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This paper presents a hardware architecture for the QR decomposition (QRD) of a complex-valued matrix based on Modified Gram-Schmidt (MGS) algorithm. A high throughput iterative-pipelined design is implemented, which achieves similar performance of a fully parallel-pipelined design, with a significant reduction in hardware usage. For a fixed-point Field Programmable Gate Array (FPGA) implementation...
In this paper we propose an efficient hardware architecture for computation of matrix inversion of positive definite matrices. The algorithm chosen is LDL decomposition followed directly by equation system solving using back substitution. The architecture combines a high throughput with an efficient utilization of its hardware units. We also report FPGA implementation results that show that the architecture...
This paper describes the architecture and implementation of a high performance QR decomposition IEEE754 single precision floating point core, using a modified Gram-Schmidt algorithm. Using Intel's new floating point Arria 10 FPGAs, synthesis is used to generate column high functional units, giving O(n2) processing times. The modified Gram-Schmidt algorithm is expressed in a different order to combine...
Matrix decomposition is required in various algorithms used in wireless communication applications. FPGAs strike a balance between ASICs and DSPs, as they have the programmability of software with performance capacity approaching that of a custom hardware implementation. However, FPGA architectures require designers to make a countless number of system, architectural and logic design decisions. By...
This paper proposes to use the discrete Fourier transform (DFT) matrix factorization based on the Kronecker product to express the family of radix rk single-path delay commutator/single-path delay feedback (SDC/SDF) pipeline fast Fourier transform (FFT) architectures. The matricial expressions of the radix r, r2, r3, and r4 decimation-in-frequency (DIF) SDC/SDF pipeline architectures are derived...
Matrix inversion is an essential computation for various algorithms which are employed in multi-antenna wireless communication systems. FPGAs are ideal platforms for wireless communication; however, the need for vast amounts of customization throughout the design process of a matrix inversion core can overwhelm the designer. Decomposition methods provide the analytic simplicity and computational convenience...
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