Abstract: Systems and methods are described for jointly optimizing communications in a multi-user network to maximize the weighted sum-rate of its data links. For example, embodiments seek to maximize overall link transmit rates, while minimizing link interference and/or noise in general multi-in multi-out (MIMO) interference networks having multiple interfering data links, each with one or more antennas at the transmitter and receiver. Novel algorithmic approaches, including an “iterative minimax” approach and a “dual link” approach, are described for solving the weighted sum-rate maximization in a manner that converges quickly and reliably on an optimal point. Some embodiments implement these approaches in a centralized transmission controller, while others implement these approaches in a distributed fashion.

Abstract: Systems and methods are described for jointly optimizing communications in a multi-user network to maximize the weighted sum-rate of its data links. For example, embodiments seek to maximize overall link transmit rates, while minimizing link interference and/or noise in general multi-in multi-out (MIMO) interference networks having multiple interfering data links, each with one or more antennas at the transmitter and receiver. Novel algorithmic approaches, including an “iterative minimax” approach and a “dual link” approach, are described for solving the weighted sum-rate maximization in a manner that converges quickly and reliably on an optimal point. Some embodiments implement these approaches in a centralized transmission controller, while others implement these approaches in a distributed fashion.

Abstract: In an aspect of the method, a received data packet is decoded in order to determine a packet error rate value, and an average package error value for N received data packets is updated based on the determined packet error rate value. The updated average packet error rate value is then compared against a threshold value and a data rate request is issued based on this comparison. In another aspect, a response to a transmitted data packet is received, the response being related to an average packet error rate value. The average packet error rate value is compared against a threshold and a data rate is modified based on the comparison. In each of the above aspects, a data rate control margin that is used to overcome channel estimate errors resulting from transmission delays may be dynamically adjusted, e.g., in real time, in order to optimize system resources.

Abstract: In the method according to the present invention, a transmit power for each eigenbeam in a set of eigenbeams forming at least a portion of a multiple transmit antenna system is determined based on noise associated with each eigenbeam in the set of eigenbeams. The set of eigenbeams is for transmitting a number of parallel complex Gaussian channels.

Abstract: In the method according to the present invention, a transmit power for each eigenbeam in a set of eigenbeams forming at least a portion of a multiple transmit antenna system is determined based on noise associated with each eigenbeam in the set of eigenbeams. The set of eigenbeams is for transmitting a number of parallel complex Gaussian channels.

Abstract: In an aspect of the method, a received data packet is decoded in order to determine a packet error rate value, and an average package error value for N received data packets is updated based on the determined packet error rate value. The updated average packet error rate value is then compared against a threshold value and a data rate request is issued based on this comparison. In another aspect, a response to a transmitted data packet is received, the response being related to an average packet error rate value. The average packet error rate value is compared against a threshold and a data rate is modified based on the comparison. In each of the above aspects, a data rate control margin that is used to overcome channel estimate errors resulting from transmission delays may be dynamically adjusted, e.g., in real time, in order to optimize system resources.