arXiv subjects

Hongwen Yang

Publications and source records attributed to Hongwen Yang.

54 records · Page 3Linked to original sources

arXiv2020

Physical Layer Security Over Mixture Gamma Distributed Fading Channels With Discrete Inputs: A Unified and General Analytical Framework

Physical layer security is investigated over mixture Gamma (MG) distributed fading channels with discrete inputs. By the Gaussian quadrature rules, closed-form expressions are derived to characterize the average secrecy rate (ASR) and secrecy outage probability (SOP), whose accuracy is validated by numerical simulations. To show more properties of the finite-alphabet signaling, we perform an asymptotic analysis on the secrecy metrics in the large limit of the average signal-to-noise ratio (SNR) of the main channel. Leveraging the Mellin transform, we find that the ASR and SOP converge to some constants as the average SNR increases and we derive novel expressions to characterize the rates of convergence. This work establishes a unified and general analytical framework for the secrecy performance achieved by discrete inputs.

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arXiv2020

Estimation for High-Dimensional Multi-Layer Generalized Linear Model -- Part I: The Exact MMSE Estimator

This two-part work considers the minimum means square error (MMSE) estimation problem for a high dimensional multi-layer generalized linear model (ML-GLM), which resembles a feed-forward fully connected deep learning network in that each of its layer mixes up the random input with a known weighting matrix and activates the results via non-linear functions, except that the activation here is stochastic and following some random distribution. Part I of the work focuses on the exact MMSE estimator, whose implementation is long known infeasible. For this exact estimator, an asymptotic analysis on the performance is carried out using a new replica method that is refined from certain aspects. A decoupling principle is then established, suggesting that, in terms of joint input-and-estimate distribution, the original estimation problem of multiple-input multiple-output is indeed identical to a simple single-input single-output one subjected to additive white Gaussian noise (AWGN) only. The variance of the AWGN is further shown to be determined by some coupled equations, whose dependency on the weighting and activation is given explicitly and analytically. Comparing to existing results, this paper is the first to offer a decoupling principle for the ML-GLM estimation problem. To further address the implementation issue of an exact solution, Part II proposes an approximate estimator, ML-GAMP, whose per-iteration complexity is as low as GAMP, while its asymptotic MSE (if converged) is as optimal as the exact MMSE estimator.

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arXiv2020

Estimation for High-Dimensional Multi-Layer Generalized Linear Model -- Part II: The ML-GAMP Estimator

This is Part II of a two-part work on the estimation for a multi-layer generalized linear model (ML-GLM) in large system limits. In Part I, we had analyzed the asymptotic performance of an exact MMSE estimator, and obtained a set of coupled equations that could characterize its MSE performance. To work around the implementation difficulty of the exact estimator, this paper continues to propose an approximate solution, ML-GAMP, which could be derived by blending a moment-matching projection into the Gaussian approximated loopy belief propagation. The ML-GAMP estimator is then shown to enjoy a great simplicity in its implementation, where its per-iteration complexity is as low as GAMP. Further analysis on its asymptotic performance also reveals that, in large system limits, its dynamical MSE behavior is fully characterized by a set of simple one-dimensional iterating equations, termed state evolution (SE). Interestingly, this SE of ML-GAMP share exactly the same fixed points with an exact MMSE estimator whose fixed points were obtained in Part I via a replica analysis. Given the Bayes-optimality of the exact implementation, this proposed estimator (if converged) is optimal in the MSE sense.

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arXiv2020

Secrecy Performance for Finite-Alphabet Inputs Over Fluctuating Two-Ray Channels in FDA Communications

To provide system design insights for practical communication systems equipped with the frequency diverse array (FDA), this paper investigates the secrecy performance of FDA systems exploiting finite-alphabet inputs over fluctuating two-ray (FTR) fading channels. More specifically, closed-form expressions for the average secrecy rate (ASR) and the secrecy outage probability (SOP) are derived, while their correctness is confirmed by numerical simulations. In addition, we perform asymptotic analysis to quantify the secrecy performance gap between Gaussian and finite-alphabet inputs, for a sufficiently large average signal-to-noise ratio (SNR) of the main channel. Compared with Gaussian inputs-based research, this letter focuses on practical scenarios which sheds lights on properties of FDA systems.

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arXiv2020

Massive Access in Multi-cell Wireless Networks Using Reed-Muller Codes

Providing connectivity to a massive number of devices is a key challenge in 5G wireless systems. In particular, it is crucial to develop efficient methods for active device identification and message decoding in a multi-cell network with fading and path loss uncertainties. In this paper, we design such a scheme using second-order Reed-Muller (RM) sequences. For given positive integer $m$, a codebook is generated with up to $2^{m(m+3)/2}$ codewords of length $2^m$, where each codeword is a unique RM sequence determined by a matrix-vector pair with binary entries. This allows every device to send $m(m+3)/2$ bits of information where an arbitrary number of these bits can be used to represent the identity of a node, and the remaining bits represent a message. There can be up to $2^{m(m+3)/2}$ devices in total. Using an iterative algorithm, an access point can estimate the matrix-vector pairs of each nearby device, as long as not too many devices transmit simultaneously. To improve the performance, we also describe an enhanced RM coding scheme with slotting. We show that both the computational complexity and the error performance of the latter algorithm exceed another state-of-the-art algorithm. The device identification and message decoding scheme developed in this work can serve as the basis for grant-free massive access for billions of devices with hundreds of simultaneously active devices in each cell.

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arXiv2019

Performance Analysis of Receive Antenna Selection in Multi-Antenna Systems under Finite Constellation Size

Antenna selection (AS) is regarded as one of the most prospective technologies to reduce hardware cost but keep relatively high spectral efficiency in multi-antenna systems. By selecting a subset of antennas to transceive messages, AS greatly alleviates the requirement on RF chains. This paper studies receive antenna selection in single-input multiple-output (SIMO) systems, namely the antenna-selection SIMO (AS-SIMO) systems, from the perspective of digital modulation. The receiver, equipped with multiple antennas, selects an optimal antenna subset to receive messages from the single-antenna transmitter. By assuming independent and identical distributed (i.i.d) flat fading Rayleigh channels, we first analyze the input-output mutual information, also referred as symmetric capacity, of AS-SIMO systems when the modulation style is BPSK/QPSK/16QAM. To reduce the computation complexity of the capacity, closed-form approximated expressions of the symmetric capacity based on asymptotic theory are given for the first time to approach the exact results. Compared with the conventional derivations, our approximation holds much lower computation complexity with the guarantee of high precision. Next, this asymptotic approximation technique is extended to estimate the symbol error rate (SER) of antenna-selection SIMO systems and approximated expressions for SER are proposed which indicates much lower complexity. Finally, a special scenario of single-antenna-selection is detailedly investigated and series expressions of the symmetric capacity are formulated for the first time. Beside analytical derivations, simulation results are provided to demonstrate the approximation precision of the derived results. Experiment results show that the asymptotic theory has a remarkable approximation effect.

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arXiv2019

Ergodic Mutual Information for Generalized Fadings

In this paper, novel expressions are derived to evaluate the ergodic mutual information (EMI) under BPSK modulation of single-input single-output (SISO) systems operating in generalized fading channels, including $η$-$μ$ fading and $κ$-$μ$ fading. To verify our derivation, we first investigate the specific fading types, namely Rayleigh, Nakagami-$m$ and Rician, and then turn to generalized fading scenarios. It is shown that all the expressions concluded from the generalized cases can be specialized into those derived from the specific ones. Different from the conventional results of the EMI, our developed expressions contain only the simplest numerical calculations, without any Meijer's G-functions which must be implemented in the particular computing software. Additionally, it should be noted that our work provides a complete analysis of the EMI in wireless channel under discrete inputs.

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arXiv2019

Performance of Multiple Antennas Selection in SIMO Systems with BPSK/QPSK Modulations

This paper studies the performance of single-input multiple-output (SIMO) systems under receive antenna selection (RAS) and BPSK/QPSK modulations. At the receiver, a subset of branches are selected and combined using maximal-ratio combining (MRC) to maximize the instantaneous Signal to Noise Ratio (SNR). By assuming independent and identical distributed (i.i.d.) Rayleigh flat fading, a closed-form expression, with considerably high precision, is developed to approximate the average input-output mutual information, also termed as symmetric capacity, of the whole system. Later, this approximated expression is further utilized to investigate the efficient capacity and energy efficiency of the SIMO system under BPSK/QPSK modulations and RAS. Besides analytical derivations, simulations are provided to demonstrate the approximation precision, feasibility and validity of the derived results.

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arXiv2019

Ergodic Secrecy Rate of Antenna-Selection-Aided MIMOME Channels with BPSK/QPSK Modulations

This paper analyzes transmit antenna selection (TAS) under Rayleigh flat fading for BPSK/QPSK modulations in multiple-input multiple-output wiretap channels, also termed as multiple-input multiple-output multiple-eavesdropper (MIMOME) channels. In our protocol, a single antenna is selected to transmit the secret message and selection combing (SC) or maximal-ratio combing (MRC) is utilized at the legitimate receiver or the eavesdropper. Novel closed-form expressions for the ergodic secrecy rates are derived to approximate the exact values, which hold high precision and compact forms. Besides theoretical derivations, simulations are provided to demonstrate the feasibility and validity of the proposed formulas.

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arXiv2019

Mutual Information Approximation

To provide an efficient approach to characterize the input-output mutual information (MI) under additive white Gaussian noise (AWGN) channel, this short report fits the curves of exact MI under multilevel quadrature amplitude modulation (M-QAM) signal inputs via multi-exponential decay curve fitting (M-EDCF). Even though the definition expression for instanious MI versus Signal to Noise Ratio (SNR) is complex and the containing integral is intractable, our new developed fitting formula holds a neat and compact form, which possesses high precision as well as low complexity. Generally speaking, this approximation formula of MI can promote the research of performance analysis in practical communication system under discrete inputs.

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arXiv2019

Enabling NB-IoT on Unlicensed Spectrum

The deployment of Internet of Things (IoT) technologies in unlicensed spectrum is a candidate feature for 5G to support massive connections of IoT devices. Current IoT unlicensed band technologies, such as Sigfox and LoRa, are all at an early stage of deployment without a significant market share. In this context, the MulteFire (MF) Alliance has envisioned to adapt the cellular NB-IoT design to operate within the Sub-1 GHz unlicensed spectrum. However, the diverse regulatory requirements within this unlicensed band put a hurdle to the world-wide deployment of unlicensed band IoT technologies. To settle this challenge, MF has designed a specific framework for narrow-band (NB)-IoT systems operating on unlicensed spectrum (NB-IoT-U), which can be utilized under both the Federal Communications Commission (FCC) and European Telecommunication Standards Institute (ETSI) regulatory requirements. In this paper, enhanced synchronization and physical broadcasting signals are proposed based upon the framework designed by MF with the aim to allow a more robust detection, and to fulfil the coverage targets set for this technology. Furthermore, in order to allow the system to operate as a frequency hopping spread spectrum (FHSS) system, a novel frequency hopping pattern generator compliant with the regulatory requirements is designed, and its performance is evaluated.

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arXiv2019

Ergodic H-S/MRC Mutual Information

This paper studies the ergodic mutual information of hybrid selection/maximal-ratio combining (H-S/MRC) diversity system under BPSK/QPSK modulations. We consider a simple single-input multiple-output (SIMO) channel, where a subset of branches are selected and combined using maximal-ratio combining (MRC) to maximize the instantaneous Signal to Noise Ratio (SNR) at the receiver. For independent and identically distributed (i.i.d.) Rayleigh flat fading, a general recursive expression is developed to estimate the ergodic input-output mutual information of the whole system. Besides analytical derivations, simulations are provided to demonstrate the feasibility and validity of the derived results.

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arXiv2019

Secrecy Performance of Antenna-Selection-Aided MIMOME Channels with BPSK/QPSK Modulations

This paper studies the secrecy performance of multiple-input multiple-output (MIMO) wiretap channels, also termed as multiple-input multiple-output multiple-eavesdropper (MIMOME) channels, under transmit antenna selection (TAS) and BPSK/QPSK modulations. In the main channel between the transmitter and the legitimate receiver, a single transmit antenna is selected to maximizes the instantaneous Signal to Noise Ratio (SNR) at the receiver. At the receiver and the eavesdropper, selection combination (SC) is utilized. By assuming Rayleigh flat fading, we first derive the closed-form approximated expression for the ergodic secrecy rate when the channel state information of the eavesdropper (CSIE) is available at the transmitter. Next, analytical formulas for the approximated and asymptotic secrecy outage probability (SOP) are also developed when CSIE is unavailable. Besides theoretical derivations, simulation results are provided to demonstrate the approximation precision of the derived results. Furthermore, the asymptotic results reveal that the secrecy diversity order degrades into 0 due to the finitealphabet inputs, which is totally different from that driven by the Gaussian inputs.

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arXiv2019

Optimal Transmit Antenna Selection Algorithm in Massive MIMOME Channels

This paper studies the transmit antenna selection in massive multiple-input multiple-output (MIMO) system over wiretap channel. The transmitter, equipped with a large-scale antenna array whose size is much larger than that of the eavesdropper and legitimate receiver, selects a subset of antennas to transmit messages. An branch-and-bound (BAB) search based algorithm for antenna selection in independent and identical Rayleigh flat fading channel is proposed to maximize the secrecy capacity between the transmitter and the legitimate receiver when the transmit power is equally allocated into the active antennas. Furthermore, the proposed algorithm is separately applied to two scenarios which is based on whether the channel side information of the eavesdropper (CSIE) is available. Simulation results show that the proposed algorithm has the same performance as the exhaustive search under both scenarios but with much lower complexity.

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arXiv2018

Massive MIMO Antenna Selection: Asymptotic Upper Capacity Bound and Partial CSI

Antenna selection (AS) is regarded as the key promising technology to reduce hardware cost but keep relatively high spectral efficiency in multi-antenna systems. By selecting a subset of antennas to transceive messages, AS greatly alleviates the requirement on Radio Frequency (RF) chains. This paper studies receive antenna selection in massive multiple-input multiple-output (MIMO) systems. The receiver, equipped with a large-scale antenna array whose size is much larger than that of the transmitter, selects a subset of antennas to receive messages. A low-complexity asymptotic approximated upper capacity bound is derived in the limit of massive MIMO systems over independent and identical distributed (i.i.d.) Rayleigh flat fading channel, assuming that the channel side information (CSI) is only available at the receiver. Furthermore, numerical simulations are provided to demonstrate the approximation precision of the asymptotic results and the tightness of the capacity bound. Besides the asymptotic analysis of the upper bound, more discussions on the ergodic capacity of the antenna selection systems are exhibited. By defining the number of corresponding rows in the channel matrix as the amount of acquired CSI, the relationship between the achievable channel capacity and the amount of acquired CSI is investigated. Our findings indicate that this relationship approximately follows the Pareto principle, i.e., most of the capacity can be achieved by acquiring a small portion of full CSI. Finally, on the basis of this observed law, an adaptive AS algorithm is proposed, which can achieve most of the transmission rate but requires much less CSI and computation complexity compared to state-of-the-art methods.

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arXiv2018

Asymptotic Upper Capacity Bound for Receive Antenna Selection in Massive MIMO Systems

This paper studies the receive antenna selection in massive multiple-input multiple-output (MIMO) system. The receiver, equipped with a large-scale antenna array whose size is much larger than that of the transmitter, selects a subset of antennas to receive messages. A low-complexity asymptotic approximated upper capacity bound is derived in the limit of massive MIMO systems over independent and identical distributed flat fading Rayleigh channel, assuming that the channel side information (CSI) is only available at the receiver. Furthermore, the asymptotic theory is separately applied to two scenarios which is based on whether the total amount of the selected antennas exceed that of the transmit antennas. Besides analytical derivations, simulation results are provided to demonstrate the approximation precision of the asymptotic results and the tightness of the capacity bound.

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arXiv2018

Grant-less Uplink Transmission for LTE Operated in Unlicensed Spectrum

Deployment of Long Term Evolution (LTE) in unlicensed spectrum has been a candidate feature to meet the explosive growth of traffic demand since 3GPP release 13. To further explore the advantage of unlicensed bands, in this context the operation of both uplink and downlink has been supported and studied in the subsequent releases. However, it has been identified that scheduled uplink transmission performance in unlicensed spectrum is significantly degraded due to the double listen-before-talk (LBT) requirements at both eNB when sending the uplink grant, and at the scheduled UEs before transmission. In this paper, in order to overcome this issue, a novel uplink transmission scheme, which does not require any grant, is proposed, and the details regarding the system design are provided. By modeling the dynamics in time of the LBT for both a system that employs a conventional uplink scheme, as well as the proposed scheme, it is verified through analytical evaluation that the double LBT scheme for uplink transmission greatly reduces the channel access probability for the UE, and leads consequently to performance loss, while the proposed scheme is able to alleviate this issue. System level simulation results, compliant with the LTE standard, show that the proposed scheme can achieve a significant performance gain in terms of throughput with negligible performance loss for the downlink, and other technologies operating in the same spectrum.

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arXiv2007

Evaluate the Word Error Rate of Binary Block Codes with Square Radius Probability Density Function

The word error rate (WER) of soft-decision-decoded binary block codes rarely has closed-form. Bounding techniques are widely used to evaluate the performance of maximum-likelihood decoding algorithm. But the existing bounds are not tight enough especially for low signal-to-noise ratios and become looser when a suboptimum decoding algorithm is used. This paper proposes a new concept named square radius probability density function (SR-PDF) of decision region to evaluate the WER. Based on the SR-PDF, The WER of binary block codes can be calculated precisely for ML and suboptimum decoders. Furthermore, for a long binary block code, SR-PDF can be approximated by Gamma distribution with only two parameters that can be measured easily. Using this property, two closed-form approximative expressions are proposed which are very close to the simulation results of the WER of interesting.

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