5G/B5G mmWave Cellular Networks with MEC Prefetching Based on User Context Information.

To deal with recent increasing mobile traffic, ultra-broadband communication with millimeter-wave (mmWave) has been regarded as a key technology for 5G cellular networks. In a previous study, a mmWave heterogeneous network was composed of several mmWave small cells overlaid on the coverage of a macro cell. However, as seen from the optical fiber penetration rate worldwide, it is difficult to say that backhaul with Gbps order is available everywhere. In the case of using mmWave access under a limited backhaul capacity, it becomes a bottleneck at the backhaul; thus, mmWave access cannot fully demonstrate its potential. On the other hand, the concept of multi-access edge computing (MEC) has been proposed to decrease the response latency compared to cloud computing by deploying storage and computation resources to the user side of mobile networks. This paper introduces MEC into mmWave heterogeneous networks and proposes a content prefetching algorithm to resolve such backhaul issues. Context information, such as the destination, mobility, and traffic tendency, is shared through the macro cell to the prefetch application and data that the users request. Prefetched data is stored in the MEC and then transmitted via mmWave without a backhaul bottleneck. The effectiveness is verified through computer simulations where we implement realistic user mobility as well as traffic and backhauling models. The results show that the proposed framework achieved 95% system capacity even under the constraint of a 1 Gbps backhaul link.

MEC/Cloud Orchestrator to Facilitate Private/Local Beyond 5G with MEC and Proof-of-Concept Implementation.

The emergence of 5G-IoT opens up unprecedented connectivity possibilities for new service use cases and players. Multi-access edge computing (MEC) is a crucial technology and enabler for Beyond 5G, supporting next-generation communications with service guarantees (e.g., ultra-low latency, high security) from an end-to-end (E2E) perspective. On the other hand, one notable advance is the platform that supports virtualization from RAN to applications. Deploying Radio Access Networks (RAN) and MEC, including third-party applications on virtualization platforms, and renting other equipment from legacy telecom operators will make it easier for new telecom operators, called Private/Local Telecom Operators, to join the ecosystem. Our preliminary studies have discussed the ecosystem for private and local telecom operators regarding business potential and revenue and provided numerical results. What remains is how Private/Local Telecom Operators can manage and deploy their MEC applications. In this paper, we designed the architecture for fully virtualized MEC 5G cellular networks with local use cases (e.g., stadiums, campuses). We propose an MEC/Cloud Orchestrator implementation for intelligent deployment selection. In addition, we provide implementation schemes in several cases held by either existing cloud owners or private and local operators. In order to verify the proposal's feasibility, we designed the system level in E2E and constructed a Beyond 5G testbed at the Ookayama Campus of the Tokyo Institute of Technology. Through proof-of-concept in the outdoor field, the proposed system's feasibility is verified by E2E performance evaluation. The verification results prove that the proposed approach can reduce latency and provide a more stable throughput than conventional cloud services.

Distributed and Scalable Radio Resource Management for mmWave V2V Relays towards Safe Automated Driving.

The millimeter-wave (mmWave) Vehicle-to-Vehicle (V2V) communication system has drawn attention as a critical technology to extend the restricted perception of onboard sensors and upgrade the level of vehicular safety that requires a high data rate. However, co-channel inter-link interference presents significant challenges for scalable V2V communications. To overcome such limitations, this paper firstly analyzes the required data rate ensuring maneuver safety via mmWave V2V relays in an overtaking traffic scenario. Based on these preparations, we propose a distributed radio resource management scheme that integrates spatial, frequency, and power domains for two transmission ranges (short/long). In the 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 on interference mitigation in the long inter-vehicle distance. Simulation results reveal that the achievable End-to-End (E2E) throughput maintains consistently higher than the required data rate for all vehicles. Most importantly, it works effectively in scalable mmWave V2V topology.

Dynamic Clustering and Coordinated User Scheduling for Cooperative Interference Cancellation on Ultra-High Density Distributed Antenna Systems.

This paper proposes dynamic clustering and user scheduling for previously conceived inter-cluster interference cancellation scheme on ultra-high density distributed antenna system (UHD-DAS). UHD-DAS is composed of one central unit (CU) and densely deployed remote radio units (RUs) serving as small cell access points. It can enhance spatial spectral efficiency by alleviating traffic load imposed per radio unit; however, intenser small cell deployment revives the inter-cell interference (ICI) problem. Cell clustering, cooperation of multiple RUs, can mitigate ICI partially, whereas inter-cluster interference (ICLI) still limits its possible capacity. Simplified ICLI cancellation based on localized RU cooperation was previously proposed to mitigate interference globally. The resolved issue is that it required frequency reuse distance to fully obtain its interference cancellation ability. This paper introduces dynamic clustering with coordinated user scheduling to ensure reuse distance without extra frequency reuse. Joint dynamic clustering and ICLI cancellation can effectively work and almost reaches ideal performance as full cooperative spatial multiplexing transmission.

Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks.

Round Robin based Intermittent Periodic Transmit (RR-IPT) has been proposed which achieves highly efficient multi-hop relays in multi-hop wireless backhaul networks (MWBN) where relay nodes are 2-dimensionally deployed. This paper newly investigates multi-channel packet scheduling and forwarding scheme for RR-IPT. Downlink traffic is forwarded by RR-IPT via one of the channels, while uplink traffic and part of downlink are accommodated in the other channel. By comparing IPT and carrier sense multiple access with collision avoidance (CSMA/CA) for uplink/downlink packet forwarding channel, IPT is more effective in reducing packet loss rate whereas CSMA/CA is better in terms of system throughput and packet delay improvement.

First Eigenmode Transmission by High Efficient CSI Estimation for Multiuser Massive MIMO Using Millimeter Wave Bands.

Drastic improvements in transmission rate and system capacity are required towards 5th generation mobile communications (5G). One promising approach, utilizing the millimeter wave band for its rich spectrum resources, suffers area coverage shortfalls due to its large propagation loss. Fortunately, massive multiple-input multiple-output (MIMO) can offset this shortfall as well as offer high order spatial multiplexing gain. Multiuser MIMO is also effective in further enhancing system capacity by multiplexing spatially de-correlated users. However, the transmission performance of multiuser MIMO is strongly degraded by channel time variation, which causes inter-user interference since null steering must be performed at the transmitter. This paper first addresses the effectiveness of multiuser massive MIMO transmission that exploits the first eigenmode for each user. In Line-of-Sight (LoS) dominant channel environments, the first eigenmode is chiefly formed by the LoS component, which is highly correlated with user movement. Therefore, the first eigenmode provided by a large antenna array can improve the robustness against the channel time variation. In addition, we propose a simplified beamforming scheme based on high efficient channel state information (CSI) estimation that extracts the LoS component. We also show that this approximate beamforming can achieve throughput performance comparable to that of the rigorous first eigenmode transmission. Our proposed multiuser massive MIMO scheme can open the door for practical millimeter wave communication with enhanced system capacity.