High-Rate Space-Time Coded Large MIMO Systems: Low-Complexity Detection and Channel Estimation

In this paper, we present a low-complexity algorithm for detection in high-rate, non-orthogonal space-time block coded (STBC) large-MIMO systems that achieve high spectral efficiencies of the order of tens of bps/Hz. We also present a training-based iterative detection/channel estimation scheme for such large STBC MIMO systems. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed multistage likelihood ascent search (M-LAS) detector in conjunction with the proposed iterative detection/channel estimation scheme at low complexities. The fact that we could show such good results for large STBCs like 16x16 and 32x32 STBCs from Cyclic Division Algebras (CDA) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot based training for channel estimation and turbo coding) establishes the effectiveness of the proposed detector and channel estimator. We decode perfect codes of large dimensions using the proposed detector. With the feasibility of such a low-complexity detection/channel estimation scheme, large-MIMO systems with tens of antennas operating at several tens of bps/Hz spectral efficiencies can become practical, enabling interesting high data rate wireless applications.Comment: v3: Performance/complexity comparison of the proposed scheme with other large-MIMO architectures/detectors has been added (Sec. IV-D). The paper has been accepted for publication in IEEE Journal of Selected Topics in Signal Processing (JSTSP): Spl. Iss. on Managing Complexity in Multiuser MIMO Systems. v2: Section V on Channel Estimation is update

The Influence of High-Energy Lithium Ion Irradiation on Electrical Characteristics of Silicon and GaAs Solar Cells

Space-grade Si and GaAs solar cells were irradiated with 15 & 40 MeV Li ions. Illuminated (AM0 condition) and unilluminated I-V curves reveal that the effect of high-energy Li ion irradiation has produced similar effects to that of proton irradiation. However, an additional, and different, defect mechanism is suggested to dominate in the heavier-ion results. Comparison is made with proton-irradiated solar-cell work and with non-ionizing energy-loss (NIEL) radiation-damage models.Comment: 8 pages, 12 figures, Data presented at 2006 NSREC, Final Version to be published in IEEE Transactions on Nuclear Science, 53, NO. 6, December 2006. Index Terms: GaAs, Ion-irradiation, Lithium, NIEL, Photovoltaic cells, Radiation effects, Silico

Quantum Revivals in Periodically Driven Systems close to nonlinear resonance

We calculate the quantum revival time for a wave-packet initially well localized in a one-dimensional potential in the presence of an external periodic modulating field. The dependence of the revival time on various parameters of the driven system is shown analytically. As an example of application of our approach, we compare the analytically obtained values of the revival time for various modulation strengths with the numerically computed ones in the case of a driven gravitational cavity. We show that they are in very good agreement.Comment: 14 pages, 1 figur

On the degree conjecture for separability of multipartite quantum states

We settle the so-called degree conjecture for the separability of multipartite quantum states, which are normalized graph Laplacians, first given by Braunstein {\it et al.} [Phys. Rev. A \textbf{73}, 012320 (2006)]. The conjecture states that a multipartite quantum state is separable if and only if the degree matrix of the graph associated with the state is equal to the degree matrix of the partial transpose of this graph. We call this statement to be the strong form of the conjecture. In its weak version, the conjecture requires only the necessity, that is, if the state is separable, the corresponding degree matrices match. We prove the strong form of the conjecture for {\it pure} multipartite quantum states, using the modified tensor product of graphs defined in [J. Phys. A: Math. Theor. \textbf{40}, 10251 (2007)], as both necessary and sufficient condition for separability. Based on this proof, we give a polynomial-time algorithm for completely factorizing any pure multipartite quantum state. By polynomial-time algorithm we mean that the execution time of this algorithm increases as a polynomial in $m,$ where $m$ is the number of parts of the quantum system. We give a counter-example to show that the conjecture fails, in general, even in its weak form, for multipartite mixed states. Finally, we prove this conjecture, in its weak form, for a class of multipartite mixed states, giving only a necessary condition for separability.Comment: 17 pages, 3 figures. Comments are welcom

Real-time Traffic Monitoring System Based on Deep Learning and YOLOv8

Computer vision applications are important nowadays because they provide solutions to critical problems that relate to traffic in a cost-effective manner to reduce accidents and preserve lives. This paper proposes a system for real-time traffic monitoring based on cutting-edge deep learning techniques through the state-of-the-art you-only-look-once v8 algorithm, benefiting from its functionalities to provide vehicle detection, classification, and segmentation. The proposed work provides various important traffic information, including vehicle counting, classification, speed estimation, and size estimation. This information helps enforce traffic laws. The proposed system consists of five stages: The preprocessing stage, which includes camera calibration, ROI calculation, and preparing the source video input; the vehicle detection stage, which uses the convolutional neural network model to localize vehicles in the video frames; the tracking stage, which uses the ByteTrack algorithm to track the detected vehicles; the speed estimation stage, which estimates the speed for the tracked vehicles; and the size estimation stage, which estimates the vehicle size. The results of the proposed system running on the Nvidia GTX 1070 GPU show that the detection and tracking stages have an average accuracy of 96.58% with an average error of 3.42%, the vehicle counting stage has an average accuracy of 97.54% with a 2.46% average error, the speed estimation stage has an average accuracy of 96.75% with a 3.25% average error, and the size estimation stage has an average accuracy of 87.28% with a 12.72% average error

A Low-Complexity Precoder for Large Multiuser MISO Systems

In this paper, we consider the problem of preceding in large multiuser MISO systems, where by 'large' we mean (i) large number of transmit antennas (N_t) at the base station of the order of tens to hundreds of transmit antennas, and (ii) large number of downlink users (N_u) of the order of tens to hundreds of users where each user has one receive antenna. Such large MISO systems will be of immense interest because of the high capacities (sum-rates) of the order of hundreds of bits/channel use possible in such systems. We propose a vector perturbation based low-complexity precoder, termed as norm descent search (NDS) precoder, which has a complexity of just O(N_uN_t) per information symbol. This low complexity attribute of the precoder is achieved by searching for the perturbation vector over a reduced search space. Interestingly, in terms of BER performance, the proposed precoder achieves increasingly better BER for increasing N_t, N_u, such that for large N_t, N_u it achieves near-exponential diversity with some SNR loss, thus making it suited for large MISO systems both in terms of complexity as well as performance. The results of uncoded/turbo-coded simulations without and with channel estimation errors are presented

Pneumothorax or Skin Fold? Mind the Gap

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