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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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Protecting the Future of Information: LOCO Coding With Error Detection for DNA Data Storage

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IEEE TRANSACTIONS ON MOLECULAR BIOLOGICAL AND MULTI-SCALE COMMUNICATIONS 2024年第2期10卷 317-333页

作者： Irimagzi, Canberk Uslan, Yusuf Hareedy, Ahmed Middle East Tech Univ Inst Appl Math TR-06800 Ankara Turkiye Middle East Tech Univ Dept Elect & Elect Engn TR-06800 Ankara Turkiye

From the information-theoretic perspective, DNA strands serve as a storage medium for 4-ary data over the alphabet {A, T, G, C} . DNA data storage promises formidable information density, long-term durability, and ease of replicability. However, information in this intriguing storage technology might be corrupted because of error-prone data sequences as well as insertion, deletion, and substitution errors. Experiments have revealed that DNA sequences with long homopolymers and/or with low GC-content are notably more subject to errors upon storage. In order to address this biochemical challenge, constrained codes are proposed for usage in DNA data storage systems, and they are studied in the literature accordingly. This paper investigates the utilization of the recently-introduced method for designing lexicographically-ordered constrained (LOCO) codes in DNA data storage to improve performance. LOCO codes offer capacity-achievability, low complexity, and ease of reconfigurability. This paper introduces novel constrained codes, namely DNA LOCO (D-LOCO) codes, over the alphabet {A, T, G, C} with limited runs of identical symbols. Due to their ordered structure, these codes come with an encoding-decoding rule we derive, which provides simple and affordable encoding-decoding algorithms. In terms of storage overhead, the proposed encoding-decoding algorithms outperform those in the existing literature. Our algorithms are based on small-size adders, and therefore they are readily reconfigurable. D-LOCO codes are intrinsically balanced, which allows us to achieve balanced AT- and GC-content over the entire DNA strand with minimal rate penalty. Moreover, we propose four schemes to bridge consecutive codewords, three of which guarantee single substitution error detection per codeword. We examine the probability of undetecting errors over a presumed symmetric DNA storage channel subject to substitution errors only. We also show that D-LOCO codes are capacity-achieving and that

关键词： Codes DNA Encoding Symbols Memory Table lookup Signal processing algorithms Constrained codes low-complexity algorithms reconfigurable coding LOCO codes homopolymer run balancing error-detection DNA data storage

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Design of Multichannel Spectrum Intelligence Systems Using Approximate Discrete Fourier Transform Algorithm for Antenna Array-Based Spectrum Perception Applications

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algorithms 2024年第8期17卷 338页

作者： Madanayake, Arjuna Lawrance, Keththura Kumarasiri, Bopage Umesha Sivasankar, Sivakumar Gunaratne, Thushara Edussooriya, Chamira U. S. Cintra, Renato J. Florida Int Univ Dept Elect & Comp Engn Miami FL 33174 USA Natl Res Council Canada Herzberg Astron & Astrophys Res Ctr Penticton BC V0H 1K0 Canada Univ Moratuwa Dept Elect & Telecommun Engn Moratuwa 10400 Sri Lanka Univ Fed Pernambuco Dept Technol BR-55015 Caruaru PE Brazil

The radio spectrum is a scarce and extremely valuable resource that demands careful real-time monitoring and dynamic resource allocation. Dynamic spectrum access (DSA) is a new paradigm for managing the radio spectrum, which requires AI/ML-driven algorithms for optimum performance under rapidly changing channel conditions and possible cyber-attacks in the electromagnetic domain. Fast sensing across multiple directions using array processors, with subsequent AI/ML-based algorithms for the sensing and perception of waveforms that are measured from the environment is critical for providing decision support in DSA. As part of directional and wideband spectrum perception, the ability to finely channelize wideband inputs using efficient Fourier analysis is much needed. However, a fine-grain fast Fourier transform (FFT) across a large number of directions is computationally intensive and leads to a high chip area and power consumption. We address this issue by exploiting the recently proposed approximate discrete Fourier transform (ADFT), which has its own sparse factorization for real-time implementation at a low complexity and power consumption. The ADFT is used to create a wideband multibeam RF digital beamformer and temporal spectrum-based attention unit that monitors 32 discrete directions across 32 sub-bands in real-time using a multiplierless algorithm with low computational complexity. The output of this spectral attention unit is applied as a decision variable to an intelligent receiver that adapts its center frequency and frequency resolution via FFT channelizers that are custom-built for real-time monitoring at high resolution. This two-step process allows the fine-gain FFT to be applied only to directions and bands of interest as determined by the ADFT-based low-complexity 2D spacetime attention unit. The fine-grain FFT provides a spectral signature that can find future use cases in neural network engines for achieving modulation recognition, IoT device identif

关键词： approximate discrete Fourier transform wideband spectrum perception wideband multibeam RF digital beamforming low-complexity algorithms

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low-complexity Linear Decoupling of Users for Uplink Massive MU-MIMO Detection 99

Low-Complexity Linear Decoupling of Users for Uplink Massive...

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IEEE 99th Vehicular Technology Conference (VTC-Spring)

作者： Sowmya, S. Muthukrishnan, Gokularam Giridhar, K. Indian Inst Technol Madras Dept Elect Engn TelWiSe Grp Chennai 600036 Tamil Nadu India

ISBN: (纸本)9798350387414

Massive MIMO (mMIMO) enables users with different requirements to get connected to the same base station (BS) on the same set of resources. In the uplink of Multiuser massive MIMO (MU-mMIMO), while such heterogeneous users are served, decoupling facilitates the use of user-specific detection schemes. In this paper, we propose a low-complexity linear decoupling scheme called Sequential Decoupler (SD), which aids in the parallel detection of each user's data stream. The proposed algorithm shows significant complexity reduction. Simulations reveal that the complexity of the proposed scheme is only 0.15% of the conventional Singular Value Decomposition (SVD) based decoupling and is about 47% of the pseudo-inverse based decoupling schemes when 80 users with two antennas each are served by the BS. Also, the proposed scheme is scalable when new users are added to the system and requires fewer operations than computing the decoupler all over again. Further numerical analyses indicate that the proposed scheme achieves significant complexity reduction without any degradation in performance and is a promising low-complex alternative to the existing decoupling schemes.

关键词： Massive Multi-User MIMO Decoupled Detection low-complexity algorithms Uplink Communication Left Nullspace Sequential Estimation

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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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low-complexity JPEG quantization table requiring only bit-shift operations

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IMAGING SCIENCE JOURNAL 2022年第8期70卷 556-563页

作者： Araar, Chaouki Chabbi, Samir Freres Mentouri Constantine 1 Univ Elect Dept POB 325 Ain Bey Way Constantine 25017 Algeria Mohamed Cher Messaadia Univ Souk Ahras Comp Sci Dept Souk Ahras Algeria

In this paper, a low-complexity quantization table is proposed for the baseline JPEG encoder. The proposed scheme does not require any multiplications or additions;only bit-shift operations are involved. The computational complexity should be drastically reduced without almost incurring any significant performance loss. The resulting approximate quantization table has extremely low arithmetic cost and is compared to state-of-the-art schemes in terms of computational complexity. Comparisons showed that our proposal exhibits better or similar results. The proposed low-complexity quantization table is also investigated in image compression context. It could outperforms other related schemes in low and high-compression scenarios. Comparisons with respect to average PSNR and SSIM are conducted. Experiment outcomes show up to 4.03 dB improvement in average PSNR over the state-of-the-art competitor. The proposed quantization table has a considerably lower computational cost while maintaining much higher image quality.

关键词： Image compression JPEG quantization table approximate quantization power-of-two quantization low-complexity algorithms

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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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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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Optimum low-complexity Decoder for Spatial Modulation

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2019年第9期37卷 2001-2013页

作者： M-Nahhal, Ibrahim Basar, Ertugrul Dobre, Octavia A. Ikki, Salama Mem Univ Fac Engn & Appl Sci St John NF A1B 3X5 Canada Koc Univ Commun Res & Innovat Lab CoreLab Dept Elect & Elect Engn TR-34450 Istanbul Turkey Lakehead Univ Dept Elect Engn Thunder Bay ON P7B 5E1 Canada

In this paper, a novel low-complexity detection algorithm for spatial modulation (SM), referred to as the minimum-distance of maximum-length (m-M) algorithm, is proposed and analyzed. The proposed m-M algorithm is a smart searching method that is applied for the SM tree-search decoders. The behavior of the m-M algorithm is studied for three different scenarios: 1) perfect channel state information at the receiver side (CSIR);2) imperfect CSIR of a fixed channel estimation error variance;and 3) imperfect CSIR of a variable channel estimation error variance. Moreover, the complexity of the m-M algorithm is considered as a random variable, which is carefully analyzed for all scenarios, using probabilistic tools. Based on a combination of the sphere decoder (SD) and ordering concepts, the m-M algorithm guarantees to find the maximum-likelihood (ML) solution with a significant reduction in the decoding complexity compared with SM-ML and existing SM-SD algorithms;it can reduce the complexity up to 94% and 85% in the perfect CSIR and the worst scenario of imperfect CSIR, respectively, compared with the SM-ML decoder. The Monte Carlo simulation results are provided to support our findings as well as the derived analytical complexity reduction expressions.

关键词： Multiple-input multiple-output (MIMO) systems spatial modulation (SM) maximum likelihood (ML) decoder sphere decoder (SD) low-complexity algorithms complexity analysis

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Power Consumption-Oriented Resource Allocation Strategy for Ultra-Reliable low-Latency Communication

Power Consumption-Oriented Resource Allocation Strategy for ...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Xie, Yuncong Ren, Pinyi Wang, Yichen Li, Jiuchao Xi An Jiao Tong Univ Dept Informat & Commun Engn Xian 710049 Shaanxi Peoples R China China Acad Space Technol Inst Telecommun Satellite Beijing 100094 Peoples R China

ISBN: (纸本)9781538676462

In this paper, we propose the optimal resource allocation strategy for uplink ultra-reliable low-latency communication (URLLC) networks. Specifically, by employing the quality-of-service (QoS)-aware packet scheduling mechanism which is built upon the theory of maximum achievable rate under finite blocklength regime, the QoS requirement is described for uplink URLLC transmissions. Then, we formulate the non-convex optimization problem which aims at minimizing the total transmit power consumption of the URLLC network while meeting the QoS requirement as well as the channel assignment and transmit power constraints. By adopting the bipartite weighted graph theory, we design the ORA-KMM algorithm to obtain the optimal joint power and channel allocation strategy. Moreover, two low-complexity suboptimal algorithms, namely BCCG and SSG-LDF, are developed and the impact of spatial diversity on transmission reliability and total transmit power consumption are also analyzed. Simulation results show that our proposed optimal resource allocation strategy can achieve better performance as compared to the developed suboptimal schemes.

关键词： Ultra-Reliable low-Latency Communication Resource Allocation low-complexity algorithms

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