Abstract: Practical methods and apparatuses are provided for determining network clusters in wireless backhaul networks comprising a plurality of hubs (102) and Remote Backhaul Modules (RBM) (104) based on link quality value (LQV) metrics. From an input LQV table of LQV values for each hub-RBM link (110), the link quality values are first ranked. Clusters are then identified from all the possible links based on the order of the highest link quality value to the lowest link quality value, any constraints on the number of RBMs per cluster, and clustering each RBM only once. Links with strong link quality values are chosen to optimize the LQV metric. LQV based clustering achieves a higher average LQV, e.g., average spectrum efficiency or weighted sum spectrum efficiency, for the entire backhaul network compared to the geographic location based clustering. The method is straightforward to implement and has low computational complexity.

Abstract: A method and system is disclosed for managing performance of a wireless backhaul network through power management, which provides a practical approach to balancing data throughput and fairness. For each transmit frame, one or more power zones is defined, each power zone comprising a set of radio resources operating at one transmit power level Pi, and the same power zone being defined over the same set of radio resources across all other clusters. The method maximizes the value of weighted weighted-sum utility, using a rate expression based on a CINR function. The optimization comprises a summation of the weighted logarithm of the rate expression plus a non-negative constant value, using a Newton's method approach, for fast and reliable convergence. Optimization may be based on long term averaged channel gains measured for each link. The value of c is selected to achieve a required balance of fairness and data throughput.

Abstract: Methods are disclosed for scheduling resources in a wireless backhaul network comprising a plurality of N Hubs, each Hub serving a plurality of K Remote Backhaul Modules (RBMs), using a coordinated power zone assignment across the backhaul network. For each Hub, a one-to-one power zone assignment, of each of the K RBM to one of the K power zones, is computed by maximizing a selected network utility across the backhaul network. Coordinated power zone assignment according to preferred embodiments based on the auction approach offers a close-to-global-optimal solution. Coordinated scheduling based on first assigning RBMs to hubs heuristically, and then optimally scheduling RBMs within each hub also offers significant performance improvement as compared to non-coordinated systems. Preferred embodiments offer a significant performance improvement as compared to conventional systems.

Abstract: Methods are disclosed for scheduling resources in a wireless backhaul network comprising a plurality of N Hubs, each Hub serving a plurality of K Remote Backhaul Modules (RBMs), using a coordinated power zone assignment across the backhaul network. For each Hub, a one-to-one power zone assignment, of each of the K RBM to one of the K power zones, is computed by maximizing a selected network utility across the backhaul network. Coordinated power zone assignment according to preferred embodiments based on the auction approach offers a close-to-global-optimal solution. Coordinated scheduling based on first assigning RBMs to hubs heuristically, and then optimally scheduling RBMs within each hub also offers significant performance improvement as compared to non-coordinated systems. Preferred embodiments offer a significant performance improvement as compared to conventional systems.

Abstract: Methods and apparatus are provided for managing interference in a wireless backhaul network comprising a plurality of hubs, each hub serving a plurality of remote backhaul modules (RBM), using power control with a one-power-zone (OPZ) constraint. Each hub uses a transmit frame structure comprising a plurality of zones, each RBM is scheduled on a different zone, and the same power level is maintained across all zones within a transmit frame. Under the OPZ constraint, and for scheduling policies under which the number of zones assigned to each RBM is fixed, the power and scheduling sub-problems are decoupled. This enables power control independent of scheduling, using methods having lower computational complexity. Methods are disclosed comprising iterative function evaluation or Newton's method approaches based on a weighted sum-rate maximization across the network, which can be implemented in a distributed fashion. Some of the methods can be implemented asynchronously at each hub.

Abstract: Systems, methods and apparatuses are provided for mitigating interference in wireless networks, and particularly in an advanced backhaul wireless network comprising several hubs, each hub serving its own remote backhaul modules (RBMs). Preferred embodiments provide practical power spectrum adaptation methods for the management of interhub interference. These methods are shown to improve the overall network throughput significantly compared to a conventional network with fixed transmit power spectrum. Optionally, joint scheduling and power control are used to optimize the network utility. Also provided are methods which evoke the channel average gains generated by measurements for managed adaptive resource allocation (MARA). The proposed methods are computationally feasible and fast in convergence. They can be implemented in a distributed fashion across all hubs. Some of the proposed methods can be implemented asynchronously at each hub.

Abstract: Methods are disclosed for scheduling resources in a wireless backhaul network comprising a plurality of N Hubs, each Hub serving a plurality of K Remote Backhaul Modules (RBMs), using a coordinated power zone assignment across the backhaul network. For each Hub, a one-to-one power zone assignment, of each of the K RBM to one of the K power zones, is computed by maximizing a selected network utility across the backhaul network. Coordinated power zone assignment according to preferred embodiments based on the auction approach offers a close-to-global-optimal solution. Coordinated scheduling based on first assigning RBMs to hubs heuristically, and then optimally scheduling RBMs within each hub also offers significant performance improvement as compared to non-coordinated systems. Preferred embodiments offer a significant performance improvement as compared to conventional systems.

Abstract: Practical methods and apparatuses are provided for determining network clusters in wireless backhaul networks comprising a plurality of hubs and Remote Backhaul Modules (RBM) (104) based on link quality value (LQV) metrics. From an input LQV table of LQV values for each hub-RBM link (110), the link quality values are first ranked. Clusters are then identified from all the possible links based on the order of the highest link quality value to the lowest link quality value, any constraints on the number of RBMs per cluster, and clustering each RBM only once. Links with strong link quality values are chosen to optimize the LQV metric. LQV based clustering achieves a higher average LQV, e.g., average spectrum efficiency or weighted sum spectrum efficiency, for the entire backhaul network compared to the geographic location based clustering. The method is straightforward to implement and has low computational complexity.

Abstract: A method and system is disclosed for managing performance of a wireless backhaul network through power management, which provides a practical approach to balancing data throughput and fairness. For each transmit frame, one or more power zones is defined, each power zone comprising a set of radio resources operating at one transmit power level Pi, and the same power zone being defined over the same set of radio resources across all other clusters. The method maximizes the value of weighted weighted-sum utility, using a rate expression based on a CINR function. The optimization comprises a summation of the weighted logarithm of the rate expression plus a non-negative constant value, using a Newton's method approach, for fast and reliable convergence. Optimization may be based on long term averaged channel gains measured for each link. The value of c is selected to achieve a required balance of fairness and data throughput.

Abstract: Methods and apparatus are provided for managing interference in a wireless backhaul network comprising a plurality of hubs, each hub serving a plurality of remote backhaul modules (RBM), using power control with a one-power-zone (OPZ) constraint. Each hub uses a transmit frame structure comprising a plurality of zones, each RBM is scheduled on a different zone, and the same power level is maintained across all zones within a transmit frame. Under the OPZ constraint, and for scheduling policies under which the number of zones assigned to each RBM is fixed, the power and scheduling sub-problems are decoupled. This enables power control independent of scheduling, using methods having lower computational complexity. Methods are disclosed comprising iterative function evaluation or Newton's method approaches based on a weighted sum-rate maximization across the network, which can be implemented in a distributed fashion. Some of the methods can be implemented asynchronously at each hub.

Abstract: Systems, methods and apparatuses are provided for mitigating interference in wireless networks, and particularly in an advanced backhaul wireless network comprising several hubs, each hub serving its own remote backhaul modules (RBMs). Preferred embodiments provide practical power spectrum adaptation methods for the management of interhub interference. These methods are shown to improve the overall network throughput significantly compared to a conventional network with fixed transmit power spectrum. Optionally, joint scheduling and power control are used to optimize the network utility. Also provided are methods which evoke the channel average gains generated by measurements for managed adaptive resource allocation (MARA). The proposed methods are computationally feasible and fast in convergence. They can be implemented in a distributed fashion across all hubs. Some of the proposed methods can be implemented asynchronously at each hub.