This paper proposes a measurement-based spectrum database (MSD) with clustered fading distributions toward greater storage efficiencies. The conventional MSD can accurately model the actual characteristics of multipath fading by plotting the histogram of instantaneous measurement data for each space-separated mesh and utilizing it in communication designs. However, if the database contains all of a distribution for each location, the amount of data stored will be extremely large. Because the main purpose of the MSD is to improve spectral efficiency, it is necessary to reduce the amount of data stored while maintaining quality. The proposed method reduces the amount of stored data by estimating the distribution of the instantaneous received signal power at each point and integrating similar distributions through clustering. Numerical results show that clustering techniques can reduce the amount of data while maintaining the accuracy of the MSD. We then apply the proposed method to the outage probability prediction for the instantaneous received signal power. It is revealed that the prediction accuracy is maintained even when the amount of data is reduced.

In this paper, we propose a secondary user (SU) resource assignment algorithm for a multi-hop (MH) cognitive radio network to improve the end-to-end throughput. In the MH networks used for spectrum sharing, each SU needs to improve the throughput by taking the primary user (PU) protection into account. For overcoming this problem, we estimate the PU acceptable received power, which is determined by the acknowledgment packet (ACK) power from the PU receiver at each SU. With this estimation, we propose an SU optimal transmit power control algorithm to not only maximize the end-to-end throughput of the SU MH flow but also maintain the considered PU acceptable interference power. In this study, a distributed joint allocation algorithm has been used to solve the optimization problem and to effectively allocate the power of each SU.

Information exchange through a relay node is attracting attention for applying machine-to-machine communications. If the node demodulates the received signal in relay processing confidentially, the information leakage through the relay station is a problem. In wireless MIMO switching, the frequency spectrum usage efficiency can be improved owing to the completion of information exchange within a short time. This study proposes a novel wireless MIMO switching method for secure information exchange. An overloaded situation, in which the access nodes are one larger than the number of antennas in the relay node, makes the demodulation of the relay node difficult. The access schedule of nodes is required for maintaining the overload situation and the high information exchange efficiency. This study derives the equation model of the access schedule and constructs an access schedule with fewer time periods in the integer programming problem. From the computer simulation, we confirm that the secure capacity of the proposed MIMO switching is larger than that of the original one, and the constructed access schedule is as large as the ideal and minimum time period for information exchange completion.

Dynamic spectrum access (DSA) exploits vacant frequency resources via distributed wireless access. The two nodes of DSA, master and slave, access different channels, and thus, cannot communicate with each other. To compensate for the access channel mismatch between the two nodes, a rendezvous channel, which exchanges control signals between two nodes, has been considered. The rendezvous channel based on channel-occupancy ratio (COR) adaptively constructs the channel in accordance with the channel occupancy of other systems, and both a high-speed rendezvous channel and high usage efficiency of the frequency resource are accomplished owing to exploitation of the vacant channel. In the rendezvous channel based on COR, the master and slave recognize the channel with minimum measured COR as the superior channel. As the master sends the control signals through the superior channel recognized by the master, the slave accesses to the superior channel recognized by the slave with higher access rate than to the other channels. As a result, the slave can receive the control signals with highly probability and thus high speed rendezvous channel is achieved. If the master and the slave recognize the different channel as the superior channel, the access rate to the other channel should be larger. This is because the slave obtains the opportunity of receiving the control signals through the different channel from the superior channel recognized by slave and thus the high probability that the slave can receive the control signals is maintained. Therefore, the access rate of slave should be constructed in accordance with the recognition of superior channel by master and slave. In this paper, the access rate of slave to the superior channel is optimally constructed using the analyzed probability of completion of rendezvous channel. The analysis of the probability of completion of rendezvous channel includes the recognition of superior channel by master and slave. Even if the master and the slave recognize the different channel, the constructed access rate of slave can maintain the high speed rendezvous channel. From the theoretical analysis and computer simulation, the rendezvous channel based on COR with the optimal access rate to the channel with the lowest COR achieves reduced time for the rendezvous channel.

Spectrum sensing is an important function for dynamic spectrum access (DSA) type cognitive radio systems to detect opportunities for sharing the spectrum with a primary system. The key requirements for spectrum sensing are stability in controlling the probability of false alarm as well as detection performance of the primary signals. However, false alarms can be triggered by noise uncertainty at the secondary devices or unknown interference signals from other secondary systems in realistic radio environments. This paper proposes a robust spectrum sensing method against such uncertainties; it is a kind of cyclostationary feature detection (CFD) approaches. Our proposed method, referred to as maximum cyclic autocorrelation selection (MCAS), compares the peak and non-peak values of the cyclic autocorrelation function (CAF) to detect primary signals, where the non-peak value is the CAF value calculated at cyclic frequencies between the peaks. In MCAS, the desired probability of false alarm can be obtained by setting the number of the non-peak values. In addition, the multiple peak values are combined in MCAS to obtain noise reduction effect and coherent combining gain. Through computer simulations, we show that MCAS can control the probability of false alarm under the condition of noise uncertainty and interference. Furthermore, our method achieves better performance with much less computational complexity in comparison to conventional CFD methods.

In this paper, we investigate a multi-packet transmitting and receiving wireless mesh network that uses a multi-antenna set on each node in the network. In wireless mesh networks for accessing 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 crowded. To prevent packet congestion around the GW, we propose setting an adaptive array antenna on the GW and the relay nodes. We also calculate an appropriate number of antenna elements considering the fair traffic over the whole region, to prevent packet congestion at each node.

In this paper, we consider a multi-cell cognitive radio network (CRN), which overlays a multi-cell primary network. To manage the coexistence, a primary-willingness based coexistent architecture and a novel intra-cell spectrum overlay and inter-cell spectrum underlay sharing method are proposed. In the system, primary base stations will broadcast pilot signals and interference margins to assist the CRN for interference channel evaluation and power control. Subject to the interference margins imposed by the primary network, we define a utility (payoff) function that can represent the secondary system performance while taking into account the co-channel interference among secondary cells. A distributed resource allocation scheme is devised to guarantee the primary performance, and at the same time, maximize the secondary utility without any cooperation among cognitive base stations (CBS). Quality of Service among users is also considered by the scheme such that the instantaneous data rate for each secondary user is larger than a given minimum rate. The resource allocation problem can be decomposed into two subproblems: subchannel allocation and distributed power allocation game (DPAG). We prove that there exists a Nash equilibrium in the DPAG and the equilibrium is unique. Moreover, the DPAG is also Pareto optimal in some constrained environments, that is, no CBS can further improve its performance without impairing others. The proposed algorithm turns out to converge to an equilibrium within a small number of iterations.

MC-CDMA has attracted significant attention as a downlink communication method for fourth generation mobile communication systems. However, MC-CDMA has a peak power problem, similarly to other nonspread multicarrier systems. In this paper, we propose a novel peak power reduction technique for MC-CDMA using code selection at the transmitter. In the proposed system, the transmitter selects the code shift pattern from plural pre-assigned code shift patterns in each cluster to minimize the output peak power of downlink signals. The proposed technique can achieve the blind code detection of transmitting codes at the receiver. However, the detection performance degrades if the number of users is extremely large or extremely small. Therefore, in this paper, a code detection error recovery technique is also considered.

A novel timing synchronizing scheme is proposed for use in inter-vehicle communication (IVC) with an autonomous distributed intelligent transport system (ITS). The scheme determines the timing of packet signal transmission in the IVC network and employs the guard interval (GI) timing in the orthogonal frequency divisional multiplexing (OFDM) signal currently used for terrestrial broadcasts in the Japanese digital television system (ISDB-T). This signal is used because it is expected that the automotive market will demand the capability for cars to receive terrestrial digital TV broadcasts in the near future. The use of broadcasts by automobiles presupposes that the on-board receivers are capable of accurately detecting the GI timing data in an extremely low carrier-to-noise ratio (CNR) condition regardless of a severe multipath environment which will introduce broad scatter in signal arrival times. Therefore, we analyzed actual broadcast signals received in a moving vehicle in a field experiment and showed that the GI timing signal is detected with the desired accuracy even in the case of extremely low-CNR environments. Some considerations were also given about how to use these findings.

This paper derives the optimal learning time for the learning-assisted rendezvous channel. One problem with the dynamic spectrum access system of cognitive radio is access channel mismatch between two wireless terminals. In the learning-assisted rendezvous channel, before exchanging packets for link connection, the rate of channel occupancy by the other system is estimated within the learning time; it is referred to as the channel occupancy rate (COR). High speed packet exchange is made possible by selecting a low COR channel. However, the optimal learning time and the impact of COR estimation errors have not been clarified yet. This paper analyzes the time to rendezvous channel (TTR), where TTR is the time needed to complete the rendezvous with a certain probability. The results indicate that the learning time and TTR have a concave relationship which means that the optimal learning time can be determined.

In this paper, we propose a novel method for gathering sensing information by using an orthogonal narrowband signal for cooperative sensing in cognitive radio. It is desirable to improve the spectrum sensing performance by countering the locality effect of a wireless channel; cooperative sensing by using multiple inputs of sensing information from the surrounding sensing nodes has attracted attention. Cooperative sensing requires that sensing information be gathered at the master node for determining the existence of a primary signal. If the used information gathering method leads to redundancies, the total capacity of the secondary networks is not improved. In this paper, we propose a novel method for gathering sensing information that maps the sensing information to the orthogonal narrowband signal to achieve simultaneous sensing information gathering at the master node. In this method, the sensing information is mapped to an orthogonal subcarrier signal of an orthogonal frequency division multiplexing (OFDM) structure to reduce the frequency resource required for sensing information gathering. The orthogonal signals are transmitted simultaneously from multiple sensing nodes. This paper evaluates the performance of the proposed information gathering method and confirms its effectiveness.

In this paper, we propose a method of unicast and broadcast packet sharing for the orthogonal frequency division multiplexing (OFDM) multi-base station (BS) indoor wireless communication system using an adaptive array antenna on mobile terminals. The adaptive array antenna placed on the mobile terminal allows quality improvement due to the diversity effect when the data transmitted from all BSs are the same, and provides capacity improvement by channel sharing when the data from each BS are different. In the proposed sharing method, unicast packets are transmitted independently from multiple BSs in order to increase the communication capacity, and broadcast packets are transmitted simultaneously with other BSs in order to enhance the communication quality without retransmission. Furthermore, by modifying the packet assignment procedure, we confirm that quality can be improved for unicast packets in a low traffic environment.

The Orthogonal Frequency Division Multiplexing (OFDM) system is one of several suitable candidates for use in broadband wireless communications. However, due to multipath propagation, the received signal suffers from frequency-selective fading which causes significant degradation of system performance. Antenna diversity reception is widely used to solve this problem. However, this approach is not suitable for the downlink, because it increases the complexity and power consumption of the mobile station (receiver). In this paper, we consider closed-loop mode transmit diversity for OFDM, instead of diversity reception, to improve the performance in the downlink. The base station (transmitter) has several transmit antennas and each antenna is weighted by a weighting factor calculated based on feedback information (FBI). This system is a closed loop, since the FBI is fed back from the receiver. We propose a new weight generation scheme by making use of the correlation between adjacent OFDM subcarriers. The performance is evaluated under a broadband wireless channel model by computer simulation. The results show that the proposed weight generation scheme exhibits better performance than the conventional weight generation scheme without increasing the number of the FBI bits in the uplink.

This paper proposes a new multi-band received signal strength (MRSS) fingerprinting based indoor location system, which employs the frequency diversity on the conventional single-band received signal strength (RSS) fingerprinting based indoor location system. In the proposed system, the impacts of frequency diversity on the enhancements of positioning accuracy are analyzed. Effectiveness of the proposed system is proved by experimental approach, which was conducted in non line-of-sight (NLOS) environment under the area of 103 m2 at Yagami Campus, Keio University. WLAN access points, which simultaneously transmit dual-band signal of 2.4 and 5.2 GHz, are utilized as transmitters. Likewise, a dual-band WLAN receiver is utilized as a receiver. Signal distances calculated by both Manhattan and Euclidean were classified by K-Nearest Neighbor (KNN) classifier to illustrate the performance of the proposed system. The results confirmed that Frequency diversity attributions of multi-band signal provide accuracy improvement over 50% of the conventional single-band.

The spectrum sensing of the orthogonal frequency division multiplexing (OFDM) system in cognitive radio (CR) has always been challenging, especially for user terminals that utilize the full-duplex (FD) mode. We herein propose an advanced FD spectrum-sensing scheme that can be successfully performed even when severe self-interference is encountered from the user terminal. Based on the “classification-converted sensing” framework, the cyclostationary periodogram generated by OFDM pilots is exhibited in the form of images. These images are subsequently plugged into convolutional neural networks (CNNs) for classifications owing to the CNN's strength in image recognition. More importantly, to realize spectrum sensing against residual self-interference, noise pollution, and channel fading, we used adversarial training, where a CR-specific, modified training database was proposed. We analyzed the performances exhibited by the different architectures of the CNN and the different resolutions of the input image to balance the detection performance with computing capability. We proposed a design plan of the signal structure for the CR transmitting terminal that can fit into the proposed spectrum-sensing scheme while benefiting from its own transmission. The simulation results prove that our method has excellent sensing capability for the FD system; furthermore, our method achieves a higher detection accuracy than the conventional method.

In this study, we propose a cooperative sensing with distributed pre-detection for gathering sensing information on shared primary system. We have proposed a system that gathers multiple sensing information by using the orthogonal narrowband signal; the system is called the orthogonal frequency-based sensing information gathering (OF-SIG) method. By using this method, sensing information from multiple secondary nodes can be gathered from the surrounding secondary nodes simultaneously by using the orthogonal narrowband signals. The advantage of this method is that the interference from each node is small because a narrowband tone signal is transmitted from each node. Therefore, if appropriate power and transmission control are applied at the surrounding nodes, the sensing information can be gathered in the same spectrum as the primary system. To avoid interference with the primary receiver, we propose a cooperative sensing with distributed pre-detection for gathering sensing information in each node by limiting sensing node power. In the proposed method, the number of sensing information transmitting nodes depends on the pre-detection ability of the individual sensing at each node. Then the secondary node can increase the transmit power by improving the sensing detection ability, and the secondary node can gather the sensing information from the surrounding secondary nodes which are located more far by redesign the transmit power of the secondary nodes. Here, we design the secondary transmit power based on OF-SIG while considering the aggregated interference from multiple sensing nodes and individual sensing ability. Finally we confirm the performance of the cooperative sensing of the proposed method through computer simulation.

In this paper, we introduce a distributed power allocation strategy for random access, that has the capabilities of multipacket reception (MPR) and successive interference cancellation (SIC). The proposed random access scheme is suitable for machine-to-machine (M2M) communication application in fifth-generation (5G) cellular networks. A previous study optimized the probability distribution for discrete transmission power levels, with implicit limitations on the successful decoding of at most two packets from a single collision. We formulate the optimization problem for the general case, where a base station can decode multiple packets from a single collision, and this depends only on the signal-to-interference-plus-noise ratio (SINR). We also propose a feasible suboptimal iterative per-level optimization process; we do this by introducing relationships among the different discrete power levels. Compared with the conventional power allocation scheme with MPR and SIC, our method significantly improves the system throughput; this is confirmed by computer simulations.

Recently, the growing concepts that information communication technologies apply to social infrastructures have caused deep interests with wireless sensor networks (WSNs). WSNs can be used for various application areas such as home, health, factory and so on. For the different application areas, there are different technical issues (e.g., security, reliability, real time gathering, long life time, scalability). Efficient information gathering can be potentially obtained if we take a suitable information gathering method with considering the requirements of each WSN application. Thus, we have not persisted all information gathering perfectly and have proposed one of simple information gathering methods in response to the requirements of WSN applications in this paper. In the proposed method, the information is converted to physical-layer parameters of wireless communications, such as frequency and time. Also, simulations are performed to validate the effectiveness of the proposed method in real time gathering and estimating with high precision.

In this paper, we propose a novel highly reliable packet transmission protocol for ad-hoc wireless networks without deciding the route from a source node to a destination node in advance. The proposed protocol uses distributed surrounding nodes as transmitters of the retransmission packet when the transmitted packet contains an error. In this protocol, when a packet is not correctly received at the destination node, the source node and the surrounding nodes that have correctly received the packet simultaneously retransmit the same data packet to the destination node. The transmitting timing is triggered by the control packet transmitted from the source node. These operations are repeated until the packet reaches to the destination node like automatic repeat request (ARQ). Moreover, the retransmitted packet is encoded by one branch of the space time block code (STBC) for improving the performance with the network diversity effect. We call this method as STBC Distributed ARQ scheme. The performance of the proposed scheme is evaluated by the computer simulations.

This paper provides theoretical analyses for maximum cyclic autocorrelation selection (MCAS)-based spectrum sensing techniques in cognitive radio networks. The MCAS-based spectrum sensing techniques are low computational complexity spectrum sensing in comparison with some cyclostationary detection. However, MCAS-based spectrum sensing characteristics have never been theoretically derived. 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 values match well with each other.