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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.