Blinq Wireless Inc.

Blinq Networks Inc.

Terasan Niyomsataya

Radu Bogdan Selea

Ho Ting Cheng

Taiwen Tang

Sorin Alexandru Michnea

Akram Bin Sediq

Alexandru Moraru

Ovidiu Mihai Leulescu

Yigit Ozcan

Xiaochang Wu

A system, apparatus and method for installation of outdoor CPE (Customer Premise Equipment) for CBRS (Citizen Broadband Radio Service) for fixed wireless access is disclosed. The system comprises a database server which stores data comprising eNodeB locations and details, pathloss models and throughput prediction data. A position/orientation sensor and WiFi access point are attached to the CPE during installation. For a specified CPE height and a range of pointing angles, a smartphone app is used in scan mode to obtain KPI and evaluate nearby eNodeBs for performance based on stored parameters and link type, to provide estimated UL/DL throughput data for each eNodeB. After selecting an eNodeB, in network entry mode, a RF link between the CPE and eNodeB is established to request SAS grant. If successful in entering operational mode, actual throughput is measured to ensure the desired performance is attained, and data are reported back to the database.

System, apparatus and methods for CBRS CPE installation

A multi-beam antenna system, apparatus and method for dynamic carrier aggregation to multi-beam antenna mapping in radio access networks, including small-cell deployments, is disclosed. Apparatus comprises a compact base transceiver unit with integrated multi-beam antenna comprising antenna groups configurable for operation in a plurality of modes, with one or more selected antenna groups enabled, for different use-case scenarios. The base transceiver unit comprises a daisy-chained radio-frequency (RF) system wherein one baseband processor feeds multiple RF transceivers; each RF transceiver front end comprises a software configurable isolation module through which each RF front end is interlinked to previous and next RF front ends to enable dynamic routing of TX/RX data streams through the daisy chain, e.g. routing a transmission data stream from any RF transceiver to any one of the antenna groups or multiple antenna groups, routing a received data stream from one or multiple antenna groups to any RF transceiver, and for contiguous or non-contiguous carrier aggregation.

System, apparatus and method for dynamic carrier aggregation to multi-beam antenna mapping

Systems and methods are disclosed for networking planning for fixed backhaul networks comprising a plurality of hubs, each serving one or more RBMs. The method comprises one or more of terrain pathloss (PL) and antenna gain prediction; network design comprising site association, hub dimensioning and pointing; and optimization of small cell (SC) deployment. PL prediction is based on correlation of user input parameters with reference use cases for channel models for each of downtown, urban, and suburban deployment scenarios. Rapid and effective network planning is achieved with limited input data, even in the absence of high resolution digital maps or building polygons, by selecting the channel model having a highest correlation with available environmental parameters. Optimization of network topology design, system design, and SC deployment, with both access link and backhaul link evaluation, is based on optimization of a sum-utility function across all links for feasible SC site locations.

Method and system for network planning in fixed wireless backhaul networks

Systems and methods are disclosed for coordinating hub-beam selection in wireless backhaul networks and optionally, for joint hub-beam selection and slot assignment. Data indicative of path loss is measured or estimated for each of a set of RBMs and for each hub-beam of a respective multi-beam serving hub. A performance metric is computed, and hub-beam selection is made based on optimizing the performance metric across the set of RBMs. A serving hub may use reserved frames to train an RBM on each hub-beam and communicate beam selections, e.g. based on minimizing path loss on a per-cell or per-sector basis, or maximizing a sum-utility function for improved performance over a neighborhood of the network. A beam assignment map may be shared amongst serving hubs. A weight table of good and bad beam combinations may be generated to evaluate the cost of a hub-beam combination, for joint hub-beam selection and slot assignment.

System and method for coordinating hub-beam selection in fixed wireless backhaul networks

A system and method of uplink power control in a fixed wireless backhaul network, wherein determining an uplink transmit power of each remote backhaul module (RBM) comprises obtaining an interference-over-thermal (IoT) noise value of each hub, determining a target IoT noise value for each RBM, determining a total path loss from each RBM to its serving hub, determining a target uplink carrier to interference and noise ratio (CINR) for the RBM, and computing the RBM uplink transmit power for each RBM by summing the target IoT noise value for the RBM, the total path loss of the RBM to its serving hub, and the target uplink CINR. Computationally expensive parameter sweeps are avoided. The method can be implemented using a centralized processing unit or distributed processing at each node. The method is self-optimizing, and initial hub and RBM transmit powers and other data may be estimated using pre-deployment tools.

System and method for self-optimized uplink power control in a fixed wireless backhaul network

A system and method for downlink power optimization in a partitioned wireless backhaul network with out-of-neighborhood utility evaluation is disclosed. The method comprises performing initial downlink power optimization for each neighborhood independently, considering only in-neighborhood utilities, by obtaining the transmit powers of all hubs and a utility performance of all served remote backhaul modules (RBMs) in the neighborhood. Power optimization data for each neighborhood are then reported to a central processing unit for storage. Thereafter, for each neighborhood, an out-of-neighborhood utility evaluation is performed by the centralized processing unit, based on reported power optimization data from other neighborhoods, for example, by obtaining delta out-of-neighborhood sum utilities for each hub as a function of hub transmit power, by curve fitting of reported data. Power optimization for each neighborhood is then performed by optimizing both in-neighborhood sum utilities and out-of-neighborhood sum utilities, and hub transmit powers are updated accordingly.

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Ottawa, Canada

Terasan Niyomsataya