Beam configuration optimization
Beam configuration optimization is disclosed. A network node device may determine a grid of beams. The grid of beams is determined to maximize a fairness function of an estimated received power of at least two of the beams of the grid of beams that are optimal for each client device of a plurality of client devices.
1 . A network node device comprising:
at least one processor; and
at least one memory including computer program code;
where the at least one memory and the computer program code are configured to, with the at least one processor, cause the network node device to perform operations comprising:
determining a grid of beams, wherein the grid of beams is determined to maximize a fairness function of an estimated received power of at least two of the beams of the grid of beams that are optimal for each client device of a plurality of client devices, wherein the fairness function comprises, for each client device, a cross-beam fairness function of the estimated received power of the at least two beams of the grid of beams that are optimal for the client device, and wherein the determining of the grid of beams comprises using an optimization algorithm comprising a greedy algorithm configured to sequentially add beams maximizing incremental gain.
2 . The network node device according to claim 1 , wherein the cross-beam fairness function is an α-fairness function.
3 . The network node device according to claim 2 , wherein an α parameter of the cross-beam α-fairness function is equal to 0, and wherein the cross-beam fairness function comprises a sum of the estimated received power of the at least two beams of the grid of beams that are optimal for the client device.
4 . The network node device according to claim 1 , wherein the fairness function comprises a cross-device fairness function of the cross-beam fairness function for each client device of the plurality of client devices.
5 . The network node device according to claim 4 , wherein the cross-device fairness function is an α-fairness function.
6 . The network node device according to claim 5 , wherein an α parameter of the cross-beam α-fairness function is equal to 1.
7 . The network node device according to claim 6 , wherein the cross-device function comprises a sum, across a plurality of azimuth and elevation quadruples, of a decibel of the cross-beam fairness function for each client device of the plurality of client devices weighted by a traffic density value in the azimuth and elevation quadruple.
8 . The network node device according to claim 7 , wherein the operations further comprise:
estimating a traffic density distribution for a radio channel between the network node device and the plurality of client devices, the traffic density distribution defining the traffic density value for each azimuth and elevation quadruple of the plurality of azimuth and elevation quadruples.
9 . The network node device according to claim 8 , wherein estimating the traffic density distribution comprises:
receiving, from the client devices, a plurality of reports, each report indicating a spatial direction for one of the client devices;
clustering the reports; and
computing the traffic density distribution based on the clustered reports.
10 . The network node device according to claim 1 , wherein the estimated received power comprises one or more of an estimated received power, or a beamforming gain.
11 . The network node device according to claim 1 , wherein the optimization algorithm comprises a policy improvement algorithm configured to iteratively choose a beam maximizing a performance of the greedy algorithm.
12 . The network node device according to claim 1 , the operations further comprising:
applying the grid of beams to a transceiver antenna array of the network node device.
13 . The network node device according to claim 1 , the operations further comprising:
generating, by the network node device, a beam dictionary, wherein the grid of beams is selected from the beam dictionary.
14 . The network node device according to claim 1 , wherein the grid of beams comprises a plurality of Synchronization Signal Block beams.
15 . A method comprising:
determining a grid of beams, wherein the grid of beams is determined to maximize a fairness function of an estimated received power of at least two of the beams of the grid of beams that are optimal for each client device of a plurality of client devices, wherein the fairness function comprises, for each client device, a cross-beam fairness function of the estimated received power of the at least two beams of the grid of beams that are optimal for the client device, and wherein the determining of the grid of beams comprises using an optimization algorithm comprising a greedy algorithm configured to sequentially add beams maximizing incremental gain.
16 . A non-transitory computer readable medium comprising instructions for causing a network node device to perform at least the following:
determining a grid of beams, wherein the grid of beams is determined to maximize a fairness function of an estimated received power of at least two of the beams of the grid of beams that are optimal for each client device of a plurality of client devices, wherein the fairness function comprises, for each client device, a cross-beam fairness function of the estimated received power of the at least two beams of the grid of beams that are optimal for the client device, and wherein the determining of the grid of beams comprises using an optimization algorithm comprising a greedy algorithm configured to sequentially add beams maximizing incremental gain.