Conventional localization techniques such as triangulation and multilateration are not reliable in non-line-of-sight (NLOS) environments such as dense urban areas. Although fingerprint-based localization techniques have been proposed to solve this problem, we may face difficulties because we do not know the parameters of the illegal radio when creating the fingerprint database. This paper proposes a novel technique to localize illegal radios in an urban environment by interpolating the channel impulse responses stored as fingerprints in a database. The proposed interpolation technique consists of interpolation in the bandwidth (delay), frequency and spatial domains. A localization algorithm that minimizes the squared error criterion is employed in this paper, and the proposed technique is evaluated through Monte Carlo simulations using location fingerprints obtained from ray-tracing simulations. Results show that utilizing an interpolated fingerprint database is advantageous in such scenarios.

Recently, wireless multi-hop network using MIMO two-way relaying technique has been attracted much attention owing to its high network efficiency. It is well known that the MIMO two-way multi-hop network (MTMN) can provide its maximum throughput in uniform topology of node location. However, in realistic environments with non-uniform topology, network capacity degrades severely due to unequal link quality. Furthermore, the end-to-end capacity also degrades at high SNR due to far (overreach) interference existing in multi-hop relay scenarios. In this paper, we focus on several power allocation schemes to improve the end-to-end capacity performance of MTMN with non-uniform topology and far interference. Three conventional power allocation schemes are reformulated and applied under the system model of MTMN. The first two are centralized methods, i.e., Eigenvector based Power Allocation (EPA) which employs linear algebra and Optimal Power Allocation (OPA) using convex optimization. The last one is Distributed Power Allocation (DPA) using game theory. It is found from numerical analyses that the power allocation schemes are effective for MTMN in terms of end-to-end capacity improvement, especially in non-uniform node arrangement and at high SNR.

In the European satellite broadcasting specifications, the symbol rate and the carrier frequency are not regulated. Furthermore, the first generation format DVB-S does not have any control signals. In a practical environment, the received signal condition is not stable due to the imperfect reception environment, i.e., unterminated receiver ports, cheap indoor wiring cables etc. These issues prevent correct detection of the satellite signals. For this reason, the conventional signal detection method uses brute force search for detecting the received signal's cyclostationarity, which is an extremely time-consuming approach. A coarse estimation method of the carrier frequency and the bandwidth was proposed by us based on the power spectrum. We extend this method to create a new method for detecting satellite broadcasting signals, which can significantly reduce the search range. In other words, the proposed method can detect the signals in a relatively short time. In this paper, the proposed method is applied to signals received in an actual environment. Our analysis shows that the proposed method can effectively reduce the detection time at almost a same detection performance.

Densification of mmWave smallcells overlaid on the conventional macro cell is considered to be an essential technology for enhanced mobile broadband services and future IoT applications requiring high data rate e.g. automated driving in 5G communication networks. Taking into account actual measurement mobile traffic data which reveal dynamicity in both time and space, this paper proposes a joint optimization of user association and smallcell base station (BS)'s ON/OFF status. The target is to improve the system's energy efficiency while guaranteeing user's satisfaction measured through e.g. delay tolerance. Numerical analyses are conducted to show the effectiveness of the proposed algorithm against dynamic traffic variation.

MIMO-OFDM combining OFDM and MIMO techniques achieves high spectral efficiency and is able to increase throughput. MIMO-OFDM systems can be classified into either “open loop” or “closed loop” depending on whether the CSI is fed back from the Rx to the Tx. As a closed loop scheme, SVD-MIMO is the optimal single user MIMO-OFDM transmission scheme while it requires knowledge of the CSI at both the Tx and Rx. In practical systems, Tx weight is fed back from the Rx to the Tx by limited bits and with feedback delay, which causes mismatch between the weight and the real channel especially if the channel exhibits time variation. Hence, the transmission performance of the SVD-MIMO scheme degrades. Therefore, the performance comparison between open loop and closed loop schemes against channel variation is very important for practical deployment of MIMO-OFDM systems. For that purpose, a unified performance calculation method for the open loop and the closed loop MIMO-OFDM schemes with finite and delayed feedback is developed in this paper. The method is effective for analysis of both STBC for the open loop and SVD-MIMO using codebook for the closed loop with per stream layer AMC. Also, to combat frequency selective fading in practical wireless channels, an interleaver is employed in this paper. In numerical analyses, it is found that simulation results agree well with the derived theoretical performance results. Secondly, from these results, the cross-over point of the throughput performance of two schemes in terms of UE velocity and SNR is found.

This paper empirically validates battery-less sensor activation via wireless energy transmission to release sensors from wires and batteries. To seamlessly extend the coverage and activate sensor nodes distributed in any indoor environment, we proposed multi-point wireless energy transmission with carrier shift diversity. In this scheme, multiple transmitters are employed to compensate path-loss attenuation and orthogonal frequencies are allocated to the multiple transmitters to avoid the destructive interference that occurs when the same frequency is used by all transmitters. In our previous works, the effectiveness of the proposed scheme was validated theoretically and also empirically by using just a spectrum analyzer to measure the received power. In this paper, we develop low-energy battery-less sensor nodes whose consumed power and required received power for activation are respectively 142µW and 400µW. In addition, we conduct indoor experiments in which the received power and activation of battery-less sensor node are simultaneously observed by using the developed battery-less sensor node and a spectrum analyzer. The results show that the coverage of single-point and multi-point wireless energy transmission without carrier shift diversity are, respectively, 84.4% and 83.7%, while the coverage of the proposed scheme is 100%. It can be concluded that the effectiveness of the proposed scheme can be verified by our experiments using real battery-less sensor nodes.

In conventional wireless cellular networks, cell coverage is static and fixed, and each user equipment (UE) is connected to one or a few local base stations (BS). However, the users' distribution in the network area commonly fluctuates during a day. When there are congeries of users in some areas, conventional networks waste idle network resources in sparse areas. To address this issue, we propose a novel approach for cooperative cluster formation to dynamically transfer idle network resources from sparse cells to crowded cells or hotspots. In our proposed scheme, BS coverage is directed to hotspots by dynamically changing the antennas' beam angles, and forming large optimal cooperative clusters around hotspots. In this study, a cluster is a group of BSs that cooperatively perform joint transmission (JT) to several UEs. In this paper, a mathematical framework for calculation of the system rate of a cooperative cluster is developed. Next, the set of BSs for each cluster and the antennas' beam angles of each BS are optimized so that the system rate of the network is maximized. The trend of performance variation versus cluster size is studied and its limitations are determined. Numerical results using 3GPP specifications show that the proposed scheme attains several times higher capacity than conventional systems.

Cognitive radio (CR) is an important technology to provide high-efficiency data communication for the IoT (Internet of Things) era. Signal detection is a key technology of CR to detect communication opportunities. Energy detection (ED) is a signal detection method that does not have high computational complexity. It, however, can only estimate the presence or absence of signal(s) in the observed band. Cyclostationarity detection (CS) is an alternative signal detection method. This method detects some signal features like periodicity. It can estimate the symbol rate of a signal if present. It, however, incurs high computational complexity. In addition, it cannot estimate the symbol rate precisely in the case of single carrier signal with a low Roll-Off factor (ROF). This paper proposes a method to estimate coarsely a signal's bandwidth and carrier frequency from its power spectrum with lower computational complexity than the CS. The proposed method can estimate the bandwidth and carrier frequency of even a low ROF signal. This paper evaluates the proposed method's performance by numerical simulations. The numerical results show that in all cases the proposed coarse bandwidth and carrier frequency estimation is almost comparable to the performance of CS with lower computational complexity and even outperforms in the case of single carrier signal with a low ROF. The proposed method is generally effective for unidentified classification of the signal i.e. single carrier, OFDM etc.

In recent years, heterogeneous cellular network (HetNet) topology has been attracting much attention. HetNet, which is a network topology with low power base stations installed inside the cell range of conventional macrocells, can realize network capacity enhancement through the effects of macrocell offloading and cell shrinkage. Due to the heterogeneity nature of HetNet, network designers should carefully consider about the interference management, resource allocation, user association and cell range expansion. These issues have been well studied in recent literatures. However, one of the important problems which has not been well investigated in conventional works is the base station (BS) deployment problem in HetNet. This paper investigates the optimal pico base station deployment in heterogeneous cellular networks especially with the existence of hotspots. In this paper, pico BS locations are optimized together with other network parameters including spectrum splitting ratio and signal-to-interference-noise ratio (SINR) bias for cell range expansion to maximize the total system rate, by considering two spectrum allocation strategies, i.e. spectrum overlapping and spectrum splitting. Numerical results show that the optimized pico BS locations can improve the system rate, the average user rate and outage user rate in HetNet with hotspots.

This paper illustrates a large-scale MIMO propagation channel measurement in a real life environment and evaluates throughput performance of various MIMO schemes in that environment. For that purpose, 44 MIMO transceivers and a novel spatial scanner are fabricated for wideband MIMO channel measurements in the 5 GHz band. A total of more than 50,000 spatial samples in an area of 150 m2, which includes a bedroom, a Japanese room, a hallway, and the living and dining areas, are taken in a real residential home environment. Statistical properties of the propagation channel and throughput performance of various MIMO schemes are evaluated by using measured data. Propagation measurement results show large dynamic channel variations occurring in a real environment in which statistical properties of the channel, such as frequency correlation and spatial correlation are not stationary any more, and become functions of the SNR. Furthermore, evaluation of throughput shows that although MIMO schemes outperform the SISO system in most areas, open loop systems perform badly in the far areas with low SNR. Paying for the cost of CSI or partial CSI at Tx, closed loop and hybrid systems have superior performance compared to other schemes, especially in reasonable SNR areas ranging from 10 dB to 30 dB. Spatial correlation, which is common in Japanese wooden residences, is also found to be a dominant factor causing throughput degradation of the open loop MIMO schemes.

This work studies the benefits of heterogeneous cellular networks with overlapping picocells in a large macrocell. We consider three different strategies for resource allocation and cell association. The first model employs a spectrum overlapping strategy with an SINR-based cell association. The second model avoids the interference between macrocell and picocell through a spectrum splitting strategy. Furthermore, picocell range expansion is also considered in this strategy to enable a load balancing between the macrocell and picocells. The last model is a hybrid one, called as fractional spectrum splitting strategy, where spectrum splitting strategy is only applied at the picocell-edge, while the picocell-inner reuses the spectrum of the macrocell. We constructs resource allocation optimization problem for these strategies to maximize the system rate. Our results show that in terms of system rate, all the three strategies outperform the performance of macrocell-only case, which shows the benefit of heterogeneous networks. Moreover, fractional spectrum splitting strategy provides highest system rate at the expense of outage user rate degradation due to inter-macro-pico interference. Spectrum overlapping model provides the second highest system rate gain and also improves outage user rate owing to full spectrum reuse and the benefit of macro diversity, while spectrum splitting model achieves a moderate system rate gain.

This paper presents a method to seamlessly extend the coverage of energy supply field for wireless sensor networks in order to free sensors from wires and batteries, where the multi-point scheme is employed to overcome path-loss attenuation, while the carrier shift diversity is introduced to mitigate the effect of interference between multiple wave sources. As we focus on the energy transmission part, sensor or communication schemes are out of scope of this paper. To verify the effectiveness of the proposed wireless energy transmission, this paper conducts indoor experiments in which we compare the power distribution and the coverage performance of different energy transmission schemes including conventional single-point, simple multi-point and our proposed multi-point scheme. To easily observe the effect of the standing-wave caused by multipath and interference between multiple wave sources, 3D measurements are performed in an empty room. The results of our experiments together with those of a simulation that assumes a similar antenna setting in free space environment show that the coverage of single-point and multi-point wireless energy transmission without carrier shift diversity are limited by path-loss, standing-wave created by multipath and interference between multiple wave sources. On the other hand, the proposed scheme can overcome power attenuation due to the path-loss as well as the effect of standing-wave created by multipath and interference between multiple wave sources.

This paper addresses a noise matching problem for MIMO receiver with mutual coupling in the presence of signal and antenna noise coupling. The matching network in this paper is designed to maximize the system's ergodic capacity by means of minimizing the noise figure matrix. For reducing RF circuit complexity, low noise matching design without crossover elements of the matching circuit is derived for compact symmetrical 2$ imes$2 MIMO receiver system with mutually coupled antenna. Numerical simulation verifies our analytical results and demonstrates the superiority of the proposed matching method among feasible ones. The paper furthermore investigates the lossy matching circuit with the corresponding circuit parameters in a specific condition and the effect of practical matching circuit.

In this paper we describe and experimentally validate a dual-band digital predistortion (DPD) model we propose that takes account of the intermodulation and harmonic distortion produced when the center frequencies of input bands have a harmonic relationship. We also describe and experimentally validate our proposed novel dual-band power amplifier (PA) linearization architecture consisting of a single feedback loop employing a dual-band mixer. Experiment results show that the DPD linearization the proposed model provides can compensate for intermodulation and harmonic distortion in a way that the conventional two-dimensional (2-D) DPD approach cannot. The proposed feedback architecture should make it possible to simplify analog-to-digital converter (ADC) design and eliminate the time lag between different feedback paths.

Location information is essential to varieties of applications. It is one of the most important context to be detected by wireless distributed sensors, which is a key technology in Internet-of-Things. Fingerprint-based methods, which compare location unique fingerprints collected beforehand with the fingerprint measured from the target, have attracted much attention recently in both of academia and industry. They have been successfully used for many location-based applications. From the viewpoint of practical applications, in this paper, four different typical approaches of fingerprint-based radio emitter localization system are introduced with four different representative applications: localization of LTE smart phone used for anti-cheating in exams, indoor localization of Wi-Fi terminals, localized light control in BEMS using location information of occupants, and illegal radio localization in outdoor environments. Based on the different practical application scenarios, different solutions, which are designed to enhance the localization performance, are discussed in detail. To the best of the authors' knowledge, this is the first paper to give a guideline for readers about fingerprint-based localization system in terms of fingerprint selection, hardware architecture design and algorithm enhancement.

Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.

Coordinated Multi-point (CoMP) transmission has long been known for its ability to improve cell edge throughput. However, in a CoMP cellular network, fixed CoMP clustering results in cluster edges where system performance degrades due to non-coordinated clusters. To solve this problem, conventional studies proposed dynamic clustering schemes. However, such schemes require a complex backhaul topology and are infeasible with current network technologies. In this paper, small power base stations (BSs) are introduced instead of dynamic clustering to solve the cluster edge problem in CoMP cellular networks. This new cell topology is called the diamond cellular network since the resultant cell structure looks like a diamond pattern. In our novel cell topology, we derive the optimal locations of small power base stations and the optimal resource allocation between the CoMP base station and small power base stations to maximize the proportional fair utility function. By using the proposed architecture, in the case of perfect user scheduling, a more than 150% improvement in 5% outage throughput is achieved, and in the case of successive proportional fair user scheduling, nearly 100% improvement of 5% outage throughput is achieved compared with conventional single cell networks.

Single front-end architecture with parasitic antenna element (PAE) in compact array system has been proposed for enhancing spectral efficiency and miniaturizing the receiver. Although most of studies paid attention to design optimal receiver with antenna mutual coupling on fading correlation, relatively little attention has been paid to noise. In this paper, we propose a low noise model for single front-end MIMO receiver system with PAE which includes arbitrary signal and noise coupling. The proposed model articulates physical noise sources and relates their spatial correlation with array receive antennas, parasitic element, front-end and matching circuit. A matching circuit is designed to achieve minimum noise figure. After that, the optimal PAE value is derived to maximize channel capacity. We present numerical analysis to verify the proposed system on certain conditions.

In this paper, a Proof-of-Concept (PoC) architecture is constructed, and the effectiveness of mmWave overlay heterogeneous network (HetNet) with mesh backhaul utilizing route-multiplexing and Multi-access Edge Computing (MEC) utilizing prefetching algorithm is verified by measuring the throughput and the download time of real contents. The architecture can cope with the intensive mobile data traffic since data delivery utilizes multiple backhaul routes based on the mesh topology, i.e. route-multiplexing mechanism. On the other hand, MEC deploys the network edge contents requested in advance by nearby User Equipment (UE) based on pre-registered context information such as location, destination, demand application, etc. to the network edge, which is called prefetching algorithm. Therefore, mmWave access can be fully exploited even with capacity-limited backhaul networks by introducing the proposed algorithm. These technologies solve the problems in conventional mmWave HetNet to reduce mobile data traffic on backhaul networks to cloud networks. In addition, the proposed architecture is realized by introducing wireless Software Defined Network (SDN) and Network Function Virtualization (NFV). In our architecture, the network is dynamically controlled via wide-coverage microwave band links by which UE's context information is collected for optimizing the network resources and controlling network infrastructures to establish backhaul routes and MEC servers. In this paper, we develop the hardware equipment and middleware systems, and introduce these algorithms which are used as a driver of IEEE802.11ad and open source software. For 5G and beyond, the architecture integrated in mmWave backhaul, MEC and SDN/NFV will support some scenarios and use cases.

Infrastructure wireless mesh network has been attracting much attention due to the wide range of its application such as public wireless access, sensor network, etc. In recent years, researchers have shown that significant network throughput gain can be achieved by employing network coding in a wireless environment. For further improvement of network throughput in one dimensional (1D) topology, Ono et al. proposed to use multiple antenna technique combined with network coding. In this paper, being inspired by MIMO network coding in 1D topology, the authors establish a novel MIMO network coding algorithm for a 2D topology consisting of two crossing routes. In this algorithm, multiple network coded flows are spatially multiplexed. Owing to the efficient usage of radio resource of network coding and co-channel interference cancellation ability of MIMO, the proposed algorithm shows an 8-fold gain in network capacity compared to conventional methods in the best-case scenario.