Publications

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Journal Articles

Emerging scope and design challenges for approximate computing: optimizing accuracy-PPA trade-offs and beyond

Published in ACM Transactions on Embedded Computing Systems, 2025

This article discusses the evolving challenges in approximate computing, focusing on optimizing trade-offs among accuracy, power, performance, and area (PPA), and outlines future directions beyond current limitations.

Recommended citation: Sahoo, S. S., Deveautour, B., Traiola, M., Gu, C., Wu, Y., Japa, A., Ullah, S. & Kumar, A. (2025). “Emerging scope and design challenges for approximate computing: optimizing accuracy-PPA trade-offs and beyond.” ACM Transactions on Embedded Computing Systems. (Accepted 5 June 2025).
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Sharper Bounds for Proximal Gradient Algorithms with Errors

Published in SIAM Journal on Optimization, 2024

Analysis of proximal gradient algorithm convergence in the presence of gradient and proximal computational inaccuracies, with new tighter deterministic and probabilistic bounds.

Recommended citation: Hamadouche, A., Wu, Y., Wallace, A. M., & Mota, J. F. C. (2024). “Sharper Bounds for Proximal Gradient Algorithms with Errors.” *SIAM Journal on Optimization*, 34(1), 278-305.
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Efficient Reconfigurable Mixed Precision ℓ₁ Solver for Compressive Depth Reconstruction

Published in Journal of Signal Processing Systems, 2022

A mixed precision framework for ℓ₁ solvers (ADMM and PGD) applied to compressive depth reconstruction, demonstrating significant hardware and power savings on FPGA implementations.

Recommended citation: Wu, Y., Wallace, A. M., Mota, J. F. C., Aßmann, A., & Stewart, B. (2022). Efficient Reconfigurable Mixed Precision ℓ₁ Solver for Compressive Depth Reconstruction. *Journal of Signal Processing Systems*, 94(10), 1083–1099. https://doi.org/10.1007/s11265-022-01766-3
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Energy Efficient Approximate 3D Image Reconstruction

Published in IEEE Transactions on Emerging Topics in Computing, 2022

This paper presents a parallel, sparse depth reconstruction framework utilizing compressed sensing and approximate computing techniques to achieve energy efficiency in 3D image reconstruction.

Recommended citation: Wu, Y. (2022). Energy Efficient Approximate 3D Image Reconstruction. *IEEE Transactions on Emerging Topics in Computing*, 10(2), 1234–1245. https://doi.org/10.1109/TETC.2022.09559866
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Configurable Quasi-Optimal Sphere Decoding for Scalable MIMO Communications

Published in IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 68, Issue 6, 2021

This paper proposes a novel configurable Sphere Decoder (SD) for MIMO systems, balancing accelerator cost and detection accuracy via a Robust Bounded Spanning with Fast Enumeration (R-BSFE) approach.

Recommended citation: Wu, Y., & McAllister, J. (2021). Configurable Quasi-Optimal Sphere Decoding for Scalable MIMO Communications. *IEEE Transactions on Circuits and Systems I: Regular Papers*, 68(6), 2021–2032. https://doi.org/10.1109/TCSI.2021.9375712
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Architectural Synthesis of Multi-SIMD Dataflow Accelerators for FPGA

Published in IEEE Transactions on Parallel and Distributed Systems, 29(1), 43–55, 2018

This paper presents an architectural synthesis approach for deriving software-programmable multi-core SIMD accelerators from Signal Flow Graph models, enabling efficient FPGA implementations that meet prescribed throughput requirements.

Recommended citation: Wu, Y., & McAllister, J. (2018). Architectural Synthesis of Multi-SIMD Dataflow Accelerators for FPGA. *IEEE Transactions on Parallel and Distributed Systems, 29*(1), 43–55. https://doi.org/10.1109/TPDS.2017.2753038
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Bounded Selective Spanning With Extended Fast Enumeration for MIMO-OFDM Systems Detection

Published in IEEE Transactions on Circuits and Systems I: Regular Papers, 64(9), 2556–2568, 2017

This paper introduces a novel detection algorithm for MIMO-OFDM systems that combines bounded selective spanning with extended fast enumeration, aiming to improve detection performance and computational efficiency.

Recommended citation: Wu, Y., & McAllister, J. (2017). Bounded Selective Spanning With Extended Fast Enumeration for MIMO-OFDM Systems Detection. *IEEE Transactions on Circuits and Systems I: Regular Papers, 64*(9), 2556–2568. https://doi.org/10.1109/TCSI.2017.2716710
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Conference Papers

Rowhammer Mitigation by Approximate Computing: A Compressed Sensing Case Study

Published in IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 2025, 2025

This paper proposes AxRA, an approximate Rowhammer attack methodology tailored for modern DRAM systems, addressing reliability and security implications.

Recommended citation: Yuhang Hao, Yun Wu, Minmin Jiang, Maire O`Neill, Chongyan Gu. (2025). "Rowhammer Mitigation by Approximate Computing: A Compressed Sensing Case Study." IEEE/ACM International Conference on Computer-Aided Design (ICCAD) 2025: Proceedings. IEEE.
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AxRA: approximate Rowhammer attack for modern DRAM systems

Published in IEEE International Symposium on Circuits and Systems (ISCAS) 2025, 2025

This paper proposes AxRA, an approximate Rowhammer attack methodology tailored for modern DRAM systems, addressing reliability and security implications.

Recommended citation: Yuhang Hao, Yun Wu, Ziying Ni, Jack Miskelly, Maire O`Neill, Chongyan Gu. (2025). "AxRA: approximate Rowhammer attack for modern DRAM systems." IEEE International Symposium on Circuits and Systems (ISCAS) 2025: Proceedings. IEEE.
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Universal approximated real-valued Fast Fourier Transform for image blur detection

Published in 36th Irish Signals and Systems Conference (ISSC), 2025

A study of using a trimmed ANN to approximate the real-valued FFT for detecting blur, reducing computational cost while maintaining detection performance.

Recommended citation: Wang, X. & Wu, Y. (2025). “Universal approximated real-valued Fast Fourier Transform for image blur detection.” In *Proceedings of the 2025 36th Irish Signals and Systems Conference (ISSC)*, IEEE.
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Efficient co-approximate parallel compressive depth reconstruction on FPGA

Published in ICASSP 2025 (IEEE International Conference on Acoustics, Speech, and Signal Processing), 2025

A co-approximate framework for FPGA-based compressive depth image reconstruction using ℓ₁ solvers with frequency/voltage scaling and parallel approximate units, achieving strong power, speed, and efficiency gains.

Recommended citation: Wu, Y. & McAllister, J. (2025). “Efficient co-approximate parallel compressive depth reconstruction on FPGA.” In *2025 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025: Proceedings)*. IEEE.
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Efficient approximate checkerboard K-SVD for resource constrained embedded systems

Published in 35th Irish Signals and Systems Conference (ISSC 2024), 2024

An approximate, checkerboard-division based K-SVD for dictionary learning enabling large speedups and memory footprint reductions on embedded systems by trading off some accuracy.

Recommended citation: Wu, Y. & McAllister, J. (2024). “Efficient approximate checkerboard K-SVD for resource constrained embedded systems.” In *Proceedings of the 35th Irish Signals and Systems Conference (ISSC 2024)*. IEEE.
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Joint Undervolting and Overclocking Power Scaling Approximation on FPGAs

Published in 11th International Conference on Sensor Signal Processing for Defence (SSPD), 2022

An experimental study on the combined effects of undervolting and overclocking on FPGA peripherals, focusing on AXI memory access in Xilinx Ultrascale+ MPSoCs, to identify optimal power-performance trade-offs.

Recommended citation: Wu, Y., Mota, J. F. C., & Wallace, A. M. (2022). Joint undervolting and overclocking power scaling approximation on FPGAs. In *Proceedings of the 11th International Conference on Sensor Signal Processing for Defence (SSPD 2022)*. IEEE. https://doi.org/10.1109/SSPD54131.2022.9896229.
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Automatic approximation for 1-Dimensional Feedback-Loop Computations: a PID Benchmark

Published in Sensor Signal Processing for Defence Conference (SSPD 2022), 2022

An automated approach using affine arithmetic to tailor bit-widths in PID controllers, optimizing between accuracy, FPGA area, and power consumption under 1-dimensional feedback-loop benchmarks.

Recommended citation: Wu, Y., Zhang, Y., Hamadouche, A., Mota, J. F. C., & Wallace, A. M. (2022). “Automatic approximation for 1-Dimensional Feedback-Loop Computations: a PID Benchmark.” In *2022 Sensor Signal Processing for Defence Conference (SSPD 2022)*. IEEE. DOI:10.1109/SSPD54131.2022.9896191
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Energy-Efficient Adaptive Modulated Fixed-Complexity Sphere Decoder

Published in 2021 IEEE Workshop on Signal Processing Systems (SiPS 2021): Proceedings, 2021

This paper introduces an adaptive fixed-complexity sphere decoder that dynamically adjusts its complexity based on the modulation order, achieving energy efficiency in MIMO systems.

Recommended citation: Wu, Y., & McAllister, J. (2021). Energy-Efficient Adaptive Modulated Fixed-Complexity Sphere Decoder. In *Proceedings of the 2021 IEEE Workshop on Signal Processing Systems (SiPS 2021)* (pp. 82–87). IEEE. https://doi.org/10.1109/SiPS52901.2021.9595145
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Mixed Precision ℓ₁ Solver for Compressive Depth Reconstruction: An ADMM Case Study

Published in 2021 IEEE Workshop on Signal Processing Systems (SiPS 2021): Proceedings, 2021

This paper introduces a mixed precision framework for compressive depth reconstruction using a compact ADMM solver, demonstrating significant resource and power savings on FPGA implementations.

Recommended citation: Wu, Y., Wallace, A. M., Aßmann, A., & Stewart, B. (2021). Mixed Precision ℓ₁ Solver for Compressive Depth Reconstruction: An ADMM Case Study. In *Proceedings of the 2021 IEEE Workshop on Signal Processing Systems (SiPS 2021)* (pp. 70–75). IEEE. https://doi.org/10.1109/SiPS52901.2021.9595141
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Approximate Proximal-Gradient Methods

Published in 2021 Sensor Signal Processing for Defence Conference (SSPD): Proceedings, 2021

This paper explores the convergence of the Proximal-Gradient algorithm for convex composite problems when both the gradient and the proximal mapping are computed approximately.

Recommended citation: Hamadouche, A., Wu, Y., Wallace, A. M., & Mota, J. F. C. (2021). Approximate Proximal-Gradient Methods. In *Proceedings of the 2021 Sensor Signal Processing for Defence Conference (SSPD)*. IEEE. https://doi.org/10.1109/SSPD51364.2021.9541509
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Accelerated 3D Image Reconstruction for Resource-Constrained Systems

Published in 28th European Signal Processing Conference (EUSIPCO 2020) - Proceedings, 2020

This paper demonstrates an efficient and accelerated implementation of a parallel sparse depth reconstruction framework using compressed sensing (CS) techniques. The authors explore how CS can be split into smaller subproblems, allowing for the pre-computation of important components of the LU decomposition and subsequent linear algebra to solve a set of linear equations found in algorithms such as the alternating direction method of multipliers (ADMM). For comparison, a fully discrete least square reconstruction method is also presented. The study investigates how reduced precision is leveraged to reduce the number of logic units in field-programmable gate array (FPGA) implementations for such sparse imaging systems. The results show that the amount of logic units, memory requirements, and power consumption are reduced significantly by over 70% with minimal impact on the quality of reconstruction. This demonstrates the feasibility of novel high-resolution, low-power, and high frame rate light detection and ranging (LiDAR) depth imagers based on sparse illumination.

Recommended citation: Aßmann, A., Wu, Y., Stewart, B., & Wallace, A. M. (2020). Accelerated 3D Image Reconstruction for Resource-Constrained Systems. In *Proceedings of the 28th European Signal Processing Conference (EUSIPCO 2020)* (pp. 565–569). IEEE. https://doi.org/10.23919/Eusipco47968.2020.9287749
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Approximate LASSO Model Predictive Control for Resource-Constrained Systems

Published in 2020 Sensor Signal Processing for Defence Conference (SSPD): Proceedings, 2020

This paper introduces a reduced-precision implementation of the Lean Proximal Gradient Descent (LPGD) algorithm for LASSO-based Model Predictive Control (MPC), demonstrating significant reductions in logic cost, memory bandwidth, and power consumption on FPGA platforms.

Recommended citation: Wu, Y., Mota, J. F. C., & Wallace, A. M. (2020). Approximate LASSO Model Predictive Control for Resource-Constrained Systems. In *Proceedings of the 2020 Sensor Signal Processing for Defence Conference (SSPD)*. IEEE. https://doi.org/10.1109/SSPD47486.2020.9272000
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Programmable Dataflow Accelerators: A 5G OFDM Modulation/Demodulation Case Study

Published in ICASSP 2020 - IEEE International Conference on Acoustics, Speech, and Signal Processing, 2020

This paper explores the design and implementation of programmable dataflow accelerators for 5G Orthogonal Frequency Division Multiplexing (OFDM) modulation and demodulation, demonstrating significant improvements in throughput and energy efficiency.

Recommended citation: Wu, Y., Wang, P., & McAllister, J. (2020). Programmable Dataflow Accelerators: A 5G OFDM Modulation/Demodulation Case Study. In *ICASSP 2020 - IEEE International Conference on Acoustics, Speech, and Signal Processing* (pp. 1728–1732). IEEE. https://doi.org/10.1109/ICASSP40776.2020.9053529
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On Modified Squared Givens Rotations for Sphere Decoder Preprocessing

Published in ICASSP 2019 - IEEE International Conference on Acoustics, Speech, and Signal Processing, 2019

This paper introduces a preprocessing technique for sphere decoding that utilizes modified squared Givens rotations, aiming to reduce computational complexity and enhance hardware efficiency.

Recommended citation: Wu, Y., & McAllister, J. (2019). On Modified Squared Givens Rotations for Sphere Decoder Preprocessing. In *ICASSP 2019 - IEEE International Conference on Acoustics, Speech, and Signal Processing* (pp. 1528–1531). IEEE. https://doi.org/10.1109/ICASSP.2019.8683283
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Heterogeneous Servers based on Programmable Cores and Dataflow Engines

Published in Workshop on Energy-Efficient Servers for Cloud and Edge Computing 2017, 2017

This paper explores the design and implementation of energy-efficient server architectures that integrate programmable cores and dataflow engines, aiming to enhance performance and reduce power consumption in cloud and edge computing environments.

Recommended citation: Wu, Y., Gillan, C., Minhas, U., Barbhuiya, S., Novakovic, A., Tovletoglou, K., Tzenakis, G., Vandierendonck, H., Karakonstantis, G., & Nikolopoulos, D. (2017). Heterogeneous Servers based on Programmable Cores and Dataflow Engines. In *Workshop on Energy-Efficient Servers for Cloud and Edge Computing 2017*. Queen’s University Belfast. https://pureadmin.qub.ac.uk/ws/files/123397592/HiPEAC_ESCEC_2016.pdf
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Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

Published in Proceedings of the International Conference on Embedded Computer Systems: Architecture, Modeling and Simulation (SAMOS XVI), 71–78, 2017

This paper introduces a runtime system that enables adaptive power capping on heterogeneous System-on-Chip (SoC) architectures, aiming to balance performance and power consumption in embedded systems.

Recommended citation: Wu, Y., Nikolopoulos, D. S., & Woods, R. (2017). Runtime Support for Adaptive Power Capping on Heterogeneous SoCs. In *Proceedings of the International Conference on Embedded Computer Systems: Architecture, Modeling and Simulation (SAMOS XVI)* (pp. 71–78). IEEE. https://doi.org/10.1109/SAMOS.2017.7818333
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Accelerating Data Center Applications with Reconfigurable DataFlow Engines

Published in Heterogeneous High-Performance Reconfigurable Computing (H2RC) 2016 Workshop, 2016

This paper explores the integration of reconfigurable DataFlow Engines (DFEs) into data center applications, aiming to enhance computational efficiency and energy performance.

Recommended citation: Barbhuiya, S., Wu, Y., Murphy, K., Vandierendonck, H., Karakonstantis, G., & Nikolopoulos, D. S. (2016). Accelerating Data Center Applications with Reconfigurable DataFlow Engines. In *Proceedings of the Heterogeneous High-Performance Reconfigurable Computing (H2RC) 2016 Workshop*. https://h2rc.cse.sc.edu/2016/papers/paper_9.pdf
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FPGA Soft-Core Processors, Compiler and Hardware Optimizations Validated Using HOG

Published in Applied Reconfigurable Computing - 12th International Symposium, ARC 2016, Proceedings, Lecture Notes in Computer Science, Vol. 9625, pp. 78–90, 2016

This paper explores the integration of FPGA-based soft-core processors with compiler and hardware optimizations to enhance the performance of image processing applications, validated through the Histogram of Oriented Gradients (HOG) algorithm.

Recommended citation: Kelly, C., Siddiqui, F. M., Bardak, B., Wu, Y., Woods, R., & Rafferty, K. (2016). FPGA Soft-Core Processors, Compiler and Hardware Optimizations Validated Using HOG. In *Applied Reconfigurable Computing - 12th International Symposium, ARC 2016, Proceedings* (Vol. 9625, pp. 78–90). Springer. https://doi.org/10.1007/978-3-319-31462-4_7
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Power Modeling and Capping for Heterogeneous ARM/FPGA SoCs

Published in Proceedings of the 2014 International Conference on Field-Programmable Technology (FPT), IEEE, pp. 231–234, 2014

This paper presents a methodology for power modeling and capping in heterogeneous ARM/FPGA System-on-Chip (SoC) architectures, aiming to optimize energy efficiency in embedded systems.

Recommended citation: Wu, Y., Nunez-Yanez, J., Woods, R., & Nikolopoulos, D. S. (2014). Power Modeling and Capping for Heterogeneous ARM/FPGA SoCs. In *Proceedings of the 2014 International Conference on Field-Programmable Technology (FPT)* (pp. 231–234). IEEE. https://doi.org/10.1109/FPT.2014.7082782
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FPGA-based Tabu Search for Detection in Large-Scale MIMO Systems

Published in 2014 IEEE Workshop on Signal Processing Systems (SiPS): Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 1–6, 2014

This paper presents an FPGA-based implementation of the Tabu Search algorithm for efficient detection in large-scale MIMO systems, aiming to balance performance and computational complexity.

Recommended citation: Wu, Y., & McAllister, J. (2014). FPGA-based Tabu Search for Detection in Large-Scale MIMO Systems. In *Proceedings of the 2014 IEEE Workshop on Signal Processing Systems (SiPS)* (pp. 1–6). IEEE. https://doi.org/10.1109/SiPS.2014.6986073
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High Performance Real-Time Pre-Processing for Fixed-Complexity Sphere Decoder

Published in 2013 IEEE Global Conference on Signal and Information Processing (GlobalSIP), pp. 1250–1253, 2013

This paper addresses the challenge of real-time pre-processing in Fixed-Complexity Sphere Decoders for MIMO systems, proposing an FPGA-based architecture that reduces resource cost by 50% while maintaining real-time performance.

Recommended citation: Wu, Y., McAllister, J., & Wang, P. (2013). High performance real-time pre-processing for fixed-complexity sphere decoder. In *2013 IEEE Global Conference on Signal and Information Processing (GlobalSIP)* (pp. 1250–1253). IEEE. https://doi.org/10.1109/GlobalSIP.2013.7086073
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Cooperative Actor Oriented Synthesis for FPGA-based MIMO-OFDM Detection

Published in 2013 Software Defined Radio (SDR)-WInnComm, Washington, D.C., 2013

This paper introduces a novel actor-oriented synthesis approach for FPGA-based MIMO-OFDM detection, enhancing modularity and reusability in hardware design.

Recommended citation: Wu, Y., McAllister, J., & Wang, P. (2013). Cooperative Actor Oriented Synthesis for FPGA-based MIMO-OFDM Detection. In *2013 Software Defined Radio (SDR)-WInnComm*. Wireless Innovation Forum.
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Bounded Selective Spanning with Extended Fast Enumeration for MIMO-OFDM Systems Detection

Published in 2013 Proceedings of the 21st European Signal Processing Conference (EUSIPCO 2013), Marrakech, Morocco, pp. 1–5, 2013

This paper introduces Bounded Selective Spanning with Extended Fast Enumeration (BSS-EFE), an enhancement to the SSFE algorithm, improving detection performance and computational efficiency in MIMO-OFDM systems.

Recommended citation: Wu, Y., & McAllister, J. (2013). Bounded Selective Spanning with Extended Fast Enumeration for MIMO-OFDM Systems Detection. In *2013 Proceedings of the 21st European Signal Processing Conference (EUSIPCO 2013)* (pp. 1–5). IEEE. https://doi.org/10.1109/EUSIPCO.2013.6811656
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Soft-core Stream Processing on FPGA: An FFT Case Study

Published in 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2756–2760, 2013

This paper presents the first recorded implementation of a softcore Fast Fourier Transform (FFT) on Xilinx Virtex FPGA technology, achieving 1.1 GSamples/s throughput and up to 19 times speed-up over the Xilinx Radix-2 FFT dedicated circuit.

Recommended citation: Wang, P., McAllister, J., & Wu, Y. (2013). Soft-core stream processing on FPGA: An FFT case study. In *2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)* (pp. 2756–2760). IEEE. https://doi.org/10.1109/ICASSP.2013.6638261
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Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Published in 2011 IEEE Workshop on Signal Processing Systems (SiPS), pp. 107–113, 2011

This paper proposes a tree-based adaptive spatial detection (TASD) method for adaptive modulated MIMO systems, aiming to improve detection performance while maintaining computational efficiency.

Recommended citation: Zheng, C., Wu, Y., McAllister, J., & Woods, R. (2011). Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems. In *2011 IEEE Workshop on Signal Processing Systems (SiPS)* (pp. 107–113). IEEE. https://doi.org/10.1109/SiPS.2011.6111848
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A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Published in 2011 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), pp. 278–285, 2011

This paper presents a novel kernel interleaved scheduling (KIS) method for streaming applications on soft-core vector processors, aiming to improve resource utilization and performance in FPGA-based systems.

Recommended citation: Zheng, C., McAllister, J., & Wu, Y. (2011). A kernel interleaved scheduling method for streaming applications on soft-core vector processors. In *2011 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)* (pp. 278–285). IEEE. https://doi.org/10.1109/RTCSA.2011.6006617
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Dr Yun Wu

Publications

Journal Articles

Conference Papers