A Novel Architecture to Eliminate Bottlenecks in a Parallel Tiled QRD Algorithm for Future MIMO Systems

Liu, Cang; Zhang, Xing; Ling, Yuan; Tang, Chuan; Zhang, Yang

doi:10.1109/tcsii.2016.2546908

Cited by 10 publications

(4 citation statements)

References 16 publications

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“…Note that the QR decomposition of a matrix can be computed using some well-known algorithms based on Gram-Schmidt orthogonalization, Householder transformation, or Givens rotation with different architectural designs. For example, the authors in [16], [17] studied different hardware architectures for low complexity hardware implementation of the QR decomposition used in the signal estimation of MIMO systems. However, the hardware architecture is out of the scope of this paper.…”

Section: Uplink Signal Estimationmentioning

confidence: 99%

Finite Precision Implementation of Recursive Algorithms for Uplink Detection in Cell-Free Networks

Ranjbar

Pollin

Moonen

2022

2022 IEEE Globecom Workshops (GC Wkshps)

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Cell-free communication where distributed access points (APs) cooperatively serve users is emerging as an important enabler for 6G. This new architecture for communication systems is expected to enhance the quality of service of all the users due to the coherent transmission and reception of multiple spatially separated APs each with a low number of antennas. When scaling to very large cell-free deployments, the communication overhead between APs becomes a bottleneck. In this paper, we study how two recursive algorithms behave under the assumption of limited bandwidth fronthaul links between APs in the uplink signal estimation of a cell-free network with a daisychain topology. We analyze the impact of finite precision on the numerical stability of two RLS implementations named QR-RLS and standard RLS (SRLS). Simulation results show that QR-RLS is numerically stable for all simulated quantization precision and scenarios, while SRLS might be stable when carefully initialized. Moreover, SRLS numerical instability becomes worse when the number of users increases.

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Section: Uplink Signal Estimationmentioning

confidence: 99%

Finite Precision Implementation of Recursive Algorithms for Uplink Detection in Cell-Free Networks

Ranjbar

Pollin

Moonen

2022

2022 IEEE Globecom Workshops (GC Wkshps)

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“…Matrix inversion is one of the most useful operations used in many signal processing algorithms (SPA), where the efficient computation and accuracy of this operation are required. Important areas such as image recovery, phased-array radar and sonar, wireless communication, control applications, and others [1] require the efficient computations of the matrix inversion in real time, specifically in Hardware (HW) implementations of wireless communication for designing multiple-input multiple-output (MIMO) systems [2,3], in multiplicative noise generators using autoregressive modeling [4], and more generally in the implementation of generic linear algebra architectures [5].…”

Section: Introductionmentioning

confidence: 99%

FPGA-Based Hardware Matrix Inversion Architecture Using Hybrid Piecewise Polynomial Approximation Systolic Cells

et al. 2020

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The hardware of the matrix inversion architecture using QR decomposition with Givens Rotations (GR) and a back substitution (BS) block is required for many signal processing algorithms. However, the hardware of the GR algorithm requires the implementation of complex operations, such as the reciprocal square root (RSR), which is typically implemented using LookUp Table (LUT) and COordinate Rotation DIgital Computer (CORDICs), among others, conveying to either high-area consumption or low throughput. This paper introduces an Field-Programmable Gate Array (FPGA)-based full matrix inversion architecture using hybrid piecewise polynomial approximation systolic cells. In the design, a hybrid segmentation technique was incorporated for the implementation of piecewise polynomial systolic cells. This hybrid approach is composed by an external and internal segmentation, where the first is nonuniform and the second is uniform, fitting the curve shape of the complex functions achieving a better signal-quantization-to noise-ratio; furthermore, it improves the time performance and area resources. Experimental results reveal a well-balanced improvement in the design achieving high throughput and, hence, less resource utilization in comparison to state-of-the-art FPGA-based architectures. In our study, the proposed design achieves 7.51 Mega-Matrices per second for performing 4 × 4 matrix operations with a latency of 12 clock cycles; meanwhile, the hardware design requires only 1474 slice registers, 1458 LUTs in an FPGA Virtex-5 XC5VLX220T, and 1474 slice registers and 1378 LUTs when a FPGA Virtex-6 XC6VLX240T is used.

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“…However, the number of antennas corresponds to the dimensions of matrix handled in signal processing, hence more antennas require more powerful hardware chips in the physical layer, especially the ability of dealing with large-scale matrix operations, which is difficult and even an important research point for traditional small-scale MIMO [5,6]. Data detection is a critical and complex task for massive MIMO signal processing [7,8], which involves matrix inversion or solving linear system of equations. Owing to the enormous complexity, some research has been carried on about low-complexity detection using approximate iteration methods [9][10][11][12][13][14], which decrease the complexity from O(M 3 ) to O(M 2 ) where M is the dimensions of the matrix to be inversed.…”

Section: Introductionmentioning

confidence: 99%

Approximate iteration detection with iterative refinement in massive MIMO systems

et al. 2017

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A Novel Architecture to Eliminate Bottlenecks in a Parallel Tiled QRD Algorithm for Future MIMO Systems

Cited by 10 publications

References 16 publications

Finite Precision Implementation of Recursive Algorithms for Uplink Detection in Cell-Free Networks

Finite Precision Implementation of Recursive Algorithms for Uplink Detection in Cell-Free Networks

FPGA-Based Hardware Matrix Inversion Architecture Using Hybrid Piecewise Polynomial Approximation Systolic Cells

Approximate iteration detection with iterative refinement in massive MIMO systems

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