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Information Theory (cs.IT)

Tue, 04 Jul 2023

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1.Cubature Kalman filter Based on generalized minimum error entropy with fiducial point

Authors:Jiacheng He, Gang Wang, Zhenyu Feng, Shan Zhong, Bei Peng

Abstract: In real applications, non-Gaussian distributions are frequently caused by outliers and impulsive disturbances, and these will impair the performance of the classical cubature Kalman filter (CKF) algorithm. In this letter, a modified generalized minimum error entropy criterion with fiducial point (GMEEFP) is studied to ensure that the error comes together to around zero, and a new CKF algorithm based on the GMEEFP criterion, called GMEEFP-CKF algorithm, is developed. To demonstrate the practicality of the GMEEFP-CKF algorithm, several simulations are performed, and it is demonstrated that the proposed GMEEFP-CKF algorithm outperforms the existing CKF algorithms with impulse noise.

2.Quantized generalized minimum error entropy for kernel recursive least squares adaptive filtering

Authors:Jiacheng He, Gang Wang, Kun Zhang, Shan Zhong, Bei Peng, Min Li

Abstract: The robustness of the kernel recursive least square (KRLS) algorithm has recently been improved by combining them with more robust information-theoretic learning criteria, such as minimum error entropy (MEE) and generalized MEE (GMEE), which also improves the computational complexity of the KRLS-type algorithms to a certain extent. To reduce the computational load of the KRLS-type algorithms, the quantized GMEE (QGMEE) criterion, in this paper, is combined with the KRLS algorithm, and as a result two kinds of KRLS-type algorithms, called quantized kernel recursive MEE (QKRMEE) and quantized kernel recursive GMEE (QKRGMEE), are designed. As well, the mean error behavior, mean square error behavior, and computational complexity of the proposed algorithms are investigated. In addition, simulation and real experimental data are utilized to verify the feasibility of the proposed algorithms.

3.A Fine Grained Stochastic Geometry Based Analysis on LEO Satellite Communication Systems

Authors:Yanshi Sun, Zhiguo Ding

Abstract: Recently, stochastic geometry has been applied to provide tractable performance analysis for low earth orbit (LEO) satellite networks. However, existing works mainly focus on analyzing the ``coverage probability'', which provides limited information. To provide more insights, this paper provides a more fine grained analysis on LEO satellite networks modeled by a homogeneous Poisson point process (HPPP). Specifically, the distribution and moments of the conditional coverage probability given the point process are studied. The developed analytical results can provide characterizations on LEO satellite networks, which are not available in existing literature, such as ``user fairness'' and ``what fraction of users can achieve a given transmission reliability ''. Simulation results are provided to verify the developed analysis. Numerical results show that, in a dense satellite network, {\color{black}it is} beneficial to deploy satellites at low altitude, for the sake of both coverage probability and user fairness.

4.New Designs of Robust Uplink NOMA in Cognitive Radio Inspired Communications

Authors:Yanshi Sun, Wei Cao, Momiao Zhou, Zhiguo Ding

Abstract: This paper considers a cognitive radio inspired uplink communication scenario, where one primary user is allocated with one dedicated resource block, while $M$ secondary users compete with each other to opportunistically access the primary user's channel. Two new designs of NOMA schemes, namely hybrid successive interference cancellation with power adaptation (HSIC-PA) and fixed successive interference cancellation with power adaptation (FSIC-PA), are proposed. The significant advantages of the proposed schemes are two folds. First, the proposed two schemes can ensure that the secondary users are opportunistically served without degrading the transmission reliability of the primary user. Besides, the transmission robustness of the served secondary users can be guaranteed. Specifically, the outage probability error floors can be avoided for the secondary users, which is proved by asymptotic analysis in the paper. Extensive simulation results are also provided to demonstrate the superior performance of the proposed schemes.

5.OTFS-based Robust MMSE Precoding Design in Over-the-air Computation

Authors:Dongkai Zhou, Jing Guo, Siqiang Wang, Zhong Zheng, Zesong Fei, Weijie Yuan, Xinyi Wang

Abstract: Over-the-air computation (AirComp), as a data aggregation method that can improve network efficiency by exploiting the superposition characteristics of wireless channels, has received much attention recently. Meanwhile, the orthogonal time frequency space (OTFS) modulation can provide a strong Doppler resilience and facilitates reliable transmission for high-mobility communications. Hence, in this work, we investigate an OTFS-based AirComp system in the presence of time-frequency dual-selective channels. In particular, we commence from the development of a novel transmission framework for the considered system, where the pilot signal is sent together with data and the channel estimation is implemented according to the echo from the access point to the sensor, thereby reducing the overhead of channel state information (CSI) feedback. Hereafter, based on the CSI estimated from the previous frame, a robust precoding matrix aiming at minimizing mean square error in the current frame is designed, which takes into account the estimation error from the receiver noise and the outdated CSI. The simulation results demonstrate the effectiveness of the proposed robust precoding scheme by comparing it with the non-robust precoding. The performance gain is more obvious in high signal-to-noise ratio in case of large channel estimation errors.

6.Mutual Information Analysis for Factor Graph-based MIMO Iterative Detections through Error Functions

Authors:Huan Li, Jingxuan Huang, Zesong Fei

Abstract: The factor graph (FG) based iterative detection is considered an effective and practical method for multiple-input and multiple-out (MIMO), particularly massive MIMO (m-MIMO) systems. However, the convergence analysis for the FG-based iterative MIMO detection is insufficient, which is of great significance to the performance evaluation and algorithm design of detection methods. This paper investigates the mutual information update flow for the FG-based iterative MIMO detection and proposes a precise mutual information computation mechanism with the aid of Gaussian approximation and error functions, i.e., the error functions-aided analysis (EF-AA) mechanism. Numerical results indicate that the theoretical result calculated by the EF-AA mechanism is completely consistent with the bit error rate performance of the FG-based iterative MIMO detection. Furthermore, the proposed EF-AA mechanism can reveal the exact convergent iteration number and convergent signal-to-ratio value of the FG-based iterative MIMO detection, representing the performance bound of the MIMO detection.

7.Integrated Sensing and Communication with MOCZ Waveform

Authors:Saeid K. Dehkordi, Peter Jung, Philipp Walk, Dennis Wieruch, Kai Heuermann, Giuseppe Caire

Abstract: In this work, we propose a waveform based on Modulation on Conjugate-reciprocal Zeros (MOCZ) originally proposed for short-packet communications in [1], as a new Integrated Sensing and Communication (ISAC) waveform. Having previously established the key advantages of MOCZ for noncoherent and sporadic communication, here we leverage the optimal auto-correlation property of Binary MOCZ (BMOCZ) for sensing applications. Due to this property, which eliminates the need for separate communication and radar-centric waveforms, we propose a new frame structure for ISAC, where pilot sequences and preambles become obsolete and are completely removed from the frame. As a result, the data rate can be significantly improved. Aimed at (hardware-) cost-effective radar-sensing applications, we consider a Hybrid Digital-Analog (HDA) beamforming architecture for data transmission and radar sensing. We demonstrate via extensive simulations, that a communication data rate, significantly higher than existing standards can be achieved, while simultaneously achieving sensing performance comparable to state-of-the-art sensing systems.

8.On the Capacity of Private Nonlinear Computation for Replicated Databases

Authors:Sarah A. Obead, Hsuan-Yin Lin, Eirik Rosnes, Jörg Kliewer

Abstract: We consider the problem of private computation (PC) in a distributed storage system. In such a setting a user wishes to compute a function of $f$ messages replicated across $n$ noncolluding databases, while revealing no information about the desired function to the databases. We provide an information-theoretically accurate achievable PC rate, which is the ratio of the smallest desired amount of information and the total amount of downloaded information, for the scenario of nonlinear computation. For a large message size the rate equals the PC capacity, i.e., the maximum achievable PC rate, when the candidate functions are the $f$ independent messages and one arbitrary nonlinear function of these. When the number of messages grows, the PC rate approaches an outer bound on the PC capacity. As a special case, we consider private monomial computation (PMC) and numerically compare the achievable PMC rate to the outer bound for a finite number of messages.