Generalized pair weights of linear codes are generalizations of minimum symbol-pair weights, which were introduced by Liu and Pan (2022) recently. Generalized pair weights can be used to characterize ...the ability of protecting information in the symbol-pair read wire-tap channels of type II. In this paper, we introduce the notion of generalized <inline-formula> <tex-math notation="LaTeX">b </tex-math></inline-formula>-symbol weights of linear codes over finite fields, which is a generalization of generalized Hamming weights and generalized pair weights. We obtain some basic properties and bounds of generalized <inline-formula> <tex-math notation="LaTeX">b </tex-math></inline-formula>-symbol weights which are called Singleton-like bounds for generalized <inline-formula> <tex-math notation="LaTeX">b </tex-math></inline-formula>-symbol weights. As examples, we calculate the generalized weight matrices for simplex codes and Hamming codes. We provide a necessary and sufficient condition for a linear code to be a <inline-formula> <tex-math notation="LaTeX">b </tex-math></inline-formula>-symbol MDS code by using the generator matrix and the parity check matrix of this linear code. Finally, a necessary and sufficient condition of a linear isomorphism preserving <inline-formula> <tex-math notation="LaTeX">b </tex-math></inline-formula>-symbol weights between two linear codes is obtained. As a corollary, we get the classical MacWilliams extension theorem when <inline-formula> <tex-math notation="LaTeX">b=1 </tex-math></inline-formula>.
This study focuses on the development of low-resolution symbol-level precoding techniques for multiuser MIMO downlink systems with PSK modulation. While for QPSK the established minimum symbol error ...probability criterion is used, a criterion for PSK modulation, in general, is proposed based on the minimum union-bound symbol-error probability. Based on these criteria different low-resolution precoding approaches are proposed. First, suboptimal solutions are computed via a partial greedy search method. Then the suboptimal solutions are utilized as initialization for a novel branch-and-bound algorithm that can exploit knowledge of the system's quality-of-service demands. Different than existing branch-and-bound approaches the proposed quality-of-service branch-and-bound method searches for a solution that attains a target symbol-error probability while going in the direction of the global optimal solution. In this sense, the proposed branch-and-bound method allows for tunable complexity performance trade-offs. Numerical results confirm that the proposed quality-of-service branch-and-bound algorithm yields reduced symbol-error probability with significantly smaller computational complexity than other state-of-the-art branch-and-bound designs.
Differential spatial modulation (DSM), which does not require the channel state information at the receiver, is an attractive alternative to its coherent counterpart. The optimal maximum-likelihood ...(ML) detector of the DSM system employs the classic block-by-block method for jointly detecting the activated antenna matrix (AM) and the modulation symbols, resulting in high computational complexity. In this letter, a low-complexity near-ML detector, which operates on a symbol-by-symbol basis, is proposed for the DSM scheme. Specifically, in each block, the index of the activated transmit antenna and modulation symbol in each time slot are first obtained, and then, these antenna indices are utilized to simply determine the index of the activated AM. Simulation results show that the proposed algorithm is capable of offering almost the same performance as that of the ML detector with more than 90% reduction in complexity.
Symbol emergence in robotics: a survey Taniguchi, Tadahiro; Nagai, Takayuki; Nakamura, Tomoaki ...
Advanced robotics,
06/2016, Letnik:
30, Številka:
11-12
Journal Article
Recenzirano
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Humans can learn a language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how ...humans can form symbol systems and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted regarding the construction of robotic systems and machine learning methods that can learn a language through embodied multimodal interaction with their environment and other systems. Understanding human?-social interactions and developing a robot that can smoothly communicate with human users in the long term require an understanding of the dynamics of symbol systems. The embodied cognition and social interaction of participants gradually alter a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER represents a constructive approach towards a symbol emergence system. The symbol emergence system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e. humans and developmental robots. In this paper, specifically, we describe some state-of-art research topics concerning SER, such as multimodal categorization, word discovery, and double articulation analysis. They enable robots to discover words and their embodied meanings from raw sensory-motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions for research in SER.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Faster-than-Nyquist (FTN) signaling can improve spectral efficiency and enable high-speed transmission for next-generation communication systems. One of the most significant challenges in FTN ...transmission is how to remove the inter-symbol interference (ISI). In this paper, we propose a novel decision-directed successive interference cancellation (DDSIC) based on frequency-domain minimum-mean-square-error (MMSE) equalization for practical FTN systems. To reduce the computational complexity, the detection process is performed frame-by-frame in the frequency domain. In addition, we derive the theoretical bit error rate (BER) expression for each iteration in DDSIC as well as the BER lower bound for <inline-formula> <tex-math notation="LaTeX">M </tex-math></inline-formula>-ary quadrature amplitude modulated FTN systems. The simulation results verify the theoretical analyses and demonstrate that our proposed method enables lower complexity and better performance compared with state-of-the-art methods.
Common operational understanding among engaged emergency responders is facilitated through shared operational pictures during crisis situations. Sharing is typically achieved through interactive ...tools, either desktop or web-based, in which map displays play an essential role. That role can be further strengthened if (1) agreed emergency symbols that are used in map-based interactive tools are sufficient to encode multifaceted operational information visually; and (2) the symbols are legible and meaningful for the diverse users of those tools. The authors revisited official emergency map symbols in use in Norway and reconsidered them against current requirements. To this end, they first conducted several meetings with stakeholders to elicit adequate revision requirements. Next, the reconsideration included the extension of the symbol set, symbol modification, and grouping. After the reconsideration, emergency management officers and specialists were interviewed. The interviews confirmed the agreement with the symbol categorization, extension of the symbols, and their modifications. The interviewees also made numerous suggestions to be considered in a follow-up study. Moreover, two concepts - symbol standardization and symbol harmonization - were proposed.
Sequential Channel Synthesis Yu, Lei; Anantharam, Venkat
IEEE transactions on information theory,
05/2023, Letnik:
69, Številka:
5
Journal Article
Recenzirano
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The channel synthesis problem has been widely investigated over the last decade. In this paper, we consider the sequential version in which the encoder and the decoder work in a sequential way. Under ...a mild assumption on the target joint distribution we provide a complete (single-letter) characterization of the solution for the point-to-point case, which shows that the canonical symbol-by-symbol mapping is not optimal in general, but is indeed optimal if we make some additional assumptions on the encoder and decoder. We also extend this result to the broadcast scenario and the interactive communication scenario. We provide bounds in the broadcast setting and a complete characterization of the solution under a mild condition on the target joint distribution in the interactive communication case. Our proofs are based on a Rényi entropy method.
Symbol detection plays an important role in the implementation of digital receivers. In this work, we propose ViterbiNet, which is a data-driven symbol detector that does not require channel state ...information (CSI). ViterbiNet is obtained by integrating deep neural networks (DNNs) into the Viterbi algorithm. We identify the specific parts of the Viterbi algorithm that depend on the channel model, and design a DNN to implement only those computations, leaving the rest of the algorithm structure intact. We then propose a meta-learning based approach to train ViterbiNet online based on recent decisions, allowing the receiver to track dynamic channel conditions without requiring new training samples for every coherence block. Our numerical evaluations demonstrate that the performance of ViterbiNet, which is ignorant of the CSI, approaches that of the CSI-based Viterbi algorithm, and is capable of tracking time-varying channels without needing instantaneous CSI or additional training data. Moreover, unlike conventional Viterbi detection, ViterbiNet is robust to CSI uncertainty, and it can be reliably implemented in complex channel models with constrained computational burden. More broadly, our results demonstrate the conceptual benefit of designing communication systems that integrate DNNs into established algorithms.
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