodes represent a transmitter, receivers, and obstructions, while edges represent propagation conditions between nodes. The graph structure enables us to recognize the reflection, diffraction, and shielding for accurate shadowing estimation. We also propose a feedforward neural network (FFNN) based representation model in a direct path scenario. Through the simulation using actual datasets in urban areas, we demonstrate that the proposal achieves twenty times faster computation than ray tracing while predicting shadowing well.

Radio Environment Map (REM) is used to enhance the communication efficiency in spatial spectrum sharing. Using the information from terminals’ reports is one of the methods to generate the REM. The open environment always leads the security problems. High accuracy of terminals’ reports is an essential problem in REM construction. Reinforcement Learning (RL) can estimate and predict the channel condition in a short time, and Multi-armed Bandit (MAB) is a good way to maximize the expected gain by allocating the choices. In this paper, we proposed an algorithm named Terminal Selection Based on MAB (TS-MAB), aim to select a group of reliable terminals to predict the channel condition. For our knowledge, this is the first time using MAB to deal with threatening environment. Simulation results show our method has a good convergence speed with a high accuracy. As long as the percentage of malicious data is less than half of the total data, the algorithm can give a good solution to do the terminal selection and have a high precision prediction of channel conditions.

Radio Environment Map (REM) is used to enhance the communication efficiency in spatial spectrum sharing. REM indicates the received signal strength at each location by measurements data from each terminal or estimated data by the database. Crowdsourcing-based spectrum sensing is a promising approach for generating the REM for a large communication area. However, the open environment also leads the security problems, which can damage the REM accuracy by some malicious activities. The accuracy of terminals’ reports became an essential problem need to be considered in REM construction system. In this paper, we introduce a Kriging-based Trust Nodes aided REM construction (KTNA-REM) system to achieve a high accuracy under the threatening environment. By adding the support of a small amount of the trust nodes, the database can evaluate the reputation of the terminals continuously and generate the REM based on the high reliable data even when the amount of the malicious terminals is big. Simulation results confirm the efficiency and accuracy of the proposed method.

This paper proposes a novel method for deriving the average blockage duration based on time-series prediction of future pedestrians using people flow data toward reliable millimeter-wave communications. The issue is to stably predict pedestrian conditions, which are the main cause of the blockage, in a realistic environment. Therefore, we utilize time-series data on people flow in an area, to predict the future state of pedestrians. The average walking speed in the area is calculated by giving the predicted values of traffic flow to pedestrian models. Furthermore, we define the occurrence of blockage as the existence of a pedestrian in the first Fresnel zone, and based on the above information, we calculate the estimated value of the time-series data of the average blockage duration in the area. In this paper, we evaluate the method via human blockage experimental measurements and computer simulations.

Low-power wide-area network (LPWAN), which includes the long-range wide-area network (LoRaWAN) protocol, is an enabling technology that satisfy low power consumption and long-range communication. In many applications of LPWAN, an end node (EN) transmits data at regular intervals. Based on this, we had previously proposed the concept of packet-level index modulation (PLIM) to increase the number of information bits transmitted by one data packet. In PLIM, the generation interval between two consecutive packets is split into multiple time slots. Each EN transmits its packet in a specific combination of time slot and frequency channel, which represents the index, to convey additional information bits. To retrieve additional information, the gateway (GW) detects the time slot in which the data packet is being transmitted. Therefore, accurate synchronization between EN and GW is essential. However, clock drift occurs due to the inexpensive real-time clock oscillator on each EN, which results in timing misalignment between each node and the GW. This article proposes a simple clock drift estimation and compensation method for the PLIM. An experimental measurement is performed to model the clock drift. The numerical results obtained using the clock drift model show that it can accurately detect the time slot index under the influence of clock drift. Furthermore, PLIM is implemented on a commercial LoRaWAN node and GW to demonstrate its practicability.

Radio Environment Map (REM) is used to enhance the communication efficiency in spatial spectrum sharing. Using the information from terminals' reports is one of the method to generate the REM. The open environment always lead the security problems. High accuracy of terminals' reports is an essential problem in REM construction. In this paper, we consider when malicious terminals are existed and doing data falsification attack, in which they usually rewrite the received signal power and report the malicious datasets to database and try to lead a wrong REM. We propose a double layer monitor method to deal with this kind of attack and the simulation results show our proposed method can remove the influence of the reported data from malicious terminals.

In low power wide area network (LPWAN), intra-system and inter-system interferences have become crucial issues due to a huge number of terminals and the use of the same frequency channels among LPWAN systems. Thus, we propose a channel allocation method for one of the LPWAN systems, long range wide area network (LoRaWAN), according to the radio environment to suppress these interferences. First, a LoRa gateway (GW) estimates an empirical cumulative distribution function (ECD F) of inter-system interference signal power in each frequency channel. Based on the obtained ECDF, the GW allocates LoRa nodes to the frequency channels in ascending order of the inter-system interference time ratio. Then, the GW reallocates the LoRa nodes to the frequency channels by a search algorithm based on a formula of intra-system interference probability so that this probability on each channel becomes lower than a threshold while maintaining the intersystem interference suppression. The simulation results show that our proposed method can suppress packet losses compared to the conventional random channel selection.

Long range wide area network (LoRaWAN) enables low-power and long-range communication suitable for wireless sensor networks (WSNs). Since LoRaWAN is a decentralized network, packet collision may occur if multiple nodes send data packets simultaneously. It is necessary to adjust the node's transmission interval properly to avoid such packet collisions. This paper proposes a transmission interval control strategy that takes advantage of an acknowledgment (ACK) signal from a gateway (GW) to each node. Instead of transmitting a controlling signal, the GW selects one of two receiving windows for ACK packet transmission to indicate 0 or 1. Thus, it does not incur any overhead. The proposed method adaptively changes the transmission interval of each LoRaWAN node by utilizing the ACK signal returned from the GW. The proposed method uses a simple prediction method that is computationally simple and can provide good properties even when there are constraints on the systems associated with observing gentle changes, such as environmental monitoring. Computer simulation results show that the proposed method can reduce the number of transmitted packets while achieving the same observation accuracy level as conventional methods.

Memory nonlinearity is an important issue in the transceivers of broadband wireless communications such as 5G. In this paper, we analyze the memory effects on nonlinear distortion by using three basic models with different frequency characteristics. Next, we propose a new post-reception nonlinear compensation scheme that consists of a memoryless blind nonlinear compensator (BNLC) and linear equalizers connected in series. Performance of the proposed compensators are validated by computer simulations as the improvement of EVM. The simulated performance is better than conventional approach employing a memory polynomial while the proposed scheme needs a smaller number of model parameters.

To reduce the registered data size and maintain the estimation accuracy of a radio map, we have proposed a shadowing classifier-based radio map. On the other hand, the radio map has been widely utilized in various systems, such as a spatial spectrum sharing, spectrum sensing, and localization. Thus, it is necessary to clarify the appropriate classification method of the shadowing components in various environments. In this paper, we evaluate the accuracy of the shadowing classification using two kinds of datasets and two comparison methods. The emulation results show that it is necessary to appropriately choose the classification method according to the presence or absence of outliers of the average received signal power.

This paper describes interference management utilizing spectrum database and beamforming in micro operator based cellular system. For administrating wireless system consisting of small cells operated by micro operators, interference mitigation has an important role for realizing realiable broadband communication under efficient resource allocation. Spectrum database which stores various information inside of meshes (rectangular small segments which cover entire commu- nicaiton area) is a quite effective tool, and this paper shows how to use data of received signal power for cotroling outage signal to interference plus noise ratio (SINR) in target meshes. Computer simulation shows the effectiveness of the proposed approach, and high potential of spectrum database in the context of micro operator based cellular system.

Collaborative Spectrum Sensing (CSS) is considered as a powerful way to improve the utilization of the spectrum resources. However, the open characteristic of Cognitive Radio Sensor Networks (CRSNs) suffer various security threats, such as Spectrum Sensing Data Falsification (SSDF) attack, the defending of this kind of attack is a popular research topic in both academia and industry due to the demanding requirements of security. To enhance the performance of sensing, the schemes based on the Dempster-Shafer (D-S) Evidence Theory have been proposed. However, if we consider that the transmitted data will be increased with the sensing nodes increasing, the energy consumption of the whole networks should be reduced. In order to reduce the total energy consumption, Sensor Selection is one efficiency way to deal with the energy limitation. In this paper, we calculate the formulas of false alarm probability and miss detection probability under the D-S Evidence Theory and propose a new algorithm to find the minimum number of sensing nodes and the optimal threshold with the given security level based on D-S Evidence Theory to against SSDF attack.

Private/local wireless networks based on LoRa with Internet of Things (IoT) devices has been paid much attention. Important issues of the LoRa based network are non-line-of-sight (NLOS) environment and inappropriate of LoRa gateway. This paper studies propagation characteristics for LoRa communications operated at 920MHz band in a harsh environment, which is assumed that i) numerous NLOS environment in the communication area and ii) high buildings surrounding the LoRa gateway. For the evaluation of the propagation characteristic in the harsh environment, we measure averaged received signal strength indicator (RSSI) values in a university campus. Based on the measurement results, we obtain the outage probability and the path loss model. These results indicate that the harsh environment causes the reduction of the communication area, i.e., the path loss model which is obtained from the measurement data almost follows COST-231 Walfisch- Ikegami model.

In this paper, we propose a measurement-based spectrum database using model classifier. In the radio propagation, path loss is the fundamental factor to recognize the coverage area. However, it is difficult to accurately estimate the radio environment only path loss estimation because of the shadowing deviation. Therefore, we estimate the propagation model including shadowing, and by determining the usage range of the estimated model, we reduce the registered data size while accurately estimating the radio environment. The database firstly accumulates the received signal strength indicator (RSSI) related to the locations of receivers and we construct the model classifier. Then, the database assigns the propagation model in each mesh so that Root Mean Squared Error (RMSE) between datasets and the models is minimized. We used measurement datasets of a 3GPP cellular band in the real environment to construct the model classifier. Our results show that the proposed method can accurately estimate the radio propagation while the registered data size is significantly reduced. Additionally, we discuss a method of power control based on the proposed method for improving the communication efficiency.

Maximum cyclic autocorrelation selection (MCAS)-based spectrum sensing is one of the low complexity spectrum sensing techniques in cyclostationary detection techniques. However, spectrum sensing features of MCAS- based spectrum sensing have never been theoretically derived. This paper provides a derivation result of spectrum sensing characteristics for MCAS-based spectrum sensing in cognitive radio networks. In this study, we derive closed form solutions for signal detection probability and false alarm probability for MCAS-based spectrum sensing. The theoretical values are compared with numerical examples, and the examples demonstrate that numerical and theoretical values match well with each other.

In this paper, we propose a spectrum database for storing received signal power distribution using clustering for reducing the types of registered distribution. In order to estimate radio environment, a measurement-based spectrum database (MSD) is considered and the distribution of the received signal is important for keeping the outage probability of the system performance. However, if we consider the database stores all of the distributions corresponding to each location, the amount of stored data becomes very large. In order to construct a practical database, the amount of stored data should be reduced while the highly estimation accuracy is maintained. Therefore, in this paper, the database firstly estimates the received signal power distribution in each location. Then, the similar distributions are integrated by clustering so the amount of stored data can be reduced. We evaluated the accuracy of the clustering and showed that similar distributions can be accurately clustered. In addition. we performed the transmit power control (TPC) by using the clustered distributions. The results showed that the permissible outage probability can be guaranteed while the amount of stored data can be drastically reduced.

In this paper, an ensemble learning (EL) framework is adopted for cooperative spectrum sensing (CSS) in an orthogonal frequency division multiplex (OFD-M) signal based cognitive radio system. Each secondary user (SU) is accordingly considered as a base learner, where the local spectrum sensing is for investigating the probability of PU being inactive or active. The convolution neural networks with simple architecture are applied given its strength in image recognition as well as the limited computation ability of each SU, meanwhile, the cyclic spectral correlation feature is introduced as the input data. Here, as for the supervised learning, the bagging strategy is helped to establish the training database. For the global decision, the fusion center employs the stacked generalization for further combination learning the SU output of the probability predictions of the PU status. Our method shows significant advantages over conventional CSS methods in term of the detection probability or false alarm probability performance.

In this paper, we propose a method to estimate the communication parameters and the number of Primary Users (PUs) by using Hidden Markov Model (HMM) from time series data such as received power in the environment. Many researchers focus on a measurement based Radio Environment Database (RED) that utilizes the actual received signal power obtained by spectrum sensing as an enabler for an efficient frequency sharing. In addition, by estimating average received power and channel occupancy, etc. from radio observation information obtained by spectrum sensing, it is possible to realize high precision RED construction. Conventional research on parameter estimation using machine learning for a system like wireless LAN assumes that the number of PUs existing in the sensing environment is known. This assumption is not realistic in an actual environment. In this research, we estimate the number of PUs and parameters of each PU by using HMM and the Bayesian Information Criterion (BIC) for spectrum sensing when the number of PUs existing in the sensing environment is unknown. Thereby, the parameters related to the each PU in the sensing environment can be separated and stored in RED. Moreover, when estimating by using HMM and BIC, we improve the estimation result of the number of PUs by using the threshold for the estimation result of the transition probability matrix which is the parameter of HMM. The simulation results confirm that the number of PUs can be estimated with high precision when targeting wireless LAN.

A low power wide area network (LPWAN) is one of the promising technologies intended for Internet of Things (IoT). The LPWAN features a wide communication area that is a few kilometers to a few tens of kilometers; low power consumption is achieved using a battery. This study measures the transmission characteristics of a LoRaWAN which is one of the LPWAN. Therefore this paper shows the measured results in field experiment of certain cases: a road along the Tamagawa river in Tokyo, inside and around campuses, and a medium city environment. These measured results indicate that it is difficult to accurately perform a carrier sensing for LoRaWAN. Subsequently, we propose a method to realize the accurate spectrum sensing for spectrum sharing considering sensing sensitivity.

In the physical wireless parameter conversion sensor network (PhyC-SN), the sensor controls the frequency of carrier according to the sensing result and all the nodes inform the sensing results to the fusion center, simultaneously. The dynamic range of sensing result which node sends to FC depends on the available channels of frequency spectrum. In spectrum sharing to the other system (primary system), PhyC-SN (secondary system) considers the assignment between the quantization level of digital sensing result and the channel of frequency spectrum. In this paper, for constructing this assignment, the fusion center collects two types of tendencies. First one is the sensing results. The mean and variance value of sensing results can be estimated by data tracking technique. Second one is a channel occupancy rate (COR). From COR, the fusion center predicts the probability of finding non-occupied channel. The fusion center can construct the assignment map based on minimum mean square error between the predicted sensing result and the exact one. As a result, the constructed assignment achieves the high spectrum usage efficiency.

This paper proposes a primary user detection method in cognitive radio system based on the features of cyclic spectral correlation and the stacked denoising autoencoder. The cyclic spectral correlation, which is sensitive to OFDM signal, is utilized as the feature-extraction tool. Then, we use the SDAE as a classifier due to its high classification accuracy. Concretely, we suppose that OFDM is applied by PU because OFDM is more commonly used than other single carrier modulations. Therefore, our mission turns to the classification of OFDM signal. In addition, a long symbols sequence is not required for this method simplifying the detection procedure and rendering rapid detection more achievable. The results of the probability of successful detection, the change in the probability of successful detection corresponding to different corruption levels are presented, demonstrating significant performance advantages over energy detection.

In a received signal strength indicator (RSSI)-based path loss estimation where mobile terminals report the decoding results from the received packets, the reported results are strongly affected by the receiver noise. Because low power instantaneous signals cannot be obtained due to the decoding failure, a path loss estimation considering no effects of the receiver noise underestimates the path loss models. In this paper, we propose a low complexity compensation method for improving the bias of the path loss estimation. The proposed method first estimates the true mean received signal power in each measurement area via a simple filtering for the reported signals. We show that the proposed method can mitigate the effect of the noise.

Recently, some papers that apply a multi-armed bandit algorithm for channel selection in a cognitive radio system have been reported. In those papers, channel selection based on Upper Confidence Bound (UCB) algorithm has been proposed. However, in those selection, secondary users are not allowed to transmit data over same channels at the same time. Moreover, they do not take security of wireless communication into account. In this paper, we propose secure channel selection methods based on UCB algorithm, taking secrecy capacity into account. In our model, secondary users can share same channel by using transmit time control or transmit power control. Our proposed methods lead to be secure against an eavesdropper compared to conventional channel selections based on only estimated channel availability. By computer simulation, we evaluate average system secrecy capacity. As a result, we show that our proposed channel selections improve average system secrecy capacity compared to conventional channel selection.

In order to realize reliable Vehicular-to-Vehicular (V2V) communication systems, the recognition of radio propagation becomes an important basic technology. However, in the current wireless distributed network systems, it is difficult to accurately estimate the radio propagation characteristics because of the locality of the radio propagation due to surrounding buildings geographical features. In this paper, we construct a measurement-based radio environment database for V2V communication systems. The database first accumulates the received signal strength indicator (RSSI) related to the transmission/reception locations from V2V systems. By using the datasets, the average received power maps linked with transmitter and receiver locations are generated. We have performed measurement campaigns of V2V communications in the real environment to observe Received Signal Strength Indicator (RSSI) for the database construction. Our results show that the proposed method has higher accuracy of the radio propagation estimation than the conventional path loss model based estimation.

Dynamic spectrum access of cognitive radio exploits the low active channel and thus achieves the high frequency spectrum usage efficiency. Since it has freedom for access channel, the access channel of a node is different from that of the other one. It is an access channel mismatch. For compensating it, the exchanging of control signal between two nodes is required but the large delay and the low spectrum efficiency are serious problem. This paper proposes novel control signal and novel receiver for compensating access channel mismatch. In the receiver, we use nonlinear amplifier and thus the wide spread spectrum of distorted control signal can be detected even under the access channel mismatch. We use an interleaved frequency division multiple access (IFDMA) modulation scheme as control signal. IFDMA modulation has robustness to nonlinear distortion. Therefore, the peculiar feature of IFDMA modulation is used as identifying the control signal from detecting the spectrum of distorted IFDMA signal. The computer simulation shows that the highly accurate detection of control signal is achieved under the access channel mismatch and it is possible to inform the access channel number to the other node.

In this demonstration, we introduce a demonstration system of highly efficient environment aware wireless sensor network by considering characteristics of sensing information and spectrum efficiency. In this network, a suitable sensor system is selected from multiple wireless sensor systems by considering the demand of each sensor and surrounding wireless environment. In our demonstration system, we prepare 2.4GHz ZigBee, 920MHz small power wireless system and 460MHz wireless sensor network converting the sensing information to frequency called physical wireless parameter conversion sensor network (PHY-C SN). In order to understand the surrounding wireless environment, we also prepare a radio environment database based on the measurement data of each sensor. In CCNC 2016, we plan to introduce a video of the field test with more than 20 sensor nodes and to exhibit a small demonstration system based on multiple wireless sensor devices and USRPs.

This paper studies a decentralized power allocation for uplink random access of secondary users in cognitive network with successive interference cancellation. First, for the additive white Gaussian noise channel, we propose a novel algorithm, which enables to obtain discrete power levels and optimize the corresponding probabilities, iterating per-level from the lowest power level to the highest one. Under a fading environment, we further propose an opportunistic transmission protocol to reduce the interference temperature at the primary base station, by allocating powers only to the secondary users who will result in small interference. The proposed algorithms are verified via computer simulations.

The concern over wireless distributed networks (WDNs) such as Machine-to-Machine (M2M) systems and Internet of Things (IoT) has risen. In massive WDNs, it is important to strictly manage the interference power among wireless links: radio propagation prediction between distributed terminals is a critical issue for highly efficient spectrum use. In this paper, we propose a novel radio propagation estimation using spectrum database which collects communication results from mobile terminals. The proposed method focuses on the spatial-correlation of radio propagation characteristics between different wireless links. Using maximum likelihood-based pathloss estimation and Kriging-based shadowing estimation, the radio propagation of the wireless link that has arbitrary location relationship can be predicted. From numerical results, it is shown that the proposed method achieves higher estimation accuracy than the conventional pathloss-based estimation methods. Furthermore, we show that the proposed technique can predict the probability density function (PDF) of the estimation error.

A cognitive radio system coexisting with various systems must perform a spectrum sensing for finding a white space (WS). In this paper, we propose a new two-stage spectrum sensing method using an energy detection (ED) based on fast Fourier transform (FFT). In the case that an unknown signal is present the FFT band, false signals are detected in the surrounding FFT bins of the received signal due to a spectral leakage. Whereas a windowed FFT is well known as the solution of the spectral leakage, the spectrum spread to out of the original signal frequency is detected. The shape of the spectrum depends on the kinds of the window function. Therefore we improve the detection performance of ED by employing the property of the windowing in the second stage of the proposed spectrum sensing method. The cognitive node can obtain the chance of the wireless communication because WS can be detected with low false alarm probability by the proposed method.

Physical conversion sensor networks (PhyC-SN) achieve simultaneous data collection in wireless sensor networks. Although the PhyC-SN can recognize the median and the outliers of all the sensing data simultaneously, their separation into each sensor data is a difficult task. To address this task, we have proposed a data separation method that utilizes multi-target tracking with use of the sensing data and the received spectrum power for the separation. Even if some of the sensor data are close to each other, the instantaneous power of the sensor data bearing signal is a useful feature for the separation. In this paper, we clarify the separation accuracy of our separation method under various wireless environments by computer simulation.

In Physical Layer Network Coding (PLNC), since the two sources access the relay station at a time, the relay station can hardly demodulate each information owing to the mutual interference between two transmitted signals. The PLNC achieves the high secure relay communication based on physical layer security (PLS). The source needs the transmit power control based on the channel state information (CSI) for maintaining the secure mutual interference. The untrusted relay, however, may impersonate the CSI for breaking it. So far, the authors have evaluated the amount of the leaked information to the untrusted relay by the impersonation of CSI but the leaked information is not maximal. For the countermeasure to the impersonation of CSI, the most powerful model of the untrusted relay to maximizing the leaked information is necessary. This paper constructs the optimal impersonation of CSI by a linear programing problem.

This paper proposes an opportunistic routing scheme maximizing space-time block code (STBC) cooperative diversity gain, scheduling access control and reducing power consumption for multi-hop relay networks. From the results of the simulation, the proposed method can achieve considerable improvement of the power consumption of each node.

Spectrum sharing by using cognitive radio technology has attracted attention as an effective solution to shortage of spectrum resource. In the spectrum sharing, unlicensed users (secondary users: SUs) exploit white space (WS) which is unused band by licensed users (primary users: PUs). In the related works, the channel assignment method maximizing the SU communication quality while protecting the PU is proposed when multiple SUs exist. In this method, the distance between SUs on the same channel is maximized in order to minimize the mutual interference among SUs. Therefore, it may cause the spatial fragmentation of spectrum resource and new SUs are difficult to share the same spectrum. In this paper, a novel channel assignment method based on perimeter to area ratio of WS is proposed. In the proposed method, WS is formed for easy entry of new SUs when the channels are assigned to SUs. The central control server with SU information is prepared and it assigns a channel to new SUs successively. Through computer simulations, we show that the number of SUs with an assigned channel increases by using the proposed method and new SUs can utilize WS effectively.

We propose and demonstrate a framework for statistical modeling of propagation using spectrum sensors mounted on moving vehicles. To illustrate the concept, we deploy sensors on four vehicles to collect signal strength measurements together with corresponding locations on a suburban road. From the data we build a model for large scale fading, that is, the path loss and shadowing, as well as the shadowing correlation of a TV transmitter on two UHF channels. Depending on a specific band to which it is applied, such a model can be used for different purposes like coverage planning, to improve accuracy of a white space spectrum database, for selection of relay nodes in an ad- hoc or a mesh network, selection of spectrum sensors with significant diversity gain for cooperative sensing, etc. For instance, obtained numerical results imply that sufficient decorrelation of signal strength can be observed in the experimental area if the sensors are separated by more than 20m.

Small cell networks enhance spectrum efficiency by handling the indoor traffic of mobile networks on a frequency‐reuse operation. Since most of the current mobile traffic happen in indoor, the authors introduce a prioritisation shift by imposing a limitation on the outage generated by the outdoor mobile system to the indoor small cells. The prioritisation shift consists of setting an outage probability threshold limitation on the macrocell system which is classically considered as a primary system. In this study, they consider downlink spectrum sharing between a system consisting of small cells and a macrocell with relays. The relays constitute a distributed‐space‐time block code (STBC) relaying for the outdoor system terminals. New closed‐form expressions are derived to validate the proposed bit error rate (BER) function used in their optimisation algorithm considering STBC with unequal branch SNR. They propose a joint transmit antenna selection and power allocation which minimises the proposed BER. The proposed optimisation yields a dynamic selection of the relays with power control pertaining to the outdoor mobile terminal performance. The simulation results show that their proposal exhibits a better BER compared with the conventional Alamouti STBC with equal power allocation.

This paper presents design and experimental evaluation of a distributed autonomous multi-hop vehicle-to-vehicle (V2V) communication system over TV white space performed in Japan. We propose the two-layer control channel model, which consists of the Zone Aware Control Channel (ZACC) and the Swarm Aware Control Channel (SACC), to establish the multi-hop network. Several vehicles construct a swarm using location information shared through ZACC, and share route and channel information, and available white space information through SACC. To evaluate the system we carried out field experiments with swarm made of three vehicles in a convoy. The vehicles observe channel occupancy via energy detection and agree on the control and the data channels autonomously. For coarse synchronization of quiet periods for sensing we use GPS driven oscillators, and introduce a time margin to accommodate for remaining drift. When a primary user is detected in any of the borrowed channels, the vehicles switch to a vacant channel without disrupting the ongoing multi-hop communication. We present the experimental results in terms of the time to establish control channel, channel switching time, delivery ratio of control message exchange, and throughput. As a result, we showed that our implementation can provide efficient and stable multi-hop V2V communication by using dynamic spectrum access (DSA) techniques.

Spectrum leasing is one of the cognitive radio models, where a primary user leases its spectrum resources for secondary user in exchange for cooperation. In [1] cooperative communication with beamforming (BF) in spectrum leasing was proposed for primary secure communications. However, interference is caused to the primary user from secondary user with its scheme. Therefore, we focus on cooperative communications where secondary users use orthogonal BFs that do not affect primary user. We consider the effects of secondary cooperation and the knowledge of eavesdropper's channel state information (CSI) on the cooperative communications. By simulation, we evaluate primary secrecy capacity, primary secrecy capacity outage probability, secondary sum throughput, and primary throughput. We show that secondary transmit BFs in spectrum leasing are effective for both primary and secondary systems in terms of primary secure communications without any interference from secondary user and with small degradation of the secondary throughput.

We present the results of TV band sensing experiments performed in a suburban environment in Iizuka, Japan. This work adds to our previous work in which we proposed to exploit dynamic spectrum access techniques to facilitate use of the white space to solve shortage of spectrum for vehicular networks. Here, we focus on the terrestrial TV band spectrum sensing, which in addition to the "whitespace database", is one of the methods envisioned to identify vacant channels. A convoy of four vehicles senses multiple TV channels using energy detection. Local signal strength measurements collected from the USRP software defined radios (SDRs) are combined at the trailing vehicle which acts as the fusion center. We post- processed collected measurements to improve accuracy of local sensing outcomes by removing temporal drift and differences between the sensors remaining after calibration. We tested three conventional fusion algorithms: 1) selection combining; 2) simple averaging; and 3) weighted averaging. The results show that collaboration provides a significant improvement in the sensing performance. We observed minor differences in performance among used fusion algorithms.

This paper presents design and experimental evaluation of a distributed autonomous multi-hop vehicle-to-vehicle (V2V) communication system over TV white space performed in Japan. We propose the two-layer control channel model, which consists of the Zone Aware Control Channel (ZACC) and the Swarm Aware Control Channel (SACC), to establish the multi-hop network. Several vehicles construct a swarm using location and direction information shared through ZACC, and share route and channel information, and available white space information through SACC. To evaluate the system we carried out field experiments with swarm made of three vehicles in a convoy. As the test case application, the leading vehicle sends real-time speed and sudden break information to the rear vehicle, while the vehicle in between acts as the relay. The vehicles observe channel occupancy via energy detection and agree on the control and the data channels autonomously. For coarse synchronization of quiet periods for sensing we use GPS driven oscillators, and introduce a time margin to accommodate for remaining drift. When a primary user is detected in any of the borrowed channels, the vehicles switch to a vacant channel without disrupting the ongoing multi-hop communication. We present results of the experiments in terms of the time to establish control channel, channel switching time, and throughput.

Relay-based communication systems bring a significant number of advantages to the communication world. However, they impose more delay on the systems than do systems without a relay. We propose a method based on rateless codes to reduce their delay. We start by calculating the boundary region of coding-based relay systems and classical relay systems, and we identify the condition under which coding-based systems function faster. We then show that this region defined by this condition significantly depends on the SNR and packet length of the systems. Finally we simulate such a system and present the results.

A novel resource allocation scheme for mobile secondary users (SU) in a cellular cognitive radio network (CRN) is presented, which shares spectrum with primary users (PU) by hybrid overlay/underlay sharing method. Assuming the PUs' activities are stable during one period, this paper studies how to allocate subchannels to several mobile SUs and power control to avoid interference to PUs. The allocation problem is defined as a maximum throughput and fair access (MTFA) problem, which seeks fair access opportunities for each SU and maximizes the expected throughput as well. With the mobility information of SUs, we present a general framework to solve the problem, which is divided into several sub-problems during each basic time period (BTP). In the proposed framework, a maximum weighted bipartite matching (MWBM) is utilized to solve the MTFA problem in each BTP. Our proposal is evaluated by simulations using assumed mobility traces. Compared with channel greedy algorithm, the proposed algorithm outperforms in terms of access fair only with a small reduction in network throughput. Compared with random access algorithm, it has much better performance not only in throughput but also access fairness.

Vehicular networking has significant potential to enable diverse range of applications, including safety and convenience. As the number of vehicles and applications using the specially designated wireless spectrum grow, one can expect substantial increase in the bandwidth requirements. In this paper and demonstration, we advocate that dynamic spectrum access techniques facilitating the utilization of white spaces for vehicles will be the first step towards solving the expected spectrum shortage. In the demonstration, we will introduce field tests of a multi-hop inter-vehicle communication system with distributed and autonomous TV white space channel selection, performed in Japan from January to February 2012. Furthermore, in addition to the field test videos, we will show an indoor emulation of the entire system used during the field tests in the vehicles.

This paper proposes a new evaluation model considering cost based on a cost parameter to evaluate the performance of cellular system. One of the issues of the next generation cellular systems is the improvement of cell-edge throughput performance. In order to improve the cell-edge throughput performance and to extend the coverage area, relay transmission is becoming a promising technique. The cell-edge throughput performance degrades because the signal from the base station (BS) becomes weak due to the large propagation loss and large inter-cell interference. By using relay transmission, cell-edge throughput performance improves because it can reduce the propagation loss. However, the larger number of relay station (RS) increasing the total cost. The cost of each RS is relatively low compared to the cost of the BS because of its simple structure. Thus, the performance evaluation considering RS cost is important in terms of whether to introduce RSs in cellular systems or not. In this paper, we propose a simple evaluation model considering cost to assess the total performance of multi-cell cooperative multi-hop cellular systems.

Routing is a challenging issue when dealing with the multi-hop cognitive radio networks (CRNs). The stability of a route is highly influenced by the behavior of the primary user. The more frequently primary user changes its activity, the less stable spectrum availability the cognitive user has. This causes tremendous route stability fluctuation in CRNs. The radio environmental issues that affect the route stability for the CRNs are: primary exposed node (PEN) and primary hidden node (PHN). These issue makes the route stability becomes one of the most important problem in the CRNs. To address this stability problem, in this paper we propose a radio environment aware stable routing scheme (RASR) for multi-hop CRNs. RASR evaluates the route stability by defining a routing metric, which uses the second smallest eigen value of the Laplacian matrixes. The proposed routing metric takes into account route stability, path length and the activity of the primary users. Moreover, the proposed RASR can avoid the PEN and PHN during routing. To solve the PEN and PHN a channel priority list (CPL) is kept locally by each secondary users. Simulation result shows that the proposed RASR enhances the route stability compared to the conventional routing schemes AODV with hop-count routing metric and connectivity based routing scheme Gymkhana.

We propose a novel channel selection method for transmitting information that takes into account the amount of communication data and control data generated by the secondary users within a cognitive radio network. In this paper, multiple primary channels are characterized according to a channel occupancy ratio and a state transition ratio (STR), from which the secondary user selects the channel most suitable for transmitting the control information. By obtaining these ratios, the secondary user can estimate the size of a spectral white space for each channel belonging to the primary user. The proposed method is evaluated through computer simulation results and we can confirm the long-term white space can be remained for data transmission.

This paper presents a joint resource allocation and interference avoidance algorithm for uplink transmissions in a multi-cell cognitive radio network (CRN), which overlays with a multi-cell primary network (PN). We consider a primary willingness based coexistent architecture. Primary base stations will broadcast pilot signals and interference margins to the CRN for interference channel evaluation and power control. The objective of the algorithm is to maximize the sum rate of cognitive radio cells without causing unacceptable interference to primary receivers, where Lagrangian duality based technique has been utilized to solve the maximization problem and jointly allocate the subchannels and power for each user. The fairness among users is considered within the joint resource allocation to guarantee that the instantaneous rate for each user is larger than a given minimum rate. Simulation results show the efficiency of our algorithm, which has good convergent performance. Moreover, compared to the conventional schemes, the proposed algorithm can satisfy the fairness well, and also obtain a large gain on cell-edge user throughput only with a small reduction in cell sum rate.

In this paper, we propose novel criterion and novel power control schemes based on the capacity conservation ratio (CCR) by taking the Rayleigh fading effect into account using theoretical analysis. The CCR is defined as the ratio of the decreased capacity in the spectrum sharing to the original capacity of a system. We utilize the CCR as a novel metric for protecting a primary system (PS) from large capacity degradation. The proposed power control schemes based on CCR are divided into two kinds of power control scheme; an exact power control scheme and a simplified power control scheme. We analytically evaluate the performance of the simplified power control scheme and compare it with that of the other. We find that the simplified power control scheme offers sufficient PS protection performance without high computational cost.

Switching estimated receiver position (SwERP) scheme is proved to be a promising solution for indoor positioning system, owing to its high achievable accuracy and consistency. The high positioning accuracy is achieved from sensitivity (Rx,S) limit, field-of-view (FOV) limit, and assisted azimuth and tilt information from 6-axis sensor. In this paper, we propose a physical simulation model that can predict the latter three factors. The conventional visible light communication (VLC) model uses only geometric optics (GO) to predict light propagation, which is not enough to define the FOV limit. Thus, we propose a novel method using rotation matrix with cone function and support vector machines (SVMs) to classify the boundary of FOV limit. Based on sensitivity and FOV limits, possible azimuth and tilt angulations are mathematically defined. Moreover, by including FOV limit into the simulation, transmitters and their mirrors that are outside FOV limit can be neglected, of which reduce at least 80% of computation during GO calculation.

Cognitive radio (CR) technology is a new communication paradigm that can be a solution for the spectrum scarcity problem. A new open spectrum operation necessitates a novel routing scheme to exploit the available spectrum opportunistically. In this paper, we propose a distributed routing scheme for multi-hop cognitive radio mesh networks. In cognitive radio networks the behavior of the primary user influences the secondary networks connectivity and the relevant performance. Some primary users may be hidden node and some primary user may be exposed node to the secondary users. The proposed routing schemes can avoid the primary exposed and primary hidden node problem during routing. We propose, a channel priority lists is kept by the secondary users. The secondary users select the channel among the channel priority lists depending on the primary user activity. Therefore it can avoid the end to end reroute procedure due to the exposed or hidden node problem. Throughput and end to end delay is used for the evaluation criteria. Simulation result shows that the proposed routing scheme enhances the network throughput and reduces the end to end delay significantly.

Nearest transmitter information is a mandatory requirement for utilizing Switching Estimated Receiver Position (SwERP) scheme, of which was proposed to enhance accuracy of Visible Light ID (VLID) positioning system. The conventional approach is achieved by controlling Sensitivity (RxS) limit. Conversely, general distance estimation by optical received power can also be used. Both of the mentioned methods have disadvantage on implementation complexity and inaccuracy due to noise fluctuation, respectively. In this paper, we propose a nearest transmitter classification (NTC) method by utilizing Optical Orthogonal Code (OOC) with On-Off Keying (OOK) modulation at transmitters (Txs), and perform oversampling at a receiver (Rx) to overcome the limitation of bandwidth resolution (B). The results confirm that the proposed method can classify the nearest Txaccurately, with some tradeoff with computation complexity from the increment of oversampling factor (Oc).

TCP service constructs high quality end-to-end communication link. TCP needs two way communication links. First link and second one are necessary for transmitting data packet from source to destination and ACK packet form destination to source, respectively. Therefore, TCP throughput strictly depends on both links. In wireless communication, the link speed is time selective due to shadowing effect. When the link speed is dramatically changed during the event of downloading, the impact of time selective link speed should be significant. In this paper, we clarify the impact of fluctuating link speed to TCP throughput by network simulator. In addition, we propose the adaptive link speed control of ACK link for achieving large ACK throughput. We also confirm the effect of proposed technique by network simulator.

Future vehicular communications systems are expected to utilize the vacant channels (white spaces) of the spectrum, otherwise allocated for specific designated use. One such candidate of white space comes from the TV broadcast band. In this demonstration, we will first present animated results of a TV spectrum measurement campaign along the entire portion of Interstate I-90 located in the US state of Massachusetts. Next, we will demonstrate a cyber-physical proof-of-concept lab implementation of our previously developed control and data channel assignment schemes for vehicle-to-vehicle communications over (TV) white space. Finally we will show a video of actual vehicle to vehicle communications field tests conducted in Japan using TV white space.

In cognitive radio, the mobile terminal senses the wireless accessing of the other wireless communications, specifies the vacant frequency channel, and then tries to use the specified frequency spectrum. In sensing technique, the detection accuracy depends on the detection time and thus the number of detectable systems also depends on it. When the other system is in the undetectable area for the cognitive radio, cognitive radio must protect the wireless access of it. In this paper, we consider the cognitive radio with using carrier sensing and transmitting power control. In considered system, the accessing protocol based on carrier sensing is established for protecting detectable other system. In addition, the transmitting power for suppressing the interference to the undetectable system is controlled. Since the sensing time depends on the detectable area, the transmitting power of cognitive radio transmitter and the opportunity of finding vacant spectrum are changed. Therefore, we derive the optimal sensing time for achieving the largest channel capacity.

In this paper we evaluate the sensing performance by using a MRC based blind channel combining scheme in low SNR environment, to sense the low level primary signal in cognitive radio with multiple antenna. MRC based blind channel combining for multiple antennas is known as achieving almost the same performance compared with an optimum MRC which has full knowledge of the channels if we apply it in moderate SNR environment (≥ 0 dB). However, in low SNR environment (≤ -10 dB), the performance degrades. A combining scheme based on Eigen-Value-Decomposition (EVD) theory is selected in this paper and we evaluate the sensing performance with multiple antennas.

In this paper, we propose a novel multi-antenna utilization scheme for avoiding the packet congestion around the gateway (GW) of the ad-hoc wireless networks. In our previous work, we have discussed the number of antenna design for suitable for packet congestion around the GW. However, only multi-user access with multi-antenna is considered at the receiver node. Moreover, we do not consider the effective media access control (MAC) protocol for this kind of networks. In this paper, in order to realize the effective multi-packet access ad-hoc wireless networks, we consider applying multi-input multi-output (MIMO) technique for packet transmission to the next hop node, and we also propose a MAC protocol avoiding the hidden node problem for supporting the multi-packet access with multi-antenna at the nodes around the GW.

In this paper, we proposed multiband received signal strength fingerprint (MRSS) based location system employing the frequency diversity of received signal strength (RSS). The enhancements of estimated accuracy contribute to the frequency diversity. This paper shows the experimental results under the area of 103 m2, we achieved the accuracy improvement over 40 percent, comparing with the singleband RF fingerprint.

This paper proposes a dynamic subcarrier utilization method using OFDM among the surrounding multi-hop nodes for improving the bottleneck node caused by unequal link quality of the flow from the source node to the destination node in TDMA multi-hop wireless networks. Although a flexible network can be realized by using multi-hop communication, a hidden node problem occurs between the links in the self flow and degrades the end-to-end throughput performance. As one of the solution of the hidden terminal problem, a TDMA multi- hop wireless network is considered. In TDMA multi-hop wireless network, the transmitting timing can be controlled not to give the interference toward the other links of the self flow. However, the data rate from the source node to the destination node of a fixed TDMA frame size is limited by the lowest quality link with small transmittable bits. As a result, the performance improvement by reducing the interference degrades. In this paper, the dynamic subcarrier assignment method is applied to reduce the effect of bottleneck link of TDMA wireless multi-hop networks. The proposed method can decide the used subcarriers by combining with a routing for establishing the multi-hop network.

This paper proposes a high contribution node selection method for STBC distributed ARQ. The STBC distributed ARQ can send the data packet with multi-hop by repeating the data packet from the surrounding distributed nodes. This system can realize the cooperative diversity without deciding the route from the source node to the destination node in advance. However, the power consumption of each node is large due to the redundant packets are generated. In this paper, in order to reduce the redundant packets, the high contribution node selection method by using the node contribution level to the communication and the limitation of repetition are considered for a power reduction method without serious degradation of packet transmission.

Abstract In multi‐carrier CDMA cellular systems, hotspot communication can be established to support the high‐traffic areas by using the same frequency band of the original cellular systems. However, interference from the hotspots deteriorates the communication performance of the original cellular system. In this paper, in order to decrease the interference, we set up the access point (AP) of hotspots with the adaptive array antenna and code assignment method between the cellular and the hotspot communication is considered. In the proposed system, OFDM hotspot communication is overlapped to the uplink of MC/DS‐CDMA cellular system in the same frequency band and the beam‐forming method is applied to eliminate inter‐system interference. Moreover, by allocating orthogonal variable spreading factors (OVSF) code to the both hotspot users and cellular users in the hotspot uplink period, the orthogonality of each user is kept. As a result, we can embed many hotspots into the cellular system with very small interference toward the uplink communication of the cellular system and we can improve the throughput of total system. The performance of the proposed system is evaluated by computer simulation under additive white Gaussian noise (AWGN) and Rayleigh fading environment. Copyright © 2007 John Wiley & Sons, Ltd.

In wireless mesh network for accessing to the Internet, the target of all traffic generated from distributed nodes is a gateway (GW). Therefore, many packets are concentrated around the GW, and the communication channel around the GW is overloaded. In this paper, in order to avoid the congestion around the GW, we consider an adaptive array antenna setting on the GW and relay nodes. By using an adaptive array antenna, the received two or more signals can be demodulated at the same time and the network capacity around the GW can be improved. The number of simultaneously demodulated signals is decided by the number of antenna elements. However, to improve the throughput of the entire network, a redundant number of antenna elements boosts a further load at the particular nodes and generates novel bottleneck nodes. Then, we propose a balance improvement design of the number of antenna elements setting up in each node. By using the computer simulation, we confirm the performance improvement of the proposed system with appropriate number of multi-antenna.

In this paper, we propose a soft decision based cooperative sensing method for cognitive radio (CR) in ad-hoc networks. A CR can sense a surrounding radio environment and adapt to the environment by the reconfigurability to achieve more effective frequency utilization. Observing the environment, CR should detect presence or absence of primary user and exploits this information to opportunistically provide communication among secondary users while performance of primary user should not be deteriorated by the secondary users. Because of multi- path fading or shadowing, the detection of primary users may be significantly difficult. For this problem, cooperative sensing (CS), where gathered observations obtained by multiple users is utilized to achieve higher performance of detection, has been investigated. We propose a soft decision based CS where test statistic used in traditional single user energy detection is treated as soft decision information. The detector is designed analytically, i.e., the statistic of the performance, detection probability and given false alarm, can be obtained analytically. By computer simulations, we have presented as follows; validity of analysis and that the CS has better performance compared to non-cooperative sensing. In addition, we have presented the detection performance of cooperative sensing when there are considerable differences regarding signal to noise ratio among users.

The cognitive radio is a secondary wireless communication system that can overlap the frequency band assigned to the primary system by recognizing the frequency status. Ad-hoc cognitive radio is considered for realizing the cognitive radio by using multi-hop communication networks without giving the large interference toward the primary system. We have proposed the STBC distributed ARQ system applied to the ad-hoc cognitive radio for realizing effective cognitive radio. This system can realize a multi-hop communication from the source terminal to the destination terminal without deciding the reliable route in advance. However, the affect of inter-system interference has not been evaluated yet. In this paper, in order to keep the interference level low at the receiver of the primary system, the permissible maximum transmit power of the cognitive terminals is analytically derived. Moreover, we propose a novel STBC distributed ARQ using multifrequency band for improving the performance of the ad-hoc cognitive radio due to the small transmit power and the large interference from the primary system. Finally, we confirm the effectiveness of the proposed system by using computer simulations

In this paper, we propose a new concept namely forward interference avoidance (FIA) using adaptive array antennas (AAAs) for wireless mobile ad hoc networks (MANETs). It enables nodes to avoid interfering with other nodes so that it results in increasing the number of co-existent wireless links. The performance improvement of MANET in terms of the increase of the number of co-existent communication links is investigated through computer simulations

In this paper, we focus on multicarrier CDMA systems, which are known as one of the candidates of the access method for broadband mobile communication systems, and propose a performance improvement method at the edge of the cells by using a novel site diversity technique. In order to improve the performance of terminals located at the cell edge in one-dimensional cell systems, we have proposed combined system between space time block coding (STBC) and the site diversity techniques for multicarrier CDMA. This method can improve the performance of terminals located around the cell edge by designing the scrambling code to keep the orthogonality of the signals transmitted from the adjacent two base stations. However, in multi-cell systems, since cells are displayed with two-dimensional expansion, the scrambling code assignment is complicated. In this paper, in order to improve the performance of the site diversity in multi-cell multicarrier CDMA systems, we propose a scrambling code design and assignment scheme with layered structure for STBC site diversity.

In order to improve the performance of multi-carrier code division multiple access (MC-CDMA) in the up-link channel, quasi-synchronous MC-CDMA with a minimum mean square error (MMSE) based subcarrier combining method is effective. However, the MMSE method requires many reference pilot symbols to derive the optimal weights with realistic computational complexity. In order to reduce the number of pilot symbols for up-link MC-CDMA systems, we propose a multi-stage RLS (MS-RLS) method for deriving the weights of MMSE subcarrier combining. In the MS-RLS, the received symbols are stored in the buffer memory and the RLS algorithm is performed repeatedly using the same pilot symbols. The weights and the inverse matrices of the correlation matrices of the adjacent subcarriers are utilized for the initial values of the next stage weight updating. By computer simulation, we can confirm that the performance of MC-CDMA in the up-link channel is improved using the proposed MS-RLS method with short pilot symbols.

MC-CDMA has attracted significant attention as one of the downlink communication methods for fourth generation mobile communication systems. However, like the other non-spreading multi-carrier systems, MC-CDMA has a peak power problem. We propose a novel peak power reduction technique for MC-CDMA using code selection at the transmitter. The transmitter selects the code shift pattern from plural preassigned code shift patterns in each user cluster to minimize the output peak power of downlink signals. The proposed technique can achieve blind code detection of the transmitting codes at the receiver. However, since the detection performance degrades if the number of users increases, a code detection error recovery technique is also considered.

MC-CDMA has attracted significant attention as one of the downlink communication methods for fourth generation mobile communication systems. However, MC-CDMA has a peak power problem as well as the other nonspread multi-carrier systems. Therefore, in this paper, we propose novel peak power reduction technique for MC-CDMA using code selection at the transmitter. In the proposed system, the transmitter selects the code from plural pre-assigned codes of each user in each symbol to minimize the output peak power of downlink signals. The proposed technique also can achieve blind code detection in the receiver using correlation of pre-assigned codes without a side information channel for informing the transmitting code to the receiver in each symbol.

We propose to set an OFDM adaptive array on a mobile terminal in order to collect the signals received from multi-base stations efficiently in an indoor wireless system. By doing so, the system will obtain some diversity gain when the received signals contain the same data. Moreover, when they contain different data, the mobile terminal is capable of mitigating the interferer waves and thus obtaining the desired signal. The performance of the proposed system is evaluated by computer simulations and the possibility of constructing a system without the use of frequency assignment or time assignment in wireless networks is discussed.

Multicarrier modulation has been considered as a solution to the frequency selective fading problem in high speed wireless LAN. With multicarrier modulation, high efficiency channel utilization is enabled by dynamic carrier assignment according to the demand of each terminal. Conventionally in FTDMA/DA, central station is used to assign carriers dynamically to terminals. However the system becomes large and lacks flexibility. Thus in this paper we propose a carrier assignment system without a central station, M-CSMA/RCA (multi-carrier sense multiple access with random pulse carrier assignment). In a decentralized multicarrier wireless LAN, this system can avoid packet collision by sending random pulses before transmission. This system can achieve almost the same performance against conventional centralized FTDMA/DA system in terms of delay and throughput.