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RRO: A Regularized Routing Optimization Algorithm for Enhanced Throughput and low Latency With Efficient complexity

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第2期43卷 437-447页

作者： Zenati, David Maimon, Tzalik Cohen, Kobi Ben Gurion Univ Negev Sch Elect & Comp Engn IL-8410501 Beer Sheva Israel Ceragon Networks Ltd IL-4810002 Tel Aviv Israel

In the rapidly evolving landscape of wireless networks, achieving enhanced throughput with low latency for data transmission is crucial for future communication systems. While low complexity OSPF-type solutions have shown effectiveness in lightly-loaded networks, they often falter in the face of increasing congestion. Recent approaches have suggested utilizing backpressure and deep learning techniques for route optimization. However, these approaches face challenges due to their high implementation and computational complexity, surpassing the capabilities of networks with limited hardware devices. A key challenge is developing algorithms that improve throughput and reduce latency while keeping complexity levels compatible with OSPF. In this collaborative research between Ben-Gurion University and Ceragon Networks Ltd., we address this challenge by developing a novel approach, dubbed Regularized Routing Optimization (RRO). The RRO algorithm offers both distributed and centralized implementations with low complexity, making it suitable for integration into 5G and beyond technologies, where no significant changes to the existing protocols are needed. It increases throughput while ensuring latency remains sufficiently low through regularized optimization. We analyze the computational complexity of RRO and prove that it converges with a level of complexity comparable to OSPF. Extensive simulation results across diverse network topologies demonstrate that RRO significantly outperforms existing methods.

关键词： Routing algorithms low-complexity algorithms enhanced-throughput enhanced-throughput low-latency low-latency low-latency

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low-complexity Network Coding algorithms for Energy Efficient Information Exchange

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JOURNAL OF COMMUNICATIONS AND NETWORKS 2008年第4期10卷 396-402页

作者： Wang, Yu Henning, Ian D. Univ Essex Dept Comp & Elect Syst Colchester CO4 3SQ Essex England

The use of network coding in wireless networks has been proposed in the literature for energy efficient broadcast. However, the decoding complexity of existing algorithms is too high for low-complexity devices. In this work we formalize the all-to-all information exchange problem and shows how to optimize the transmission scheme in terms of energy efficiency. Furthermore, we prove by construction that there exists O(1)-complexity network coding algorithms for grid networks which can achieve such optimality. We also present low-complexity heuristics for random-topology networks. Simulation results show that network coding algorithms outperforms forwarding algorithms in most cases.

关键词： Broadcast information exchange low-complexity algorithms network coding wireless network

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Sparsity-aware space-time adaptive processing algorithms with L₁-norm regularisation for airborne radar

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IET SIGNAL PROCESSING 2012年第5期6卷 413-423页

作者： Yang, Z. de Lamare, R. C. Li, X. Natl Univ Def Technol Elect Sci & Engn Sch Res Inst Space Elect Changsha 410073 Hunan Peoples R China Univ York Dept Elect Commun Res Grp York YO10 5DD N Yorkshire England

This study proposes novel sparsity- aware space-time adaptive processing (SA-STAP) algorithms with L-1-norm regularisation for airborne phased-array radar applications. The proposed SA-STAP algorithms suppose that a number of samples of the full-rank STAP datacube are not meaningful for processing and the optimal full-rank STAP filter weight vector is sparse, or nearly sparse. The core idea of the proposed method is imposing a sparse regularisation (L-1-norm type) to the minimum variance STAP cost function. Under some reasonable assumptions, the authors firstly propose an L-1-based sample matrix inversion to compute the optimal filter weight vector. However, it is impractical because of its matrix inversion, which requires a high computational cost when using a large phased-array antenna. In order to compute the STAP parameters in a cost-effective way, the authors devise low-complexity algorithms based on conjugate gradient techniques. A computational complexity comparison with the existing algorithms and an analysis of the proposed algorithms are conducted. Simulation results with both simulated and the Mountain-Top data demonstrate that fast signal-to-interference-plus-noise-ratio convergence and good performance of the proposed algorithms are achieved.

关键词： radar signal processing Electromagnetic compatibility and interference Linear algebra (numerical analysis) optimal full-rank STAP filter weight vector phased array radar minimum variance STAP cost function antenna phased arrays large phased-array antenna Radar equipment, systems and applications SA-STAP algorithms matrix inversion mountain-top data Filtering methods in signal processing L1-based sample matrix inversion space-time adaptive processing radar interference Antenna arrays airborne phased-array radar applications L1-norm regularisation full-rank STAP datacube Interpolation and function approximation (numerical analysis) fast signal-to-interference-plus-noise-ratio convergence computational complexity low-complexity algorithms sparsity-aware space-time adaptive processing algorithms conjugate gradient methods filtering theory airborne radar conjugate gradient techniques

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Multibeam Digital Array Receiver Using a 16-Point Multiplierless DFT Approximation

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2019年第2期67卷 925-933页

作者： Ariyarathna, Viduneth Coelho, Diego F. G. Pulipati, Sravan Cintra, Renato J. Bayer, Fabio M. Dimitrov, V. S. Madanayake, Arjuna Univ Akron Dept Elect & Comp Engn Akron OH 44325 USA Florida Int Univ Dept Elect & Comp Engn Miami FL 33199 USA Univ Fed Pernambuco Dept Estat Signal Proc Grp BR-50670901 Recife PE Brazil Univ Calgary Dept Elect & Comp Engn Calgary AB T2N 1N4 Canada Univ Fed Santa Maria Dept Estat Lab Ciencias Espaciais Santa Maria BR-97105 Santa Maria RS Brazil IOTA Fdn D-10405 Berlin Germany

An N-element array with receivers subject to an N-point spatial fast Fourier transform (FFT) leads to N directionally orthogonal radio frequency (RF) beams. FFTs are fast algorithms for computing the N-point discrete Fourier transform (DFT) at reduced complexity. The brute-force computation of a DFT requires O(N-2) multiplications while an FFT provides the same computation at O(N log N) multiplications. The digital chip area and power consumption of the DFT computation are still dominated by the multipliers required by the FFT used. In this paper, an approximation to the 16-point DFT is proposed which maintains mathematical properties close to the ideal 16-point DFT to obtain 16 RF beams by computing an approximate spatial DFT in every clock cycle at significantly lower area and power in the digital realization. The proposed approximation can be implemented using FFT-like fast algorithms that are multiplierless, thereby further reducing the digital chip area and power consumption associated with multiplication in a conventional FFT approach to zero. A 16-beam beamformer employing a 16-element linear array of patch antennas, direct-conversion receivers, and a Xilinx Virtex-6 field-programmable gate array-based real-time digital back-end clocked at 240 MHz are described as an example realization of 16 complex-valued (IQ) receive-mode RF beams, centered at 2.4 GHz with 120 MHz of bandwidth per beam.

关键词： Beamforming low-complexity algorithms multibeam spatial DFT

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Mixed modified weighted bit-flipping decoding of low-density parity-check codes

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IET COMMUNICATIONS 2015年第2期9卷 283-290页

作者： Huang, Haiyi Wang, Yige Wei, Gang S China Univ Technol Sch Elect & Informat Engn Guangzhou 510641 Guangdong Peoples R China

In this study, a new weighted bit-flipping (WBF) algorithm called mixed modified WBF (MM-WBF) decoding is proposed for low-density parity-check codes. The new algorithm is built by mixing two WBF algorithms, one acting as the main decoding algorithm and the other acting as the auxiliary. Simulation results show that the new algorithm achieves a notable performance gain over reliability ratio-based WBF, improved M-WBF and low-complexity WBF algorithms with almost the same computational complexity. Compared with some belief-propagation-based algorithms, MM-WBF also provides an appealing performance against complexity trade-off.

关键词： parity check codes decoding computational complexity belief-propagation-based algorithms computational complexity low-complexity algorithms reliability ratio performance gain MM-WBF decoding LDPC codes low-density parity-check codes mixed modified weighted bit-flipping decoding

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Improved 8-Point Approximate DCT for Image and Video Compression Requiring Only 14 Additions

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2014年第6期61卷 1727-1740页

作者： Potluri, Uma Sadhvi Madanayake, Arjuna Cintra, Renato J. Bayer, Fabio M. Kulasekera, Sunera Edirisuriya, Amila Univ Akron Dept Elect & Comp Engn Akron OH 44325 USA Univ Fed Pernambuco Dept Estat Signal Proc Grp Recife PE Brazil Univ Fed Santa Maria Dept Estat BR-97119900 Santa Maria RS Brazil Univ Fed Santa Maria Lab Ciencias Espaciais Santa Maria LACESM BR-97119900 Santa Maria RS Brazil

Video processing systems such as HEVC requiring low energy consumption needed for the multimedia market has lead to extensive development in fast algorithms for the efficient approximation of 2-D DCT transforms. The DCT is employed in a multitude of compression standards due to its remarkable energy compaction properties. Multiplier-free approximate DCT transforms have been proposed that offer superior compression performance at very low circuit complexity. Such approximations can be realized in digital VLSI hardware using additions and subtractions only, leading to significant reductions in chip area and power consumption compared to conventional DCTs and integer transforms. In this paper, we introduce a novel 8-point DCT approximation that requires only 14 addition operations and no multiplications. The proposed transform possesses low computational complexity and is compared to state-of-the-art DCT approximations in terms of both algorithm complexity and peak signal-to-noise ratio. The proposed DCT approximation is a candidate for reconfigurable video standards such as HEVC. The proposed transform and several other DCT approximations are mapped to systolic-array digital architectures and physically realized as digital prototype circuits using FPGA technology and mapped to 45 nm CMOS technology.

关键词： Approximate DCT low-complexity algorithms image compression HEVC low power consumption

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On the complexity Reduction of Uplink Sparse Code Multiple Access for Spatial Modulation

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IEEE TRANSACTIONS ON COMMUNICATIONS 2020年第11期68卷 6962-6974页

作者： Al-Nahhal, Ibrahim Dobre, Octavia A. Ikki, Salama Mem Univ St Johns Fac Engn & Appl Sci St John NF A1B 3X5 Canada Al Azhar Univ Fac Engn Cairo 11651 Egypt Lakehead Univ Dept Elect Engn Thunder Bay ON P7B 5E1 Canada

Multi-user spatial modulation (SM) assisted by sparse code multiple access (SCMA) has been recently proposed to provide uplink high spectral efficiency transmission. The message passing algorithm (MPA) is employed to detect the transmitted signals, which suffers from high complexity. This paper proposes three low-complexity algorithms for the first time to the SM-SCMA. The first algorithm is referred to as successive user detection (SUD), while the second algorithm is the modified version of SUD, namely modified SUD (MSUD). Then, for the first time, the tree-search of the SM-SCMA is constructed. Based on that tree-search, another variant of the sphere decoder (SD) is proposed for the SM-SCMA, referred to as fixed-complexity SD (FCSD). SUD provides a benchmark for decoding complexity at the expense of bit-error-rate (BER) performance. Further, MSUD slightly increases the complexity of SUD with a significant improvement in BER performance. Finally, FCSD provides a near-optimum BER with a considerable reduction of the complexity compared to the MPA decoder and also supports parallel hardware implementation. The proposed algorithms provide flexible design choices for practical implementation based on system design demands. The complexity analysis and Monte-Carlo simulations of the BER are provided for the proposed algorithms.

关键词： complexity theory Decoding Transmitting antennas Receiving antennas Uplink Iterative decoding Sparse code multiple access (SCMA) spatial modulation (SM) message passing algorithm (MPA) low-complexity algorithms complexity analysis

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low-complexity transcoding algorithm from H.264/AVC to SVC using data mining

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2013年第1期2013卷 1页

作者： Garrido-Cantos, Rosario De Cock, Jan Luis Martinez, Jose Van Leuven, Sebastian Cuenca, Pedro Garrido, Antonio Univ Castilla La Mancha Albacete Res Inst Informat Albacete 02071 Spain Ghent Univ IBBT Dept Elect & Informat Syst Multimedia Lab B-9050 Ghent Belgium

Nowadays, networks and terminals with diverse characteristics of bandwidth and capabilities coexist. To ensure a good quality of experience, this diverse environment demands adaptability of the video stream. In general, video contents are compressed to save storage capacity and to reduce the bandwidth required for its transmission. Therefore, if these compressed video streams were compressed using scalable video coding schemes, they would be able to adapt to those heterogeneous networks and a wide range of terminals. Since the majority of the multimedia contents are compressed using H.264/AVC, they cannot benefit from that scalability. This paper proposes a low-complexity algorithm to convert an H.264/AVC bitstream without scalability to scalable bitstreams with temporal scalability in baseline and main profiles by accelerating the mode decision task of the scalable video coding encoding stage using machine learning tools. The results show that when our technique is applied, the complexity is reduced by 87% while maintaining coding efficiency.

关键词： low-complexity algorithms Scalable video coding H.264/AVC Transcoding Temporal scalability Data mining

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A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2022年第3期53卷 1384页

作者： Comminiello, Danilo Nezamdoust, Alireza Scardapane, Simone Scarpiniti, Michele Hussain, Amir Uncini, Aurelio Sapienza Univ Rome Dept Informat Engn Elect & Telecommun I-00184 Rome Italy Edinburgh Napier Univ Sch Comp Edinburgh EH10 5DT Midlothian Scotland

Nonlinear models are known to provide excellent performance in real-world applications that often operate in nonideal conditions. However, such applications often require online processing to be performed with limited computational resources. To address this problem, we propose a new class of efficient nonlinear models for online applications. The proposed algorithms are based on linear-in-the-parameters (LIPs) nonlinear filters using functional link expansions. In order to make this class of functional link adaptive filters (FLAFs) efficient, we propose low-complexity expansions and frequency-domain adaptation of the parameters. Among this family of algorithms, we also define the partitioned-block frequency-domain FLAF (FD-FLAF), whose implementation is particularly suitable for online nonlinear modeling problems. We assess and compare FD-FLAFs with different expansions providing the best possible tradeoff between performance and computational complexity. Experimental results prove that the proposed algorithms can be considered as an efficient and effective solution for online applications, such as the acoustic echo cancellation, even in the presence of adverse nonlinear conditions and with limited availability of computational resources.

关键词： Efficient adaptive filtering frequency-domain adaptive filters (FDAFs) functional links low-complexity algorithms nonlinear adaptive filters

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A low-complexity frame synchronization and frequency offset compensation scheme for OFDM systems over fading channels

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 1999年第5期48卷 1596-1609页

作者： Hsieh, MH Wei, CH Natl Chiao Tung Univ Dept Elect Engn Hsinchu Taiwan

dThis paper presents a fast low-complexity synchronization scheme for orthogonal frequency division multiplexing (OFDM) systems over fading channels. By utilizing the guard interval in OFDM signals, the Frame synchronization and the frequency offset estimation are considered simultaneously. The Implementation can be simplified by only using the sign bits of the in-phase and the quadrature components of the received OFDM signal for frame synchronization and frequency offset compensation. A frequency-offset independent frame synchronization algorithm is derived, and a low-complexity frequency offset estimator based on the synchronized correlator output is presented in this paper. Due to the subcarrier ambiguity in the guard-interval-based (GIB) frequency detector, the maximum correctable frequency range is limited to +/- 1/2 of the subcarrier spacing. In this paper, we also present a new frequency acquisition scheme that can solve the subcarrier ambiguity problem and extend the frequency acquisition range to nearly a half of the useful OFDM signal bandwidth.

关键词： frame synchronization frequency offset compensation low-complexity algorithms OFDM

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