Evolutionary algorithms for geographic load balancing using a distributed antenna system

Abstract

Methods and apparatuses are presented for balancing non-uniformly distributed network traffic in a wireless communications system having a plurality of digital remote units (DRUs). In some embodiments, a method comprises partitioning the plurality of DRUs into a plurality of DRU sectors, and dynamically repartitioning the plurality of DRU sectors depending on traffic conditions in at least one of the DRU sectors, such that the repartitioning satisfies at least one of a soft capacity constraint or a hard capacity constraint. The dynamic repartitioning may be based on at least one optimization algorithm.

1 . (canceled) 
     
     
         2 . A method for dynamically repartitioning cells of a mobile network, the method comprising:
 a) providing a digital access unit (DAU) associated with a plurality of sectors of a virtual base station;   b) providing a plurality of digital remote units (DRUs) associated with the DAU;   c) partitioning the plurality of DRUs into a plurality of DRU sectors;   d) measuring at least one metric associated with the plurality of DRU sectors;   e) comparing the at least one metric to a predetermined threshold;   f) determining that iteration of partitioning is warranted, and   g) iterating on at least elements (c) through (e).   
     
     
         3 . The method of  claim 2  wherein measuring the at least one metric further comprises determining a compactness index of each sector of the plurality of DRU sectors. 
     
     
         4 . The method of  claim 3  wherein partitioning the plurality of DRUs comprises maximizing a compactness index of each sector of the plurality of DRU sectors. 
     
     
         5 . The method of  claim 2  wherein the at least one metric further comprises minimizing session handoffs. 
     
     
         6 . The method of  claim 2  wherein the at least one metric further comprises a maximum number of users associated with a predetermined signal to noise ratio (SNR). 
     
     
         7 . The method of  claim 2  wherein iterating comprises utilizing at least one optimization algorithm. 
     
     
         8 . The method of  claim 7  wherein the at least one optimization algorithm is at least one of a Genetic Algorithm (GA) or an Estimation Distribution Algorithm (EDA). 
     
     
         9 . The method of  claim 2  wherein each sector of the plurality of DRU sectors comprises connected DRUs. 
     
     
         10 . A digital access unit (DAU) for dynamically repartitioning cells of a mobile network, the DAU comprising a data processor coupled to a non-transitory computer-readable storage medium comprising a plurality of computer-readable instructions tangibly embodied on the computer-readable storage medium, which, when executed by the data processor, provide for balancing of network traffic, the plurality of instructions comprising:
 a) instructions that cause the data processor to partition a plurality of DRUs into a plurality of DRU sectors;   b) instructions that cause the data processor to measure at least one metric associated with the plurality of DRU sectors;   c) instructions that cause the data processor to compare the at least one metric to a predetermined threshold; and   d) instructions that cause the data processor to determine that the at least one metric is greater than the predetermined threshold; and   e) iterating at least elements (a) through (d).   
     
     
         11 . The DAU of  claim 10  wherein the at least one metric further comprises minimizing session handoffs. 
     
     
         12 . The DAU of  claim 10  wherein the instructions that cause the data processor to measure the at least one metric further comprises determining a compactness index of each sector of the plurality of DRU sectors. 
     
     
         13 . The DAU of  claim 12  wherein instructions that cause the data processor to partition the plurality of DRUs comprises maximizing the compactness index of each sector of the plurality of DRU sectors. 
     
     
         14 . The DAU of  claim 10  wherein the at least one metric further comprises a maximum number of users associated with a predetermined signal to noise ratio (SNR). 
     
     
         15 . The DAU of  claim 10  wherein iterating comprises utilizing at least one optimization algorithm. 
     
     
         16 . The DAU of  claim 15  wherein the at least one optimization algorithm is at least one of a Genetic Algorithm (GA) or an Estimation Distribution Algorithm (EDA). 
     
     
         17 . The DAU of  claim 10  wherein each sector of the plurality of DRU sectors comprises connected DRUs.