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Latest Publications

Galicia Cota, M., Merchant, F. and Leupers, R.: A Parallel SystemC Virtual Platform for Neuromorphic Architectures, in ISQED, Apr. 2022, accepted for publication ©2022 IEEE


Galicia Cota, M., Menzel, S., Merchant, F., Müller, M., Chen, H.-Y. , Zhao, Q.-T. , Cüppers, F. , Jalil, A. R. , Shu, Q. , Schüffelgen, P., Mussler, G., Funck, C. , Lanius, C. , Wiefels, S. , von Witzleben, M. , Bengel, C. , Kopperberg, N. , Ziegler, T. , Walied, R. , Krüger, A. , Pöhls, L. , Dittmann, R. , Hoffmann-Eifert, S. , Rana, V., Grützmacher, D. , Wuttig, M. , Wouters, D. , Vescan, A. , Gemmeke, T. , Knoch, J. , Lemme, M. , Leupers, R. and Waser, R.: NEUROTEC I: Neuro-inspired Artificial Intelligence Technologies for the Electronics of the Future, in Proceedings of the Conference on Design, Automation & Test in Europe (DATE), Mar. 2022, accepted for publication ©2022 IEEE


Staudigl, F., Al Indari, H., Schön, D., Šišejković, D., Merchant, F., Joseph, J. M., Rana, V., Menzel, S. and Leupers, R.: NeuroHammer: Inducing Bit-Flips in Memristive Crossbar Memories, in Proceedings of the Conference on Design, Automation & Test in Europe (DATE), 2022, accepted for publication


Reimann, L. M., Hanel, L., Šišejković, D., Merchant, F. and Leupers, R.: QFlow: Quantitative Information Flow for Security-Aware Hardware Design in Verilog, in Proceedings of the International Conference on Computer Design (ICCD) , pp. 603-607, Oct. 2021, 10.1109/ICCD53106.2021.00097 ©2021 IEEE


Joseph, J. M., Baloglu, M. S. , Pan, Y., Leupers, R. and Bamberg, L.: NEWROMAP: mapping CNNs to NoC-interconnected self-contained data-flow accelerators for edge-AI, in NOCS '21: Proceedings of the 15th IEEE/ACM International Symposium on Networks-on-Chip, p. 15–20, Oct. 2021, 10.1145/3479876.3481591


Staudigl, F., Merchant, F. and Leupers, R.: A Survey of Neuromorphic Computing-in-Memory: Architectures, Simulators and Security, in IEEE Design & Test, Sep. 2021, 10.1109/MDAT.2021.3102013 ©2021 IEEE


He, Z., Huang, H., Yang, J., Gui, G., Ohtsuki, T., Abedisi, B. and Gacanin, H.: Fast Beamforming Design Method for IRS-Aided MISO Systems, in IEEEVTC 2021-Fall, 27 Sept. - 30 Sept. 2021, Virtual conference, pp. 1-5, Sep. 2021, 10.1109/VTC2021-Fall52928.2021.9625497


Liang, Z. and Ascheid, G.: Subcarrier Grouping with Linear Time-Domain Compensation for Low-Complexity Millimeter Wave OFDM Multiuser Systems, in Proceedings of IEEE Vehicular Technology Conference (VTC-Fall), pp. 1-5, IEEE, Sep. 2021, 10.1109/VTC2021-Fall52928.2021.9625504 ©2021 IEEE


Joseph, J. M., Bamberg, L., Hajjar, I., Perjikolaei, B., García-Ortiz, A. and Pionteck, T.: Ratatoskr: An Open-Source Framework for In-Depth Power, Performance, and Area Analysis and Optimization in 3D NoCs, in ACM Trans. Model. Comput. Simul., Vol. 32, No. 1, Association for Computing Machinery, New York, NY, USA, p. 21, Sep. 2021, ISSN: 1049-3301, 10.1145/3472754


Nasser, A., Muta, O., Gacanin, H. and Elsabrouty, M.: Non-Cooperative Game Based Power Allocation for Energy and Spectrum Efficient Downlink NOMA HetNets, in IEEE Access, Vol. 9, pp. 136334-136345, Sep. 2021, 10.1109/ACCESS.2021.3116706 ©2021 IEEE


Shi, W., Sun, Y., Liu, M., Xu, H., Gui, G., Ohtsuki, T., Abedisi, B., Gacanin, H. and Adebisi, B.: Joint UL/DL Resource Allocation for UAV-Aided Full-Duplex NOMA Communications, in IEEE Transactions on Communications, Vol. 69, No. 12, 10.1109/TCOMM.2021.3110298, pp. 8474-8487, Sep. 2021, 10.1109/TCOMM.2021.3110298 ©2021 IEEE


Zhang, Y., Sun, J., Gui, G., Gacanin, H. and Sari, H.: A Generalized Channel Dataset Generator for 5G New Radio Systems Based on Ray-Tracing, in IEEE Wireless Communications Letters, Vol. 10, No. 11, pp. 2402-2406, Aug. 2021, 10.1109/LWC.2021.3101908 ©2021 IEEE


Šišejković, D., Merchant, F., Reimann, L. M. and Leupers, R.: Deceptive Logic Locking for Hardware Integrity Protection against Machine Learning Attacks, in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Jul. 2021, ISSN: 1937-4151, 10.1109/TCAD.2021.3100275 ©2021 IEEE


Hadzi-Velkov, Z. , Pejoski, S., Zlatanov, N. and Gacanin, H.: Designing Wireless Powered Networks assisted by Intelligent Reflecting Surfaces with Mechanical Tilt, in IEEE Communications Letters, Jul. 2021, 10.1109/LCOMM.2021.3098128 ©2021 IEEE


Chen, X., Liu, M., Gui, G., Abedisi, B., Gacanin, H. and Sari, H.: Complex Deep Neural Network Based Intelligent Signal Detection Methods for OFDM-IM Systems, in The 2021 Joint EuCNC & 6G Summit, 8-11 June 2021, Porto, Portugal., Jun. 2021, 10.1109/EuCNC/6GSummit51104.2021.9482564


Wang, J., Gui, G., Ohtsuki, T., Abedisi, B., Gacanin, H. and Sari, H.: Compressive Sampled CSI Feedback Method Based on Deep Learning for FDD Massive MIMO Systems, in IEEE Transactions on Communications, pp. 1-1, Jun. 2021, 10.1109/TCOMM.2021.3086525 ©2021 IEEE


Xu, Y., Gui, G., Ohtsuki, T., Gacanin, H., Abedisi, B., Sari, H. and Adachi, F.: Robust Resource Allocation for Two-Tier HetNets: An Interference-Efficiency Perspective, in IEEE Transactions on Green Communications and Networking, IEEE, pp. 1-1, Jun. 2021, 10.1109/TGCN.2021.3090592 ©2021 IEEE


Wang, Y., Gui, G., Gacanin, H., Abedisi, B., Sari, H. and Adachi, F.: Federated Learning for Automatic Modulation Classification under Class Imbalance and Varying Noise Condition, in IEEE Transactions on Cognitive Communications and Networking , IEEE, pp. 1 -1, Jun. 2021, 10.1109/TCCN.2021.3089738 ©2021 IEEE


Song, X. , Wang, J., Wang, J., Gui, G., Ohtsuki, T., Gacanin, H. and Sari, H.: SALDR: Joint Self-Attention Learning and Dense Refine for Massive MIMO CSI Feedback With Multiple Compression Ratio, in IEEE Wireless Communications Letters, Vol. 9, No. 10, pp. 1899-1903, Jun. 2021, 10.1109/LWC.2021.3085317 ©2021 IEEE


Šišejković, D., Merchant, F., Reimann, L. M., Srivastava, H., Hallawa, A. and Leupers, R.: Challenging the Security of Logic Locking Schemes in the Era of Deep Learning: A Neuroevolutionary Approach, in ACM Journal on Emerging Technologies in Computing Systems (JETC), Vol. 17, No. 3, Association for Computing Machinery, p. 26, May. 2021, ISSN: 1550-4832, 10.1145/3431389


Zhao, R. , Yin, J., Xue, Z., Gui, G., Abedisi, B., Ohtsuki, T., Gacanin, H. and Sari, H.: An Efficient Intrusion Detection Method Based on Dynamic Autoencoder, in IEEE Wireless Communications Letters, pp. 1-1, May. 2021, 10.1109/LWC.2021.3077946 ©2021 IEEE


Zeng, J., Sun, J., Gui, G., Abedisi, B., Ohtsuki, T., Gacanin, H. and Sari, H.: Downlink CSI Feedback Algorithm with Deep Transfer Learning for FDD Massive MIMO Systems, in IEEE Transactions on Cognitive Communications and Networking, Vol. 7, No. 4, pp. 1253-1265, May. 2021, ISSN: 2332-7731, 10.1109/TCCN.2021.3084409 ©2021 IEEE


Saxena, V., Reddy, A., Jonathan, N., Gustafson, J. L., Sangeeth, N., Leupers, R. and Merchant, F.: Brightening the Optical Flow through Posit Arithmetic, in International Symposium on Quality Electronic Design (ISQED), Apr. 2021, 10.1109/ISQED51717.2021.9424360 ©2021 IEEE


Yin, Y., Liu, M., Gacanin, H., Sari, H. and Adachi, F.: Cross-Layer Resource Allocation for UAV-Assisted Wireless Caching Networks with NOMA, in IEEE Transactions on Vehicular Technology, IEEE, Mar. 2021, 10.1109/TVT.2021.3064032 ©2021 IEEE


Popoola, S., Abedisi, B., Hammoudeh, M., Gui, G. and Gacanin, H.: Hybrid Deep Learning for Botnet Attack Detection in the Internet-of-Things Networks, in IEEE Internet of Things Journal, Vol. 8, No. 6, IEEE, Mar. 2021, 10.1109/JIOT.2020.3034156


Führ (Onnebrink), G.: MPSoC power-performance trade-off : strategies for SW mapping optimisation, Ph. D. Dissertation RWTH Aachen Univeristy, Mar. 2021, 10.18154/RWTH-2021-03407


Alouani, I., BEN KHALIFA, A., Merchant, F. and Leupers, R.: An Investigation on Inherent Robustness of Posit Data Representation, in Proceedings of the International Conference on VLSI Design (VLSID), pp. 276-281, Feb. 2021, 10.1109/VLSID51830.2021.00052 ©2021 IEEE


Xu, Y., Gui, G., Gacanin, H. and Adachi, F.: A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends, and Challenges, in IEEE Communications Surveys Tutorials, Vol. 23, No. 2, pp. 668 - 695, Feb. 2021, 10.1109/COMST.2021.3059896


Wang, J., Liu, M., Sun, J., Gui, G., Gacanin, H., Sari, H. and Adachi, F.: Multiple Unmanned Aerial Vehicles Deployment and User Pairing for Non-Orthogonal Multiple Access Schemes, in IEEE Internet of Things Journal, Vol. 8, No. 3, pp. 1883-1895, Feb. 2021, 10.1109/JIOT.2020.3015702 ©2021 IEEE


Nasser, A., Muta, O. and Gacanin, H.: Joint User Pairing and Power Allocation with Compressive Sensing in NOMA Systems, in IEEE Wireless Communications Letters, Vol. 10, No. 1, pp. 1-1, Jan. 2021, ISSN: 2162-2345, 10.1109/LWC.2020.3023619 ©2021 IEEE


Yin, Y., Liu, M., Gui, G., Gacanin, H. and Adachi, F.: QoS-Oriented Dynamic Power Allocation in NOMA-based Wireless Caching Networks, in IEEE Wireless Communications Letters, Vol. 10, No. 1, pp. 82-86, Jan. 2021, ISSN: 2162-2345, 10.1109/LWC.2020.3021204 ©2021 IEEE


Copic, M., Leupers, R. and Ascheid, G.: Leveraging Nondeterminism in Mixed Classic/Adaptive AUTOSAR Systems for Runnable Configuration, in Design Automation Conference (DAC), Work-in-Progress Session, 2021, accepted for publication


Galicia, M., BanaGozar, A., Sturm, K. J. X., Staudigl, F., Stuijk, S., Corporaal, H. and Leupers, R.: NeuroVP: A System-Level Virtual Platform for Integration of Neuromorphic Accelerators, in International Conference on Communications and Technology, IEEE SOCC, 2021, accepted for publication ©2021 IEEE


Sun, J., Gui, G., Sari, H., Gacanin, H. and Adachi, F.: Aviation Data Lake : Using Side Information to Enhance Future Air-Ground Vehicle Networks, in IEEE Vehicular Technology Magazine, 2021, 10.1109/MVT.2020.3014598 ©2021 IEEE


Jünger, L., Bianco, C., Niederholtmeyer, K., Petras, D. and Leupers, R.: Optimizing Temporal Decoupling using Event Relevance, in Proceedings of the Asia South Pacific Design Automation Conference (ASP-DAC), 2021, 10.1145/3394885.3431419


Rai, S., Garg, S., Pilato, C., Herdt, V., Moussavi, E., Šišejković, D., Karri, R., Drechsler, R., Merchant, F. and Kumar, A.: Vertical IP Protection of the Next-Generation Devices: Quo Vadis?, in Proceedings of the Conference on Design, Automation & Test in Europe (DATE), IEEE, 2021, 10.23919/DATE51398.2021.9474132


Polian, I., Altmann, F., Arul, T., Boit, C., Brederlaw, R., Davi, L., Drechsler, R., Du, N., Eisenbarth, T., Gü­ney­su, T., Hermann, S., Hiller, M., Leupers, R., Merchant, F., Mussenbrock, T., Katzenbeisser, S., Kumar, A., Kunz, W., Mikolajick, T., Pachauri, V., Seifert, J.-P., Torres, F. S. and Trommer, J.: Nano Security: From Nano-Electronics to Secure Systems, in Proceedings of the Conference on Design, Automation & Test in Europe (DATE), IEEE, 2021, 10.23919/DATE51398.2021.9474187


Joseph, J. M., Bamberg, L., Geonhwa, J., Chien, R.-T., Leupers, R., García-Ortiz, A., Krishna, T. and Pionteck, T.: Bridging the F requency Gap in Heterogeneous 3D SoCs through Technology-Specific NoC Router Architectures, in Proceedings of the Asia South Pacific Design Automation Conference (ASP-DAC), 2021, 10.1145/3394885.3431421


Joseph, J. M., Samajdar, A., Zhu, L., Leupers, R., Lim, S.-K., Pionteck, T. and Krishna, T.: Architecture, Dataflow and Physical Design Implications of 3D-ICs for DNN-Accelerators, in International Symposium on Quality Electronic Design (ISQED), 2021, 10.1109/ISQED51717.2021.9424349


Merchant, F., Šišejković, D., Reimann, L. M., Yasotharan, K., Grass, T. and Leupers, R.: ANDROMEDA: An FPGA Based RISC-V MPSoC Exploration Framework, in Proceedings of the International Conference on VLSI Design (VLSID), 2021, 10.1109/VLSID51830.2021.00051 ©2021 IEEE


Hou, W., Sun, J., Gui, G., Ohtsuki, T., Engelhardt, T., Gacanin, H. and Sari, H.: Federated Learning for DL-CSI Prediction in FDD Massive MIMO Systems, in IEEE Wireless Communications Letters, pp. 1-1, 2021, 10.1109/LWC.2021.3081695 ©2021 IEEE


Yu, W., Gui, G., Ohtsuki, T., Gacanin, H., Dobre, O. and Poor, H. V.: An Efficient Specific Emitter Identification Method Based on Complex-Valued Neural Networks and Network Compression, in IEEE Journal on Selected Areas in Communications, Series on Machine Learning in Communications and Networks, Vol. 39, No. 8, pp. 2305-2317, 2021, 10.1109/JSAC.2021.3087243 ©2021 IEEE


Šišejković, D., Reimann, L. M., Moussavi, E., Merchant, F. and Leupers, R.: Logic Locking at the Frontiers of Machine Learning: A Survey on Developments and Opportunities, in IFIP/IEEE 29th International Conference on Very Large Scale Integration (VLSI-SOC), 2021, 10.1109/VLSI-SoC53125.2021.9606979 ©2021 IEEE


Šišejković, D. and Leupers, R.: Trustworthy Hardware Design with Logic Locking, in IFIP/IEEE 29th International Conference on Very Large Scale Integration (VLSI-SOC), IEEE, 2021, 10.1109/VLSI-SoC53125.2021.9606998 ©2021 IEEE


Nambi, S., Ullah, S., Siva Satyendra, S., Lohana, A., Merchant, F. and Kumar, A.: ExPAN(N)D: Exploring Posits for EfficientArtificial Neural Network Design inFPGA-based Systems, in IEEE Access, Vol. 9, 2021, 10.1109/ACCESS.2021.3098730 ©2021 IEEE


Fu, X., Gui, G., Wang, Y., Ohtsuki, T., Abedisi, B., Gacanin, H. and Adachi, F.: Lightweight Automatic Modulation Classification Based on Decentralized Learning, in IEEE Transactions on Cognitive Communications and Networking, 2021, 10.1109/TCCN.2021.3089178 ©2021 IEEE


Copic, M., Leupers, R. and Ascheid, G.: Runnable Configuration in Mixed Classic/Adaptive AUTOSAR Systems by Leveraging Nondeterminism, in Proceedings of 24th Euromicro Conference on Digital System Design (DSD), 2021, 10.1109/DSD53832.2021.00070


Bytyn, A., Leupers, R. and Ascheid, G.: ConvAix: An Application-Specific Instruction-Set Processor for the Efficient Acceleration of CNN, in IEEE Open Journal of Circuits and Systems, Vol. 2, pp. 3-15, 2021, 10.1109/OJCAS.2020.3037758


Liang, Z., Wu, S.-j. and Ascheid, G.: Low Time-Complexity Learning-Aided Codebook-Based Beam Forming Selection in MmWave System, in Proceedings of European Wireless Conference (EW), VDE, 2021, ISBN: 978-3-80075-672-8


Bamberg, L., Krishna, T. and Joseph, J. M.: Technology-Aware Router Architectures for On-Chip-Networks in Heterogeneous Technologies, in Proceedings of the Eight Annual ACM International Conference on Nanoscale Computing and Communication, Association for Computing Machinery, New York, NY, USA, 2021, ISBN: 978-1-45038-710-1, 10.1145/3477206.3477457


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