This paper proposes a digital twin (DT)-based system to enhance pedestrian safety by visualizing blind-spot hazards through AR glasses. The system leverages roadside units (RSUs) with LiDAR and edge servers for real-time object detection, trajectory prediction, and collision prediction. Potential risks are classified into three levels, and corresponding warnings are displayed in AR to prompt timely evasive actions. To achieve accurate AR visualization, the system also integrates DT-enhanced self-localization for centimeter-level accuracy and an end-to-end latency compensation mechanism. A prototype system was developed, and its effectiveness and practicality were validated through proof-of-concept experiments.

Next-generation wireless networks are expected to leverage multi-modal data sources in order to execute various wireless communication tasks such as beamforming and blockage prediction with situational-awareness. To do so, multi-modal transformers emerged as an effective tool, however, existing transformer-based approaches suffer from high inference latency and large memory footprints when processing multi-modal data. Hence, such existing solutions cannot handle wireless communication tasks that require fast inference to track a dynamically changing environment with moving vehicles and blockages. One major bottleneck is the reliance on attention mechanisms whose complexity grows quadratically with respect to the number of tokens. Hence, in this paper, a novel, fast multi-modal transformer inference framework is designed to practically support wireless communication tasks by processing only important tokens. To this end, an optimization problem is formulated to find the optimal number of tokens under a target floating point operations (FLOPs) for a given wireless communication task while maintaining the task accuracy. To solve this problem, modality-specific tokenizers are first designed to project each modality into the same embedding dimension. Then, a token router is introduced to learn the importance of each token and process only important tokens. Subsequently, a trainable keep ratio is introduced to learn how many tokens should be processed for each layer under the target FLOPs. Simulation results show that, on DeepSense 6G beamforming tasks, the proposed framework can reduce the inference latency, GPU memory, and FLOPs by 86.2% 35%, and 80%, respectively, with negligible accuracy loss compared to a baseline that processes all tokens. To further validate the feasibility of the proposed framework for real-world deployments, a multi-modal handover dataset is developed using a real-world testbed. Emulation results on the developed dataset show that the proposed framework can proactively initiate handover before blockage, while the baseline experiences significant received signal strength degradation due to higher inference latency.

This paper presents a digital twin-based digital signage platform designed to improve the accuracy of advertising effectiveness measurement and introduce new content switching methods. By utilizing real-time pedestrian data captured through Light Detection And Ranging (LiDAR), the platform enables dynamic content switching based on pedestrian distance and movement direction. A prototype system was implemented, demonstrating the effectiveness of these new switching methods and the platform's enhanced measurement accuracy. Future work includes conducting evaluation experiments to further validate the system's practicality.

This paper presents a digital twin-empowered real-time optimal delivery system specifically validated through a proof-of-concept (PoC) demonstration of a real-world autonomous car-sharing service. This study integrates real-time data from roadside units (RSUs) and connected and autonomous vehicles (CAVs) within a digital twin of a campus environment to address the dynamic challenges of urban traffic. The proposed system leverages the Age of Information (AoI) metric to optimize vehicle routing by maintaining data freshness and dynamically adapting to real-time traffic conditions. Experimental results from the PoC demonstrate a 22% improvement in delivery efficiency compared to conventional shortest-path methods that do not consider information freshness. Furthermore, digital twin-based simulation results demonstrate that this proposed system improves overall delivery efficiency by 12% and effectively reduces the peak average AoI by 23% compared to the conventional method, where each vehicle selects the shortest route without considering information freshness. This study confirms the practical feasibility of cooperative driving systems, highlighting their potential to enhance smart mobility solutions through scalable digital twin deployments in complex urban environments.

Millimeter-wave (mmWave) communication has emerged as a pivotal technology for 5G/6G networks, offering abundant bandwidth to meet escalating data demands. However, its susceptibility to severe path loss and blockages requires efficient relay-assisted transmission. Massive relay multiple-input multiple-output (MIMO) systems can enhance coverage and spectral efficiency, but their performance is critically dependent on dynamic user scheduling and resource allocation under channel state uncertainty. In this paper, we consider the application of the massive relay MIMO system in urban environments. We propose a user scheduling algorithm based on simulated annealing and a resource allocation algorithm based on deep learning to improve resource utilization and increase user channel capacity. The effectiveness of the proposed algorithm was validated through simulations in comparison with the single-user and Max-Min baselines.

Millimeter wave (mmWave) in vehicle-to-everything (V2X) communications offers incredibly high data rates and low latency while facing significant reliability challenges due to signal blockages and limited range. This paper introduces a blockage-aware system for managing dynamic multi-hop mmWave V2X communications, with a focus on predictive blockage detection and avoidance. The proposed system integrates a mobility digital twin (DT), allowing the multi-hop routing control plane to anticipate blockages before they occur and proactively adjust routing decisions. The embedded control plane algorithm combines high-precision environmental data with trajectory prediction to predict imminent line-of-sight (LoS) disruptions and dynamically reconfigure V2X paths before communication quality degrades. We establish the mobility DT of the Nishi-Shinjuku area for simulations. The results indicate a higher connectivity ratio by using our proposed system, and this system can robustly handle both fully connected and mixed-traffic environments.

This paper explores the challenges associated with mmWave communications, particularly in terms of coverage, blockages, and network resiliency. To address these issues, we propose a multi-user, multi-hop massive relay MIMO system that extends base station coverage through the deployment of a large number of relay stations. Additionally, we present a hybrid user-centric path selection algorithm designed to optimize routing and reduce interference. These innovations enhance the system's robustness against signal blockages and environmental variability, which are critical for improving the resiliency of 6G networks. Through numerical simulations, we compare the performance of the proposed multi-hop system to traditional single-hop configurations, demonstrating substantial improvements in coverage, capacity, and overall system reliability. Our findings confirm that the proposed system offers a promising solution to the limitations of mmWave networks, paving the way for the development of resilient and efficient 6G communication systems.

Digital twin (DT) can help create a digital representation of a physical system, thereby reflecting its real-time status. The digital object, often called cyber twin (CT), facilitates real-time monitoring and control of the physical object, i.e., the so-called physical twin (PT). Owing to this ability, CTs can optimize the PTs and simulate their status, without interrupting the physical world. Given the various CT use cases, one can identify two distinct types of DT tasks: 1) update tasks for PT-CT synchronization and 2) inference tasks for obtaining real-time testing responses. The diverse real-time requirements for update/inference tasks raise the task scheduling problem that has been neglected in previous studies. In this article, the real-time DT task scheduling problem is investigated. In particular, a new approach for evaluating the performance of real-time scheduling of DT tasks is introduced considering the relationship between update/inference tasks and fairness among CTs. Moreover, offline and online DT task scheduling schemes are proposed with the goals of maximizing the DT freshness ratio and minimizing task rejections. In particular, the DT freshness ratio maximization problem is formulated as an offline task scheduling scheme. The proposed offline solution can significantly reduce the solution space without losing optimality. Furthermore, the scheduling policies for achieving the maximal DT freshness ratio are established using which an online scheduling algorithm is designed. Simulation results show that the proposed offline/online schemes increase the DT freshness ratio by at least 16% and 11%, respectively, compared to benchmarks. The results also show that the task rejection ratio of the proposed online algorithm is within 8% of the lower bound.

The commercialization of 5G has been initiated for a while. Yet, we haven't seen wide penetrations of the disruptive applications as promised, like the extended reality (XR), internet of vehicles (IoV), telesurgery, etc. Digital twins (DTs) are one of these highly anticipated applications. However, DTs demand all 5G capabilities, including enhanced mobile broadband (eMBB), ultra-reliable and low latency communications (URLLC), and massive machine type communication (mMTC) simultaneously, which makes their implementation more challenging. Owing to the advanced sensing, communication, and computing networks for beyond 5G (B5G) and 6G at Tokyo Institute of Technology, we are able to build a real-time DT on campus and demonstrate two smart mobility applications for safety and traffic efficiency, respectively, by utilizing DT-derived knowledge. Our demonstrations will convince society of the values and potentials of DTs and encourage current 5G progress towards B5G and 6G.

Recently, vehicular over-the-air (OTA) updates have been raised as an intelligent solution for the autonomous vehicle revolution. It is critical to download important vehicular safety and stability updates onboard. The forthcoming six-generation (6G) systems might consider OTA a cach service delivered by base stations or roadside units (RSUs). This paper introduces the practical implementation of OTA updates using roadside units and dual-band WiGig/Wi-Fi communications. The system's performance is investigated against different blocking vehicles (small, medium, and large), simulating realistic scenarios. Experimental results ensure the 60 GHz WiGig performance efficiency regarding download speed and response time.

Digital twin (DT) technology can replicate physical entities in cyberspace. A mobility DT digitalizes connected and autonomous vehicles (CAVs) and their surrounding traffic environment, allowing to monitor the maneuvering and distribution of CAVs in real-time, which is crucial for managing vehicle-to-everything (V2X) connectivity, especially when millimeter wave (mmWave) is adopted. MmWave V2X relies on dynamic multi-hop communications to ensure high reliability. Therefore, in this paper, the challenges of mmWave V2X are presented to motivate the utilization of DT, and then we introduce the system model for DT-based multi-hop routing management, incorporating two different routing algorithms: with and without future trajectory prediction. For proof of concept, we implement the proposed DT system using Unity-based AWSIM and evaluate the proposed algorithms via simulations. The results show that, compared to the conventional routing algorithm in vehicular ad hoc networks (VANETs), the DT-based algorithms significantly improve the reliability of mmWave V2X, and such improvements can be seen in both fully connected and mixed traffic scenarios.

In this paper, a novel joint energy and age of information (AoI) optimization framework for IoT devices in a non-stationary environment is presented. In particular, IoT devices that are distributed in the real-world are required to efficiently utilize their computing resources so as to balance the freshness of their data and their energy consumption. To optimize the performance of IoT devices in such a dynamic setting, a novel lifelong reinforcement learning (RL) solution that enables IoT devices to continuously adapt their policies to each newly encountered environment is proposed. Given that IoT devices have limited energy and computing resources, an unmanned aerial vehicle (UAV) is leveraged to visit the IoT devices and update the policy of each device sequentially. As such, the UAV is exploited as a mobile learning agent that can learn a shared knowledge base with a feature base in its training phase, and feature sets of a zero-shot learning method in its testing phase, to generalize between the environments. To optimize the trajectory and flying velocity of the UAV, an actor-critic network is leveraged so as to minimize the UAV energy consumption. Simulation results show that the proposed lifelong RL solution can outperform the state-of-art benchmarks by enhancing the balanced cost of IoT devices by 8.3% when incorporating warm-start policies for unseen environments. In addition, our solution achieves up to 49.38% reduction in terms of energy consumption by the UAV in comparison to the random flying strategy.

In Cooperative Intelligent Transportation System (C-ITS), cooperative perception emerges as a core application empowered by Vehicle-to-Everything (V2X) communications to improve road safety. Connected vehicles are able to share and receive sensor information from any other V2X-capable facilities. While most research interests lie in the utilization and integration of V2X data inside the connected vehicle systems, we stress the importance of understanding the unique role of roadside units (RSUs) for cooperative perception, as well as appropriate strategies for them to deliver this application. To that end, we designed an SDVN-based cooperative perception framework running on RSUs. By leveraging Dedicated Short-Range Communications (DSRC) and Millimeter Wave (mmWave) V2X, this framework system can adaptively support message-based cooperative perception and raw sensor data-based cooperative perception. In addition, we propose a DSRC-triggered dynamic sensor ON/OFF strategy to improve energy efficiency and RSU scheduling flexibility. The field trial results agree well with our design expectations, i.e., small delay for activation (< 30 ms), significant power reduction (~60 %), and good scalability.

Discussions have begun worldwide toward Beyond 5G/6G in the 2030s. In these challenges, the topic of intelligence is a controversial point on various layers of RAN (radio-access-network), core, edge, automation, etc. One of the ideas on that topic is a digital twin platform that integrates physical and cyberspace. This study focuses on the RAN side as the data input to the digital twin. Mainly, this paper proposes a method to obtain accurate coverage data and store it in cyberspace in a dynamically changing coverage environment. Besides, we implement the proposed method and evaluate its measurement results and effectiveness in an outdoor proof-of-concept field.

One of the key enablers for the realization of a variety of unmanned aerial vehicle (UAV)-based systems is the high-performance communication system linking many UAVs and ground station. We have proposed a spectrum-efficient full-duplex directional-antennas-equipped multi-UAV communication system with low hardware complexity to address the issues of low spectrum efficiency caused by co-channel interference in areal channels. In this paper, by using the prototype system including UAVs and ground station, field experiments are carried out to confirm the feasibility and effectiveness of the proposed system's key feature, i.e., co-channel interference cancellation among UAVs by directional antennas and UAV relative position control, instead of energy-consuming dedicated self-interference cancellers on UAVs in traditional full-duplex systems. Both uplink and downlink performance are tested. Specially, in downlink experiment, channel power of interference between a pair of two UAVs is measured when UAVs are in different positional relationships. The experiment results agree well with the designs and confirm that the proposed system can greatly improve the system performance.

Accommodating digital twins (DTs) in the metaverse is essential to achieving digital reality. This need for integrating DTs into the metaverse while operating them at the network edge has increased the demand for a decentralized edge-enabled metaverse. Hence, to consolidate the fusion between real and digital entities, it is necessary to harmonize the interoperability between DTs and the metaverse at the edge. In this paper, a novel decentralized metaverse framework that incorporates DT operations at the wireless edge is presented. In particular, a system of autonomous physical twins (PTs) operating in a massively-sensed zone is replicated as cyber twins (CTs) at the mobile edge computing (MEC) servers. To render the CTs' digital environment, this zone is partitioned and teleported as distributed sub-metaverses to the MEC servers. To guarantee seamless synchronization of the sub-metaverses and their associated CTs with the dynamics of the real world and PTs, respectively, this joint synchronization problem is posed as an optimization problem whose goal is to minimize the average sub-synchronization time between the real and digital worlds, while meeting the DT synchronization intensity requirements. To solve this problem, a novel iterative algorithm for joint sub-metaverse and DT association at the MEC servers is proposed. This algorithm exploits the rigorous framework of optimal transport theory so as to efficiently distribute the sub-metaverses and DTs, while considering the computing and communication resource allocations. Simulation results show that the proposed solution can orchestrate the interplay between DTs and sub-metaverses to achieve a 25.75% reduction in the sub-synchronization time in comparison to the signal-to-noise ratio-based association scheme.

Millimeter wave (mmWave) is an indispensable technology in 5G communication system, as its wider bandwidth assures larger channel capacity than previous 4G/LTE communication system. However, due to the high path loss in mmWave band, the deployment of more base stations is required to achieve the same coverage. Massive analog relay MIMO system, in which massive analog relay stations are deployed to construct artificial channel and enhance communication coverage, had been proposed to solve this issue. In this paper, we further consider multi-user MIMO scenario using massive analog relay MIMO system. We introduce a beam selection algorithm and resource block allocation algorithm to utilize the resource and improve the performance of the whole multi-user MIMO system. In addition, the feasibility and validity of this method is demonstrated by numerical simulation showing that the channel capacity can be improved.

We propose to combine multi-beam transmission with fountain code toward full automated driving. The proposed scheme consider a scenario where a vehicle with multiple antenna communicate with BS with multiple antenna using multi-beam. In our proposed scheme, data encoded by fountain encoder are transmitted over multi-beam. Multi-beam transmission can improve datarate due to spatial multiplexing. Fountain code is expected to reduce latency due to no need for retransmission. Moreover, the combination of fountain code and multi-beam transmission is expected to efficiently add redundancy efficiently in spatial domain, thus improve the system’s reliability in the presence of random blockage. In this paper, the reliability of our proposed scheme against different required latencies in comparison with other conventional schemes is analysed. Furthermore, we propose a beam-aware beam selection method taking into account the information about blockage probability. Numerical results show that the proposed scheme can achieve higher reliability and lower latency in blockage environment.

Millimeter-wave (mmWave) and terahertz (THz) technologies are under consideration for Beyond 5G (B5G) and 6G. However, mmWave/THz bands suffer from high propagation loss and blockage effects, making it challenging to deploy communication areas. To address these issues, we propose a digital twin platform for future wireless communication that expands communication coverage areas for mmWave bands in 5G and beyond. In this study, we construct cyberspace based on simulation results and measurement data for the mmWave environment and use augmented reality (AR) to visualize them. We also present the effectiveness of the proposed system by verifying it in an outdoor experimental field as a proof-of-concept using an actual mmWave base station.

During the past decade, smart mobility and intelligent vehicles have attracted increasing attention, because they promise to create a highly efficient and safe transportation system in the future. Meanwhile, digital twin, as an emerging technology, will play an important role in automated driving and intelligent transportation systems. This technology is applied in this paper to design a platform for smart mobility, providing large-scale route planning services. Utilizing sensing technologies and cloud/edge computing, we build a digital twin system model that reflects the static and dynamic objects from the real world in real time. With the smart mobility platform, we realize traffic monitoring and route planning through cooperative environment perception to help automated vehicles circumvent jams. A proof-of-concept test with a real vehicle in real traffic is conducted to validate the functions and the delay performance of the proposed platform.

Millimeter-wave (mmWave) vehicle-to-vehicle (V2V) with relays has been regarded as a key technology to compensate for the restriction of sensors and improve the level of autonomous vehicles. However, under mmWave V2V with relays, interference will occur when the bandwidth is reused. This interference will seriously reduce the quality and scalability of mmWave V2V with relays. Besides, the connectivity structure of mmWave V2V topology varies rapidly due to the highly mobile vehicles, which requires a fast resource control mechanism. To cope with these limitations, a distributed and scalable radio resource management scheme is proposed for mmWave V2V with relays in this paper. This scheme integrates radio resource management into spatial, frequency, and power domains. In spatial domain, ZigZag antenna configuration is utilized to mitigate the interference, which plays a decisive role in the short inter-vehicle distance. In frequency and power domains, two resource blocks are allocated alternately and transmit power is controlled to suppress the interference, which has a decisive impact in the long inter-vehicle distance. Simulation results reveal that the achievable end-to-end (E2E) throughput maintains always higher than the required data rate for all vehicles. Most importantly, it works effectively in scalable mmWave V2V topology.

UAV-based wireless systems, such as wireless relay and remote sensing, have attracted great attentions from academia and industry. To realize them, a high-performance wireless aerial communication system, which bridges UAVs and ground stations, is one of the key enablers. However, there are still issues hindering its development, such as the severe co-channel interference among UAVs, and the limited payload/battery-life of UAVs. To address the challenges, we propose an aerial communication system which enables system-level full-duplex communication of multiple UAVs with lower hardware complexities than ideal full-duplex communication systems. In the proposed system, each channel is re-assigned to the uplink and downlink of a pair of UAVs, and each UAV employ a pair of separated channels for its uplink and downlink. The co-channel interference between UAVs that reuse same channels is eliminated by exploiting advantages of UAVs’ maneuverability and high-gain directional antennas equipped in UAVs and ground stations, so that dedicated cancellers are not necessary in the proposed system. The system design and performance analysis are given, and the simulation results well agree with the designs.

As one of the realization for real-time remote monitoring and object recognition using high-definition camera images that can support safe and automated driving, this paper proposes image size reduction by differentiation from the background, focusing on fixedly installed cameras at Road-Side Unit (RSU). The video images acquired by the camera installed on RSU are transferred to the edge server, and information related to the traffic situation is recognized by image processing. Since it requires high-capacity transmission, the use of the millimeter-wave band having large bandwidth available is essential. Meanwhile, a multi-hop relay is desirable due to its short coverage. In this case, a multi-hop relay should support video image traffic from multiple RSU nodes and hence it accumulates the transmission latency. The proposed scheme greatly reduces the size of the image that needs to be transmitted, while maintaining object (vehicle) detection accuracy.

The 5th generation (5G) mobile communication system has started to provide services in many countries. The millimeter-wave (mmW) and beamforming are emerging technologies therein to support ultra-high communication speed. To combat the limited coverage and blocking problem of mmW, deploying relay stations (RS, a.k.a repeaters) is a promising solution for a reliable and efficient service area. However, the design of service areas, or more specifically, the deployment of RS requires a detailed understanding of the propagation environment. This paper proposes a novel digital twin architecture that can reproduce the real-time propagation environment in virtual space to support the dynamic placement of the RSs. As an initial study, we carried out high-precision propagation measurements in the Beyond 5G R&D Proof-of-Concept field in Ookayama Campus of Tokyo Institute of Technology and investigated RS deployment challenges.

For the purpose of establishing a digital twin society, this paper proposes an object recognition network architecture using high-definition (HD) camera images. HD camera is installed to the edge computing resource in Road-Side Unit (RSU). The edge computing resource detects vehicles by object detection and Re-ID function based on deep learning. Its key feature is to reduce the amount of network data traffic by extracting vehicle images and directly transferring them to neighboring RSUs, i.e. vehicle identification and tracking can be achieved in the localized backhaul network. This paper experimentally verifies its fundamental feasibility using outdoor testbed field. The proposed framework can significantly reduce the data traffic by more than 90% while maintaining vehicle Re-ID accuracy.

3G and 4G mobile services have become widespread in our lifecycle, and expectations for a better quality of throughput/latency experience are being placed to 5G era. In recent two years, 5G pilot services have been launched to deal with the drastic increase in mobile devices and application types. However, since 5G adopts a higher frequency than conventional 3G/4G, base stations must be densified. Therefore, virtualization resources for softwarization in various technologies (e.g., Virtualized RAN (Radio Access Network), Virtualized Core, Virtualized Applications) are more appreciated. In this research, we focus on edge computing, which is one of the cores of Beyond 5G, to utilize the virtualization resources. Critical potentials of edge computing are traffic reduction, low latency, and high security for mobile networks. However, various studies were made based only on numerical analysis or parts of the trial of the experiment due to a lack of technical preparation for end-to-end (E2E) environments (e.g., devices, RAN, Core, applications, human resources) with software/hardware flexibility. To show the state-of-the-art edge computing for Beyond 5G (B5G), we established a true E2E B5G Edge Cloud in Ookayama Campus of Tokyo Institute of Technology, Japan. In addition, focusing on the effective use of computation resources in Edge Clouds as an advantage of edge computing, we proposed a cloud-native with network function deployment architecture for computation resource sharing in different Edge Clouds. Specifically, we focused on Virtualized CU (Central Unit) in RAN and proposed to operate CU-CP (Control Plane) and CU-UP (User Plane) in different Edge Cloud. Its feasibility is validated through a measurement.

The development of automated driving is actively progressing, and many countries have carried out field tests and showed its navigation system. In spite that navigation algorithm is one of the important factors affecting automated driving, obtaining rich information from sensor data also plays a key role because the accuracy of navigation algorithms highly depends on sensor data. Typically when a vehicle drives in an urban area, the sensor view of the ego vehicle is usually blocked, which leads to blind angle and potential accidents. Cooperative perception is one of the most promising solutions to obtain rich information sensor data even in a complex traffic environment with blocked views. In this paper, we analyzed the required sensor data rate to pass through an intersection safely with the help of cooperative perception and compared it with the outage capacity realized by conventional V2I bands and millimeter-wave bands. Finally, we derived the maximum velocity that ensured no collision under multiple target vehicles at each carrier frequency.

This paper proposes a framework of blind-spot visualization to see through obstacle via augmented reality (AR) glasses for safe driving enabled by millimeter-wave vehicle-to-everything (V2X) communications. Cooperative perception is known as promising technology to realize safe (automated-) driving where the driver can make immediate and accurate decisions by widely collecting information on the surrounding traffic environment. It is realized by extended sensors such as high-definition cameras and light detection and ranging (LiDAR) to be installed in road-side units (RSUs) all over the place. Camera and LiDAR sensor data of the blind-spot are transferred from RSU to the vehicle, and these sensor fusion data are created as the colored three-dimensional point cloud. It is then projected on the AR glasses. The key feature of our proposal is to provide blind-spot information as a realistic view so that drivers can recognize it without having to look at other display devices. Our initial implementation presents its feasibility through indoor and outdoor trials.

Augmented reality (AR) has drawn great attention in recent years. However, current AR devices have drawbacks, e.g., weak computation ability and large power consumption. To solve the problem, mobile edge computing (MEC) can be introduced as a key technology to offload data and computation from AR devices to MEC servers via 5th Generation Mobile Communication Technology (5G) networks. To this end, a context-based MEC platform for AR services in 5G networks is proposed in this paper. On the platform, MEC is employed as a data processing center while AR devices are simplified as universal input/output devices, which overcomes their limitations and achieves better user experience. Moreover, the proof-of-concept (PoC) hardware prototype of the platform, and two typical use cases providing AR services of navigation and face recognition respectively are implemented to demonstrate the feasibility and effectiveness of the platform. Finally, the performance of the platform is also numerically evaluated, and the results validate the system design and agree well with the design expectations.

Drones are attracting increasing attention in varieties of research fields because of their flexibility and are expected to be applied to a wide range of potential applications, among which the super-high-resolution video surveillance system using drones especially gains the authors' research attention. Surveillance systems using cameras with fixed locations always suffer the blind spots due to the blockage or inappropriate deployments. Instead, by using the drones equipped with cameras, the surveillance performance can be drastically improved due to their high mobilities. The video quality is also a key factor of the surveillance performance. In face recognition, one of the most important surveillance applications, the uncompressed video can greatly improve the detection accuracy, but it is difficult to transmit uncompressed video in real time due to the huge data sizes. To address the issue, we propose to use the ultra-high speed mmWave communication for the video transmission from drones. Moreover, due to the limited battery energy and computing power in drones, we introduce the edge computing and propose to offload all the computation from the drones to the ground station. In addition, a proof-of-concept prototype hardware of the proposed uncompressed 4K video transmission system from drones through mmWave is developed, and the experiments results are consistent with the system design expectations.

In a high-density hotspot that occurs temporarily, the data rate per user is significantly reduced. In addition, if the base station stops working in the disaster area, it is necessary to provide wireless infrastructure promptly. To address in these situations, we focus on a UAV (Unmanned Aerial Vehicle) with wireless communication infrastructure to provide services. Moreover, for access links in UAV, it will be installed with mmWave interface to achieve high-speed throughput and line- of-sight environment could be guaranteed. However, under limited frequency bandwidth, when multiple UAVs are deployed, frequency interference will occur between UAVs, and the data rate will be deteriorated. To reduce the interference between neighboring UAVs, in this paper, we propose a combined method with placement and frequency division under the multiple UAVs environment. Hence, it turns out that the data rate is improved by proposal method under interference environment.

Millimeter wave (mmWave) has great potential to be used for Vehicle-to-Vehicle (V2V) communications due to the characteristics of ultra-high throughput and ultra-low latency. Besides, one mmWave channel can be reused in all V2V links since it is easily blocked by surrounding obstacles, which highly improves the spectrum efficiency. However, links with reflected interference still exist that degrade the throughput of mmWave V2V communications, even though the direct interference link can not penetrate vehicle bodies. To mitigate this negative effect, in this paper, we firstly analyze the channel model of mmWave V2V under interference from ground and surrounding reflections. In order to maintain a higher practical throughput than the required data rate (1 Gbps), a new method of ZigZag antenna configuration is proposed. Secondly, via simulation, the antenna height is optimized under ZigZag antenna configuration. At the optimal antenna height, throughputs of mmWave V2V communications with/without ZigZag antenna configuration are fully compared with non-equal inter-vehicle distance at 60 GHz, where the ZigZag antenna configuration significantly suppresses the destructive interference. Finally, the effectiveness of ZigZag antenna configuration is proved by outdoor experiments.

Recently, since mobile traffic increases rapidly, 5G network is required to support enhanced mobile broadband (eMBB) communications. Self-backhauling mm Wave overlay heterogeneous network is proposed to realize eMBB at low cost. However, intra-channel interferences among mm Wave backhaul links become an issue. This work proposes solutions to this problem through several approaches including proper deployment of mmWave access point, orthogonal channel allocation when necessary, and finally optimal power transmission allocation for alleviating bottleneck of the mesh backhaul networks. Ray-tracing based simulation result shows that the proposed algorithm can cope with bottleneck of the backhaul networks through the effects of the employed interference management schemes.

Conventional wisdom to enhance driving safety of automated vehicles focuses on the massive deployments of intelligent sensors, which generate enormous amount of data. As the solution of 5G era, creating a highly connected vehicular network is considered more reliable to guarantee the driving safety because single vehicle is prone to estimation error with blocked vision. Millimeter- wave, which is one of the key enablers of 5G, is promising to provide multi-gigabit ultra-high data rate and millisecond-level ultra-low latency data transmission. At the same time, software defined networking (SDN), which has proved its ability of dynamic resource management in wired networks, attracts us to extend its advantages into the vehicular environment. In this paper, we enumerate the benefits of mmWave and SDN on the vehicular network. In order to highlight their benefit on driving safety, we propose an architecture of SDN- based mmWave V2X network for HD dynamic map reception and distribution, i.e., cooperative perception. In addition, a proof-of-concept (PoC) is practically conducted in an outdoor environment to validate the performances of the proposed system.

In recent years, the demand for further expansion of the capacity of wireless communication is increasing due to the drastic growth in the number of connected devices and the emergence of various services and applications utilizing wireless networks. It is necessary to decrease the traffic on the backhaul networks and reduce the end- to-end (E2E) latency. In order to address the problems, Multi-Access Edge Computing (MEC) where services, computing resource, storage, etc., would be deployed at the edge of the network is proposed. However, it is difficult for the operators to determine if and how MEC should be deployed in cellular networks because it is still unclear whether a return on investment of MEC could be obtained. In order to deploy MEC on the cellular network, to the best of authors knowledge, no research has been conducted on whether a business model can be established when additional funds are paid for MEC. In this paper, we propose a more sophisticated business model with an ecosystem for MEC deployment. This paper investigates E2E latency and analyzes the optimal MEC resource deployment in the cellular network, and the numerical results verify our analysis. The analysis results reveal that the profit for telecom operator’s revenue tended to increase with the addition of MECs, and the optimal number of MEC maximizing the profit is a function of MEC resource cost and application requirements.

The combination of automated driving based on onboard sensors and decisions and external interactions with the environments through wireless communication has great advantages over the conventional driving systems in terms of safety and reliability. High resolution dynamic maps, which contain the real time information of the driving environment obtained by the collection and fusion of external sensors, can improve the driving safety and reliability dramatically thanks to the additional information beyond the perceptions of the onboard sensors. In this paper, we analyzed the required amount of dynamic information to be exchanged for the cooperative perception in order to enable a new level of safe and reliable automated driving. The results confirm the indispensability of millimeter-wave communications in automated driving systems. In this paper, we focus on an analysis of the required amount of the dynamic information exchange from cooperative sensor perception to enable a new level of safe and automated driving. The results show the necessity of millimeter wave communications for automated driving systems.

Recently, high-density deployment of mmWave small cell base stations has been focused as a means to cope with the rapidly increasing mobile data traffic. MmWave overlay heterogeneous network (HetNet) is proposed to realize eMBB, however laying cost of backbone utilizing high-capacity optical fibers is very costly to support ultra- broadband accesses. On the other hand, Multi- access Edge Computing (MEC) is proposed to reduce mobile data traffic on backhaul networks. MEC deploys contents requested by User Equipment (UE) nearby in advance based on registered context information e.g. location, destination, and required contents to the orchestrator. Therefore, it is possible to utilize mmWave access under existing backhaul networks by introducing prefetching algorithm. The architecture is enabled by wireless Software Defined Network (SDN) technology. In this paper, Proof-of-Concept (PoC) architecture is proposed, and the effectiveness of mmWave HetNet with MEC utilizing prefetching algorithm is confirmed by measuring the download time of real content.

Future mobile data traffic predictions expect a significant increase in user data traffic, requiring new forms of mobile network infrastructures. Fifth generation (5G) communication standards propose the densification of small cell access base stations (BSs) in order to provide multigigabit and low latency connectivity. This densification requires a high capacity backhaul network. Using optical links to connect all the small cells is economically not feasible for large scale radio access networks where multiple BSs are deployed. A wireless backhaul formed by a mesh of millimeter-wave (mmWave) links is an attractive mobile backhaul solution, as flexible wireless (multihop) paths can be formed to interconnect all the access BSs. Moreover, a wireless backhaul allows the dynamic reconfiguration of the backhaul topology to match varying traffic demands or adaptively power on/off small cells for green backhaul operation. However, conducting and precisely controlling reconfiguration experiments over real mmWave multihop networks is a challenging task. In this paper, we develop a Software-Defined Networking (SDN) based approach to enable such a dynamic backhaul reconfiguration and use real-world mmWave equipment to setup a SDN-enabled mmWave testbed to conduct various reconfiguration experiments. In our approach, the SDN control plane is not only responsible for configuring the forwarding plane but also for the link configuration, antenna alignment, and adaptive mesh node power on/off operations. We implement the SDN-based reconfiguration operations in a testbed with four nodes, each equipped with multiple mmWave interfaces that can be mechanically steered to connect to different neighbors. We evaluate the impact of various reconfiguration operations on existing user traffic using a set of extensive testbed measurements. Moreover, we measure the impact of the channel assignment on existing traffic, showing that a setup with an optimal channel assignment between the mesh links can result in a 44% throughput increase, when compared to a suboptimal configuration.

In recent years, ultra-broadband communication using densification of millimeter-wave (mmWave) smallcells has attracted attention owing to its ability to accommodate increasing mobile data traffic. To make full use of mmWave access, we need to deploy ultra-broadband backhauling lines such as 10Gbps Ethernet everywhere at the expense of very high installation costs. The mmWave Edge Cloud system proposed in this paper is a solution to this problem. Based on achievable user context information e.g. mobility and traffic demand, user data can be transmitted and stored in storage (prefetching) installed at the smallcell site in advance. By using this, mmWave access can bring out sufficient performance even with low-capacity backhaul. For the analysis, we have developed a new mobility model, traffic model, and prefetching algorithm. Numerical results showed that the proposed method with 1Gbps-backhaul and prefetching can achieve 95% of the ideal system rate while reduce the average access latency by a factor of 67% as compared to the case without prefetching.

This paper focuses on analyzing some key business aspects that arise during the deployment of key novel enabling technologies for 5G systems. Results are taken out of two EU-funded ongoing research projects, namely 5G-MiEdge and Superfluidity, which largely exploit mmWave communications and softwarization concepts for 5G networks. We initially provide a stakeholder analysis of the 5G ecosystem, as well as a Strengths Weaknesses Opportunities Threats (SWOT) analysis of a couple of key and most promising 5G use cases. For one use case also a preliminary business model is provided. Then we detail an economic 5G cost model, which is able to provide indications on the profitability of 5G networks. Finally, we highlight the planned future works.

Although Wireless Gigabit (WiGig) access operating in the 60 GHz band plays a significant role towards multi-Gbps WLANs, its transmission suffers from harsh propagation loss and path blocking reducing its transmission range to be few meters around a WiGig access point/station (AP/STA). Consequently, directional transmissions using antenna beamforming is tremendously used in WiGig communication. In this paper, a novel approach of leveraging Wi-Fi channel fingerprints for localizing WiGig coverage area along with reducing its beamforming training (BT) complexity over conventional exhaustive search BT is proposed. The proposed approach is motivated by the fact that Wi-Fi fingerprints, WiGig coverage area and the best beam identifications (IDs) of a WiGig AP and STA are all location dependent. Hence, by linking Wi-Fi fingerprints with WiGig information, e.g., WiGig coverage and the best AP/STA beam IDs, using statistical learning, Wi-Fi fingerprints comparisons can be used to detect if a WiGig STA is within the coverage area of a WiGig AP or not and which AP/STA beam IDs are expected to maximize the link quality. Experimental work in real indoor environment is conducted to prove the effectiveness of the proposed approach compared to the conventional exhaustive search BT.

Wireless Gigabit (WiGig) access points (APs) using 60 GHz unlicensed frequency band are considered as key enablers for future Gbps WLANs. Due to its short range transmission with high susceptibility to path blocking, a multiple number of WiGig APs should be installed to fully cover a typical target environment. However, using autonomously operated WiGig APs with IEEE 802.11ad DCF, the exhaustive search analog beamforming and the maximum received power based autonomous users association prevent the establishment of optimal WiGig concurrent links that maximize the total system throughput in random access scenarios. In this paper, we formulate the problem of WiGig concurrent transmissions in random access scenarios as an optimization problem, then we propose a Wi-Fi/WiGig coordination architecture to solve it. The proposed coordinated Wi-Fi/WiGig WLAN is based on a tight coordination between the 5 GHz (Wi-Fi) and the 60 GHz (WiGig) unlicensed frequency bands. By which, the wide coverage Wi-Fi band controls the establishment of the WiGig concurrent links. Statistical learning using Wi-Fi fingerprinting is used for estimating the best candidate AP and its best beam identification (ID) for establishing the WiGig concurrent link without making any interference to the existing WiGig data links.

5G communication networks will bring enhanced mobile broadband services to users and vertical markets supporting very wide range requirements from context-dependent applications. To support such applications in 5G, not only the conventional area traffic capacity but network energy efficiency is also a critical factor since energy consumption of information processing is also becoming an economic issue for operators. Dealing with this problem, our project considers a C-RAN based cloud cooperated HetNet architecture which enables global resource optimization among smallcells to maximize objective functions of interest e.g. energy efficiency. On the other hand, a dynamic traffic model based on that the network can dynamically adapt to the variation in a cost-effective way is also crucial for the design of 5G. This paper develops such traffic model based on realistic measurement data in metropolitan Tokyo. Based on the developed model, a on-demand cell activation / deactivation jointly with user association mechanism is applied to maximize the network's energy efficiency defined as the system rate over the total consumed energy. Numerical results show the effectiveness of the proposed algorithm against dynamic variation of hourly traffic while improving users' satisfaction as compared to conventional homogeneous network. The paper also confirms the superiority of mm-wave smallcell HetNet against conventional microwave HetNet in terms of energy efficiency in bps/W.

Wireless Gigabit (WiGig) access points (APs) using the 60 GHz unlicensed frequency band are considered as key enablers for future Gbps wireless local area networks (WLANs). Exhaustive search analog beamforming (BF) is mainly used with WiGig transmissions to overcome channel propagation loss and accomplish data transmissions. Due to its short range transmission with high susceptibility to path blocking, a multiple number of WiGig APs should be installed to fully cover a typical target environment. Therefore, coordination among the installed APs is highly needed for enabling WiGig concurrent transmissions while overcoming packet collisions and reducing interference, which highly increases the total throughput of WiGig WLANs. In this paper, we propose a comprehensive architecture for coordinated WiGig WLANs. The proposed WiGig WLAN is based on a tight coordination between the 5 GHz (WiFi) and the 60 GHz (WiGig) unlicensed frequency bands. By which, the wide coverage WiFi band is used to do the signaling required for organizing WiGig concurrent data transmissions using control/user (C/U) plane splitting. To reduce the interference to existing WiGig data links while doing BF, a novel location based BF mechanism is also proposed based on WiFi fingerprinting.

The mobile traffic explosion predicted to be increased by 1000 times in the next 10 years has become a remarkable issue due to the proliferation of smart devices such as smart phones or tablets. Energy consumption of information processing is also becoming an economic issue for operators. It is a critical task to design the next generation cellular networks (5G) to be both spectral/energy efficient. This paper considers a future C-RAN based cloud cooperated HetNet which enables global resource optimization among smallcells. The architecture allows optimal user association for data offloading as well as dynamic ON/OFF of smallcell BSs in adaptation to daily data traffic. A joint optimization on both user association and dynamic ON/OFF scheme of BSs to maximizing the system rate over consumed energy of the network investigated in the paper reveals that without sacrificing the system's power resource, our proposed approach can effectively deactivate unnecessary BSs and attain the target 1000× system rate gain in the case of mm-wave smallcells.

Increasing wireless cellular networks capacity is one of the major challenges for the coming years, especially if we consider the annual doubling of mobile user traffic. Towards that and thanks to the fact that a significant amount of mobile data is indeed delay tolerable, in this paper, we suggest embedding the delayed offloading of some user traffic to be a part of future wireless cellular networks. To accomplish this, user delayed files will be offloaded using ultra-high speed Millimeter Wave (Mm-W) gates. The Mm-W gate, which will be distributed inside the Macro basestation (BS) area, consists of number of Mm-W Access Points (APs) controlled by a local coordinator installed inside the gate. To effectively manage the delayed offloading mechanism, utilizing the concept of User/Control (U/C) data splitting, the gates coordinators and the Macro BS are connected to the Cloud Radio Access Network (C-RAN) through optical fiber links. Also, files offloading organizer software is used by the User Equipment (UE). A novel weighted proportional fairness (WPF) user scheduling algorithm is proposed to maximize the Gate Offloading Efficiency (GOFE) with maintaining long term fairness among the different mobility users pass through the gate. If the gate is properly designed and the files delay deadlines are properly set; near 100% GOFE with average reduction of 99.7% in UE energy consumption can be obtained, in time the user just passes through the gate.

In traditional heterogeneous cellular networks (Het-Net), base stations (BS) basically associate users based on received signal power. However, in the case of multiband HetNet, in which macro BSs and smallcell BSs use different frequency bands, this conventional cell association method is not effective because there is no interference between macro BSs and smallcell BSs. Additionally, there are huge differences in coverage and available bandwidth. These differences cause inefficient association which causes the imbalance between achievable rate and traffic demand. In order to overcome this problem, we propose a novel cell association method based on the combinatorial optimization. The proposed method considers achievable rates, traffic demands and the number of users belonging to each BSs simultaneously. Numerical simulation results show that the proposed association method achieves system rate gain twice as high as the conventional one.

The millimeter-wave frequency bands, especially the license free band at 60 GHz, is a candidate for future broadband access links. Path loss measurements have been performed in a typical small cell access scenario. Path loss model parameters were derived for these results, including large and small scale effects. Using this model a system level analysis was performed to evaluate the performance of a heterogeneous network using millimeter-wave access links.

Spatial spectrum sharing with MIMO cognitive radio is efficient and attractive for wireless systems with limited communication resources. MIMO cognitive radio is a kind of cognitive radios using MIMO beamforming techniques to avoid interference to other nodes. There are many theoretical works on this topic but validation of the algorithm on real hardware has not been realized. Most of these works assume perfect CSI though it is always obtained with errors in practice, especially CSIT. It is known that MIMO beamforming techniques are sensitive to CSI errors and their performance might severely be degraded in practice. Despite the fact that cognitive radio with MIMO beamforming techniques is powerful in terms of spatial efficiency as shown by theoretical results, the feasibility of such systems in real environment have never been studied before. Therefore, we attempt to provide the first implementation of a MIMO cognitive radio system using Tx/Rx beamforming and prove the feasibility by measuring its throughput performance. In this paper, we will explain our implementation and measurement results. In the measurement, we measure achievable throughput of both primary and secondary system. As a result, we found that this system works effectively when transmit power of primary nodes is large enough while that of the secondary nodes is relatively small.

This paper presents an indoor experiment to verify the battery-less sensor activation via multi-point wireless energy transmission with carrier shift diversity which realizes seamless coverage extension of the sensor activation. The multi-point scheme is employed to overcome path-loss attenuation. The carrier shift diversity has been developed to achieve uniform coverage of power transmission by combating standing-wave problem caused by multi-point transmitters as well as multipath waves, while its effectiveness on activation of battery-less sensors has never been studied in real environments. In this paper, we develop prototype hardware of battery-less sensor and conduct an indoor experiment with the developed sensor node. The experimental results show that the coverage of single-point and simple multi-point wireless energy transmission are limited at 44% and 70% respectively, while that of the proposed multi-point wireless energy transmission with carrier shift diversity achieves 100% to activate the developed sensor node which consumes -4 dBm for a transmission period of 1s.

Relay deployment has been gaining attention for network designers. Recently, MIMO Two-way Multi-hop Network (M2WMN) where all links share the same frequency is introduced as a relaying scheme which achieves higher spectral efficiency than other conventional multi-hop schemes. A power control strategy for M2WMN has been proposed to alleviate the frequency-sharing interference problem which degrades the scheme's performance. However, for ease of analysis, the past studies on M2WMN just theoretically assumed Rayleigh fading model for all links of the network. This assumption is far from reality where the channels of different links might experience different pathloss conditions including shadowing. This paper conducts 3D ray-tracing simulation in a U-shaped corridor environment to attain practical propagation channels. Based on the channel data, this paper studies the performance of different multi-hop schemes and investigates an open problem of choosing optimal relay placement which can maximize the performance of M2WMN in real environments. Our results show that without power control, the optimal locations are where adjacent nodes are both in Line-of-Sight (LOS). Interestingly, the optimal locations are no more LOS environments when power control is applied. In addition, this paper also proposes a sub-optimal relay placement search algorithm relaxing the complexity of exhaustive search.

This work analyzes the optimal pico base station (BS) deployment in heterogeneous cellular networks (HetNet) with hotspots. Most of conventional works for HetNet focused on interference coordination and effective cell association methods, however, the problem of pico BS deployment (cell planning) for HetNet with hotspots has not been analyzed so much. In this paper, we extend the previously proposed optimization problem in terms of network parameters (spectrum splitting ratio and SINR bias value) to the optimal pico BS locations to maximize the system rate. Furthermore, the average user and outage user rates are evaluated numerically to show the effectiveness of the proposed optimization method. Numerical results show that the optimized pico BS locations can improve both the average and outage user rates in HetNet with hotspots.

MIMO 2-way relay network is known as a solution to realize high data rate relay networks. 2-way relaying is possible provided that interference cancellation techniques, e.g. MIMO beamforming or network coding are properly introduced. Many theoretical works on relaying using beamforming exist, but no implementation on real hardware has been reported. These works try to maximize the throughput and the relay node is not allowed to be a data source. Such relaying schemes are not suitable for our targeting networks, e.g. smart utility networks, sensor networks, etc. We implement a simple beamforming scheme that allows the relay node to be a data source. Moreover, most theoretical works assume perfect CSIT without consideration on implementation. We employ RF calibration to obtain CSIT. We evaluate the accuracy of the calibration using the channels measured in real environment, and the result confirms the validity of the method. We also present a demonstration system to show the flexibility of the implemented scheme.

In recent years, wireless mesh network functioning as backbone for other sensor network applications has been attracting much of attention. For realization of a high data rate and reliable mesh network, a synchronized mesh network technology employing OFDM as a block processing scheme has been proposed. However, the conventional scheme is not convenient as it requires network synchronization of all the nodes in the network done before starting data communication. This paper proposes a novel scalable network synchronization scheme where data transmission and network synchronization setup can be done simultaneously. The proposed algorithm is implemented in the developed 950MHz TDD MIMO two-way network prototype hardware, and its behavior is verified.

Deployment of relay nodes can enhance the coverage of wireless network in shadowing environments. Recently, MIMO Two-way Multi-hop Network (MTMN) has been introduced as a communication scheme to improve channel capacity of relay networks. Moreover, the strategy of Power Adaptation (PA) has been proposed for MTMN to adjust the Signal-to-Interference plus Noise Ratio (SINR) to achieve the highest performance. However, the studies of MTMN has been based on Rayleigh fading channel model which may be far from the reality since all links in the network are not in the same condition, especially when shadowing is dominant. Moreover, the realization of optimum placements in MTMN for relays in the real shadowing environment is still a left-behind issue. Therefore, this paper aims to investigate the optimum relay placements of MTMN by conducting 3D ray-tracing simulation of propagation channel in a real shadowing environment. Based on the results, the optimum relay placements of MTMN without PA are where relay links do not suffer from shadowing effect. On the contrary, the results show that the optimum placements for MTMN with PA case is different since PA can more efficiently reduce the interference at these locations. In addition, this paper proposed a methodology to estimate the optimum locations for MTMN with PA by using the knowledge of node-to-node signal strength which can be simply obtained in the real environment.

We investigate the joint optimization of power allocation and transceiver weights in multiple-input multiple-output(MIMO) two-way multihop networks. The objective is to maximize the minimum weighted signal-to-interference-plus noise power ratio (SINR) of the multihop links while satisfying general linear power constraints at the transmit nodes. First, we derive a distributed power allocation algorithm by extending the notion of link SINR metric and analyze its convergence and optimality. Using that result, we propose an alternating optimization algorithm for solving the more complex MIMO transceiver weights optimization. We compare its performance against those of centralized and conventional schemes through numerical simulations. Our results show that the proposed algorithm provides considerable improvement to the end-to-end rate of multihop networks. In fact, it achieves, with low complexity and low coordination overhead, a rate performance close to an upper-bound that was obtained from a centralized optimization with a relaxed power constraint.

In this paper, we describe a design method of a spatial fading emulator based on Clarke's model which is one of OTA (Over-The-Air) measurement systems for creating an artificial propagation environment for evaluation of multi-antenna handsets. The emulator is composed of scatterers located at equal angle intervals on a circle around the handset. For evaluating multi-antenna systems such as MIMO, OTA systems should generate multi-path propagation environment where spatial correlation is correctly realized. Spatial fading emulator based on Clarke's model with limited number of scatterers can generate the propagation environment inside a quiet zone where spatial correlation is correctly realized around the center of emulator. In this paper, we show that the size of quiet zone is derived by the Bessel function with the order of the number of scatterers. Furthermore, we show the variation of the size of quiet zone against the offset angle of test antennas. Finally, an equation for obtaining the required number of scatterers that satisfies required size of quiet zone is presented.

Base Station Cooperation (BSC) is one of the key technologies for next generation cellular systems. The BSC can improve channel capacity at the cell-edge unlike conventional single cell transmission. In this paper, we will study about beam tilt angle of base station antennas for the BSC systems. In conventional systems, beam tilt angle is designed to maximize the power of its own cell while minimizing the power from adjacent cells to reduce Inter-Cell Interference (ICI). Unfortunately, performance at the cell-edge cannot be improved since Signal-to-Interference Ratio (SIR) is unchanged regardless of the beam tilt angle. However, since the problem of ICI is removed in the BSC system, beam tilt angle is required to be designed differently from the conventional way. In this paper, we will derive optimal beam tilt angle for the BSC systems based on these considerations. For that purpose, an objective function to maximize average channel capacity of cooperative cell is defined, and the optimal beam tilt angle is derived by solving the problem. By numerical analysis, it is shown that the optimal beam tilt angle for the BSC system is smaller than that of the single cell transmission. By using the optimal base station antennas, channel capacity of the BSC system is greatly improved, especially at the cell-edge.

Sensor node life-time limitation in wireless sensor networks has long become an issue, preventing it to become a reliable ubiquitous network. In this paper, a new concept called wireless grid, which includes a fusion of wireless sensor network and wireless power transmission is introduced. By doing this, battery life-time problem can be avoided, hence, providing high network reliability. Wireless power transmission scheme adjusted to the sensor network operating environment is proposed to satisfy power requirement at the sensor nodes. Simulation results show that by using the proposed schemes, two power transmission nodes can supply the energy required for sensor nodes operating in a square room of 25m2with 99% reliability.

We propose a new cross-layer approach to mitigate interference in multihop networks. Precisely, we cancel all adjacent node interference in a multihop path by MIMO two-way relay scheme and jointly optimize the routing and power allocation to mitigate the interference from far nodes. We model and efficiently solve this optimization problem using a geometric programming framework. Our simulation results showed that this cross-layer approach provided significant end-to-end capacity gain and outperformed conventional multihop schemes. Also, a number of hops ranging from 2 to 6 was optimal in interference-limited regime. Finally, single hop MIMO routing was shown to provide higher capacity only in very high SNR scenarios.

Base station cooperation (BSC) has been identified as a key radio access technology for next-generation cellular networks such as LTE-Advanced. BSC maximizes its gains over non-cooperation (NC) in a network wherein interference from cooperating BSs is the main limitation. However, at locations where the signals from non-cooperating BSs are the dominant interference, the gains are minimal. Therefore, for every user equipment, the set of cooperating BSs must be properly selected in order to achieve the potential gains of BSC in a cellular network. In this paper, various BSC cluster types and cell regions are introduced, and the impact of dynamic clustering on BSC spectral efficiency is discussed. It is shown that to maximize the spectral efficiency gains of BSC multi-user MIMO to a UE, the BSs which induce the strongest received signal powers must be selected for cooperation. Simulation results show that by performing dynamic clustering, the geographical area at which BSC achieves better spectral efficiency over NC can be significantly increased over that of static clustering.

Shadowing effect caused by obstacles between transmitter and receiver always weakens the signal in wireless communications. Relay technique is proposed as a solution to the problem of shadowing. Various relaying schemes have been proposed in recent literature. However, in most of the works, performance of relaying schemes were evaluated using theoretical channel models which may be far from realistic environment. In this paper, performance of various relaying schemes are assessed by using real propagation data in a shadowing environment. MIMO wideband propagation measurements are performed in an L-shaped corridor with various positions of relay node. Using measurement data, capacity performance of well-known relaying schemes including decode-and-forward, cooperative relay and two-way relay employing network coding are evaluated. Analysis results show the benefits of relay technique against shadowing effect in a real environment as well as give directions about an optimal location to place the relay node. Furthermore, by comparing performance of different relaying schemes, the paper finds that two-way relay employing network coding has superior performance while the introduction of cooperative relay in an environment, where signal strength of direct link is extremely weak, is not efficient.

This paper develops the first prototype hardware for TDD/TDMA two-way multi-hop relay network with MIMO network coding. Since conventional wireless multi-hop relay networks have drawbacks of low data rate, TDD/TDMA two-way multi-hop relay networks have been studied as a solution to realize high data rate recently. In these networks, forward and backward streams are spatially multiplexed by using interference cancellation technology such as MIMO beamforming or MIMO network coding. In this prototype hardware, MIMO network coding and network synchronization scheme are implemented to realize such TDD/TDMA two-way multi-hop relay network in real environment. In the demonstrator using the prototype hardware, each transmitter and each receiver performs network coded broadcast (BC) and MIMO multiple access (MA) respectively. Performance of the demonstrator shows that the TDD/TDMA two-way multi-hop relay network with MIMO network coding can be realized.

This paper proposes novel time-efficient network synchronization schemes for TDD/TDMA based two-way multi-hop relay networks with block modulation. One of the proposed schemes is based on broadcast (BC) timing synchronization. Since this scheme causes network synchronization errors at each receiver, additional guard interval (GI) to compensate the error is introduced. The second proposed scheme is based on both of BC and multiple access (MA) timing synchronization. The additional GI is not required and the time-efficiency is improved because the transmit and receive timing at each node are adjusted to eliminate the network synchronization errors. The second proposed scheme achieves over 98.8% time-efficiency with arbitrary node arrangement, bandwidth, and number of hops when the number of symbols per frame is hundred.

In recent years, network coding has been introduced at physical layer to increase network capacity of wireless mesh networks (WMN). In this paper, to support reliable packet relaying in WMN employing network coding, we propose an efficient retransmission scheme. The proposed scheme is efficient since it exploits the property of network coded packet header instead of using conventional schemes based on transmission of acknowledgement (ACK/NAK) packets as shown by analytic results. Benefit of the proposed scheme is furthermore verified in a one dimensional (1D) MIMO two-way relay network employing network coding. Numerical result shows that our proposed scheme can significantly improve end-to-end packet delivery ratio in the presence of lossy wireless links.

Infrastructure wireless mesh network has been attracted much of attention due to a wide range of its application such as public wireless access, sensor network, etc. The application of well-known CSMA/CA based MAC protocols to mesh network, however, reveals high latency and low resource utilization due to problems of hidden terminal, exposed terminal, information asymmetry etc. Several alternative protocols including directional MAC, multichannel MAC only provide marginal improvement. In recent publication, a cross-layer design employing multiple antenna techniques called MIMO two-way relay is proposed for one dimensional mesh network. Owing to interference cancellation and bidirectional stream multiplexing ability of MIMO in combination with an efficient channel access scheme of TDMA/TDD, MIMO two-way relay provides significantly high end-to-end capacity. In this paper, we propose MIMO two-way relay as an alternative PHY/MAC protocol of CSMA/CA. A network simulator employing MIMO two-way relay is developed and more details on packet relaying mechanism of the algorithm are presented. Simulation results show that MIMO two-way relay achieves an extremely large improvement in network throughput, and packet delay reduction in comparison with CSMA/CA mesh networks.

Cooperative transmission (CT) (i.e. base station cooperation, multicell transmission) techniques have been shown to theoretically increase the average and cell-edge spectral efficiencies of cellular networks. These techniques aim to suppress or even take advantage of intercell signals. However, to realize the benefits of CT in actual cellular networks, cell planning parameters must be adjusted accordingly. This paper builds a framework that relates the two fields. It shows how coverage, traffic, handover and intercell-interference evaluation metrics are redefined for CT and how they are unified through the traffic coverage metric to lessen the cell plan optimization criteria. The cell planning framework allows comparison of full CT (or FCT, where all base stations can cooperate), group- wise CT (or GCT, where cooperation is by groups), and non- cooperative transmission (or NCT) designs. A simple network example shows that over NCT, CT permits superior network designs which have higher cell traffic, greater overlap of cell coverage areas and requires less number of base stations to meet the traffic demand. The service advantages of CT however, are offset by the expected higher cost of equipment due to additional complexity. The feasibility of using CT over NCT in a particular service area must therefore be carefully studied before network deployment.

Wireless mesh networks, consist of mesh routers and clients, have attracted researchers in the field of sensor network or wireless plant control for its potential to achieve high connectivity and wide area coverage in an ad-hoc way. The mesh routers should supply the backbone of the network with high capacity to support accumulated traffic from or to mesh clients. In the conventional mesh network it is a biggest problem of inefficient network channel capacity due to multiple access interference among the mesh routers. In this paper we will propose a novel MIMO mesh network, where the mesh routers support multiple antennas, to avoid multiple access interference and to supply higher network capacity via link multiplexing. As a MIMO transmission scheme, linear (such as Zero-Forcing) and nonlinear (such as Dirty Paper Coding / Successive Interference Cancellation) MIMO algorithm are developed for the proposed mesh network. It is found from numerical analysis that the proposed MIMO mesh network achieves extremely higher channel capacity than that of conventional mesh network.

In this paper, an architecture of MIMO mesh network which avoids co-channel interference and supplies link multiplexing simultaneously is proposed. As a MIMO transmission scheme, linear (such as zero-forcing) and nonlinear (such as dirty paper coding and successive interference cancellation) MIMO algorithm are developed for the proposed mesh network. It is found from numerical analysis that the proposed MIMO mesh network achieves extremely higher channel capacity than that of conventional mesh network.

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.

Implementation of RFID reader/writer on software defined radio is studied in this paper. The target RFID is ISO 18000-3 mode 2 which has 8 reply channels for simultaneous communication with 8 different RFID tags. In the software defined radio architecture, the 8 reply channels are sampled at a single A/D converter and separated by digital down converters, whereas conventional RFID architecture has redundant 8 parallel analog down converters. A novel multi-stage transmultiplexing digital down converter is proposed for efficient implementation of multi-channel digital down converter. Moreover the proposed architecture is implemented on a FPGA evaluation board, and validity of the system is confirmed on a real hardware.

As the wireless channel is constantly changing, MIMO-OFDM eigenmode transmission is extremely vulnerable to the presence of feedback delay which is unavoidable in a practical system. Under such imperfect conditions, the inter-eigenmode interference can be removed through the use of the MMSE interference canceller. However, to the best of our knowledge, the performance of MIMO-OFDM eigenmode with MMSE interference canceller has not been proven by experimental results. In this paper, we present experimental results for the bit error rate (BER) performance of MIMO-OFDM eigenmode transmission with and without MMSE interference canceller. In the experiment, a time-varying channel is synthetically generated in a static environment by exploiting the inherent spatial correlation in a static environment. Our experimental results proved the robustness of MIMO-OFDM eigenmode with MMSE interference canceller in the presence of feedback delay

A real-time multiple-input multiple-output (MIMO) channel measurement system was implemented by using a 4times4 MIMO software defined radio (SDR) testbed. A target application of this system is to evaluate realistic performance of closed-loop MIMO transmission in time-varying channels at 5 GHz band. The results of indoor measurements showed that feedback delay of the closed-loop transmission causes severe degradation of channel capacity, and an interference canceller in eigenbeamspace is indispensable in achieving the benefits of channel state information (CSI) feedback

In this paper, throughput performance of MIMO-OFDM system in real residential home environment was evaluated by using wideband MIMO channel measurement data. Computer simulations were carried out to compare the performance of MIMO-OFDM systems with various detection methods, i.e. MMSE, VBLAST, QRM-MLD and SVD-MIMO, in addition to that of the SISO-OFDM system. The results showed that the SVD-MIMO transmission can provide the highest average and outage throughput under the assumption of perfect CSI feedback. On the other hand, QRM-MLD yielded the best performance among the systems without CSI available at the transmitter. It was also found that the outage throughput performance of MMSE and VBLAST degrades severely due to the existence of spatial correlation in the real home environment.

Adaptive MIMO eigenmode transmission system is a promising candidate for future high data rate wireless systems. However under practical conditions when channel state information (CSI) is imperfect, the eigenbeams lose their orthogonality and inter-eigenmode interference occurs. No work so far has attempted to consider the effects of inter-eigenmode interference on the adaptive signaling algorithm which is essential in ensuring a practical and robust adaptive system. Thus in this paper, we will propose an adaptive algorithm that account for CSI imperfections and practical operating conditions explicitly, namely imperfect channel estimation at receiver, delayed quantized feedback to transmitter and a spatially correlated continuous fading channel. A metric for the SINR of each eigenmode under the above practical conditions is identified and this metric is used in the adaptive signaling to ensure a robust adaptive algorithm. Both simulation and experimental results showed that the proposed algorithm is robust and superior to conventional schemes under practical operating conditions. Furthermore, a low complexity look up table-based computation method is also devised

An area coverage of 4×4 MIMO-OFDM system was measured in residential home environment at 5GHz band. A novel spatial scanner was fabricated to suit the needs of measurements in environments with household furniture such as beds, sofa and tables. The coverage was calculated based on a total of 55,000 spatial samples in an area of 150m2which includes two rooms, a hallway and living and dining areas. The results shown that the 4×4 MIMO system can greatly increase the area coverage compared to SISO system, especially at high data rate. It was also found that the introduction of optimum power allocation in the MIMO system is effective to increase area boundary with lower data rate.

MIMO communication systems can provide high channel capacity and is considered as a candidate for the next generation wireless systems. However, there is insufficient investigation about effects of the imperfection caused by the RF hardware on the MIMO systems. In this paper, we focus on the influence of the IQ imbalance on a MIMO-OFDM communication system. As a result, it is found that the IQ imbalance causes both inter-subcarrier and inter-stream interferences in the MIMO-OFDM system, and severely degrades the performance of the system. To combat this problem, a new extended channel matrix including the influence of IQ imbalance is introduced. Then the method of IQ imbalance compensation by using the extended channel matrix is proposed in this paper. The validity of the proposed IQ imbalance compensation scheme on the MIMO-OFDM system is investigated by computer simulation.

The paper present the results of a multiple-input multiple-output (MIMO) channel capacity measurement experiment conducted in an indoor line-of-sight (LOS) office environment. Channel responses were taken systematically with varying distance in a static indoor environment. Results showed measurements with high received signal-to-noise ratio (SNR) and a high level of correlation among the antenna elements. Further analysis of the results showed that MIMO systems can be efficient in the indoor LOS office environment, despite the high antenna correlation. Theoretical analysis reveals that when the SNR is sufficiently high, the loss in channel capacity due to high correlation is relatively low. Therefore, it is shown that in the indoor LOS environment, MIMO systems can be achieve sufficiently high channel capacity because the MIMO channel is more robust to correlation when the SNR is high.

Adaptive MIMO eigenmode transmission system is a promising candidate for future high data rate wireless systems. However under practical conditions when channel state information (CSI) is imperfect, the eigenbeams lose their orthogonality and inter-eigenmode interference occurs. No work so far has attempted to consider the effects of inter-eigenmode interference on the adaptive signaling algorithm which is essential in ensuring a practical and robust adaptive system. Thus in this paper, we propose an adaptive algorithm that account for CSI imperfections explicitly. Our results showed that the proposed algorithm is robust and superior to conventional schemes under practical operating conditions. Furthermore, a low complexity look-up table-based computation method is also devised.