A blind adaptive transmit antenna algorithm for wireless communication

Abstract

A method is proposed for forming an adaptive phased array transmission beam pattern at a base station without any knowledge of array geometry, path angles or mobile feedback. Estimates of receive vector channels are used to form a transmit weight vector optimization problem. We provide closed form solutions for both the single user case and the multiple user case. We show through simulation of a multiple user cellular network that our cooperative transmission network algorithm is capable of improving network frequency re-use capacity by a factor of 5 to 8.

Transmit beamforming and power control for cellular wireless systems

“…With different numbers of antennas at the base stations we have implemented Algorithms B-E and evaluated the maximum achievable SINR in the network. Algorithms D and E with fixed power allocation (without power control) are called R1 and R2, respectively [7], and are simulated in a system where each base station transmits with the maximum power. The results of a Monte Carlo analysis for 100 iterations is summarized in Table I.…”

“…When we find the beamforming vectors, we can calculate the minimal power allocation for the downlink using the third step of the algorithm. In the next section, for comparison purposes we compare the performance of our algorithms with a modified version of the algorithms proposed in [7]. In the first algorithm we try to maximize the received power at the desired mobile with a fixed norm transmit beamforming vector.…”

“…In [9], in a scenario where adaptive arrays are used at transmitters and receivers, an algorithm is proposed for selective transmission which uses the weight vectors calculated by single tap diversity combiners at the receivers. In [7] and [10], transmitter patterns are adjusted to minimize the overall interference to the other cochannel receivers using single tap transmit diversity. In [6], the use of multitap transmit diversity is proposed to reject the interference to other links.…”

Great Expectations: The Value of Spatial Diversity in Wireless Networks

“…However, for frequency-selective channels, a 26 Channel state knowledge at the transmitter can be reasonable when the transmission and reception take place at the same carrier frequency as in time division duplexing (TDD) [213], [237]. However, even in frequency division duplex (FDD) for two-way communication systems, statistical knowledge of the channel could be used to enhance performance [211], [214]. 27 It is also possible to combine closed-loop and open-loop techniques as shown recently in [152], [232].…”

A simple gradient sign algorithm for transmit antenna weight adaptation with feedback

“…These are then used to adapt transmit antenna weights. This may require accurate antenna calibration as, for example, in estimating the angle of arrival and angular dispersion of the received signal to steer the transmit beam [11], or it may assume that the long-term characteristics of the uplink and downlink channels are strongly correlated [12]. However, these algorithms do not provide fading diversity, and if the antennas experience independent fading then blind techniques will not work, as without correlation between antennas, no correlation from uplink to downlink channel can be extracted.…”