Arithmetic complexity of the Adaptive Antenna Array (AAA) consists of two parts: the complexity of the beamforming (the AAA input signal weighting and combination) and the AAA weights computation (the adaptive algorithm). The beamforming complexity cannot be reduced because it depends on the number of the antennas/channels which are selected to ensure the required properties of the array. At the same time, if the number of the adaptively controlled weights is less than the total number of the array weights, the arithmetic complexity of the adaptive algorithm can be reduced. Such an AAA is called a partially adaptive one. In the case of the rectangular AAA the partial adaptation can be achieved by the combination of the signals received by the antennas of the rows and the columns of the array prior to the adaptive weighting. This reduces the adaptive algorithm complexity because the reduced number of the adaptively computed/controlled weights is required in this case. However if the receiving signals number (the informational one and the interfering ones) is less than the array rows and columns number the partially adaptive array provides the steady-state performance which is almost the same as that of the array with all adaptively controlled weights. If the AAA is a symmetrical one (the pairs of its weights, which correspond the antennas placed in the locations symmetrical relatively the array phase center, are complex conjugated to each other) then a further reduction of the arithmetic complexity might be achieved by means of the usage of the real-valued computations. The main steps of the development of the real-valued partially adaptive antenna array with the combination of the row and column signals are considered in this paper. The AAA architecture, its computational procedure and the results of the AAA simulation are also considered. This simulation demonstrates about 3 dB better cancellation of the interferences and about two times shorter transient response of the proposed AAA compared to the same AAA in the complex-valued arithmetic.

Rectangular Partially Adaptive Antenna Array in Real-Valued Arithmetic

/pdf/a-fast-method-of-generating-pseudo-random-vectors-of-high-3v2posoo07.pdf

A Fast Method of Generating Pseudo-Random Vectors of High Dimension for testing Systems-on-Chip

Arithmetic complexity of the Adaptive Antenna Array (AAA) consists of two parts: the complexity of the beamforming (the AAA input signal weighting and combination) and the AAA weights computation (the adaptive algorithm). The beamforming complexity cannot be reduced because it depends on the number of the antennas/channels which are selected to ensure the required properties of the array. At the same time, if the number of the adaptively controlled weights is less than the total number of the array weights, the arithmetic complexity of the adaptive algorithm can be reduced. Such an AAA is called a partially adaptive one. In the case of the rectangular AAA the partial adaptation can be achieved by the combination of the signals received by the antennas of the rows and the columns of the array prior to the adaptive weighting. This reduces the adaptive algorithm complexity because the reduced number of the adaptively computed/controlled weights is required in this case. However if the receiving signals number (the informational one and the interfering ones) is less than the array rows and columns number the partially adaptive array provides the steady-state performance which is almost the same as that of the array with all adaptively controlled weights. If the AAA is a symmetrical one (the pairs of its weights, which correspond the antennas placed in the locations symmetrical relatively the array phase center, are complex conjugated to each other) then a further reduction of the arithmetic complexity might be achieved by means of the usage of the real-valued computations. The main steps of the development of the real-valued partially adaptive antenna array with the combination of the row and column signals are considered in this paper. The AAA architecture, its computational procedure and the results of the AAA simulation are also considered. This simulation demonstrates about 3 dB better cancellation of the interferences and about two times shorter transient response of the proposed AAA compared to the same AAA in the complex-valued arithmetic. 

Designing a high-performance SoC based on a 16-bit processor core

/pdf/a-methodology-for-testing-the-microprocessor-core-of-a-13hd5v629z.pdf

M.I. Dyabin

Papers

Designing a high-performance SoC based on a 16-bit processor core

A methodology for testing the microprocessor core of a system on chip with a x86-compatible microprocessor

A Fast Method of Generating Pseudo-Random Vectors of High Dimension for testing Systems-on-Chip

An Algorithm of Building Fast Hash Functions Based on Replacement of Symbols