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Huazi Zhang

Publications and source records attributed to Huazi Zhang.

At least 55 records · Page 3Linked to original sources

Predicting the Mumble of Wireless Channel with Sequence-to-Sequence Models

Accurate prediction of fading channel in the upcoming transmission frame is essential to realize adaptive transmission for transmitters, and receivers with the ability of channel prediction can also save some computations of channel estimation. However, due to the rapid channel variation and channel estimation error, reliable prediction is hard to realize. In this situation, an appropriate channel model should be selected, which can cover both the statistical model and small scale fading of channel, this reminds us the natural languages, which also have statistical word frequency and specific sentences. Accordingly, in this paper, we take wireless channel model as a language model, and the time-varying channel as talking in this language, while the realistic noisy estimated channel can be compared with mumbling. Furthermore, in order to utilize as much as possible the information a channel coefficient takes, we discard the conventional two features of absolute value and phase, replacing with hundreds of features which will be learned by our channel model, to do this, we use a vocabulary to map a complex channel coefficient into an ID, which is represented by a vector of real numbers. Recurrent neural networks technique is used as its good balance between memorization and generalization, moreover, we creatively introduce sequence-to-sequence (seq2seq) models in time series channel prediction, which can translates past channel into future channel. The results show that realistic channel prediction with superior performance relative to channel estimation is attainable.

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An Asymmetric Adaptive SCL Decoder Hardware for Ultra-Low-Error-Rate Polar Codes

In theory, Polar codes do not exhibit an error floor under successive-cancellation (SC) decoding. In practice, frame error rate (FER) down to $10^{-12}$ has not been reported with a real SC list (SCL) decoder hardware. This paper presents an asymmetric adaptive SCL (A2SCL) decoder, implemented in real hardware, for high-throughput and ultra-reliable communications. We propose to concatenate multiple SC decoders with an SCL decoder, in which the numbers of SC/SCL decoders are balanced with respect to their area and latency. In addition, a novel unequal-quantization technique is adopted. The two optimizations are crucial for improving SCL throughput within limited chip area. As an application, we build a link-level FPGA emulation platform to measure ultra-low FERs of 3GPP NR Polar codes (with parity-check and CRC bits). It is flexible to support all list sizes up to $8$, code lengths up to $1024$ and arbitrary code rates. With the proposed hardware, decoding speed is 7000 times faster than a CPU core. For the first time, FER as low as $10^{-12}$ is measured and quantization effect is analyzed.

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Learning to Flip Successive Cancellation Decoding of Polar Codes with LSTM Networks

The key to successive cancellation (SC) flip decoding of polar codes is to accurately identify the first error bit. The optimal flipping strategy is considered difficult due to lack of an analytical solution. Alternatively, we propose a deep learning aided SC flip algorithm. Specifically, before each SC decoding attempt, a long short-term memory (LSTM) network is exploited to either (i) locate the first error bit, or (ii) undo a previous `wrong' flip. In each SC attempt, the sequence of log likelihood ratios (LLRs) derived in the previous SC attempt is exploited to decide which action to take. Accordingly, a two-stage training method of the LSTM network is proposed, i.e., learn to locate first error bits in the first stage, and then to undo `wrong' flips in the second stage. Simulation results show that the proposed approach identifies error bits more accurately and achieves better performance than the state-of-the-art SC flip algorithms.

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A Flip-Syndrome-List Polar Decoder Architecture for Ultra-Low-Latency Communications

We consider practical hardware implementation of Polar decoders. To reduce latency due to the serial nature of successive cancellation (SC), existing optimizations improve parallelism with two approaches, i.e., multi-bit decision or reduced path splitting. In this paper, we combine the two procedures into one with an error-pattern-based architecture. It simultaneously generates a set of candidate paths for multiple bits with pre-stored patterns. For rate-1 (R1) or single parity-check (SPC) nodes, we prove that a small number of deterministic patterns are required to guarantee performance preservation. For general nodes, low-weight error patterns are indexed by syndrome in a look-up table and retrieved in O(1) time. The proposed flip-syndrome-list (FSL) decoder fully parallelizes all constituent code blocks without sacrificing performance, thus is suitable for ultra-low-latency applications. Meanwhile, two code construction optimizations are presented to further reduce complexity and improve performance, respectively.

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A 5.16Gbps decoder ASIC for Polar Code in 16nm FinFET

Polar codes has been selected as 5G standard. However, only a couple of ASIC featuring decoders are fabricated,and none of them support list size L > 4 and code length N > 1024. This paper presents an ASIC implementation of three decoders for polar code: successive cancellation (SC) decoder, flexible decoder and ultra-reliable decoder. These decoders are all SC based decoder, supporting list size up to 1,8,32 and code length up to 2^15,2^14,2^11 respectively. This chip is fabricated in a 16nm TSMC FinFET technology, and can be clocked at 1 Ghz. Optimization techniques are proposed and employed to increase throughput. Experiment result shows that the throughput can achieve up to 5.16Gbps. Compared with fabricated AISC decoder and synthesized decoder in literature, the flexible decoder achieves higher area efficiency.

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Polarization Weight Family Methods for Polar Code Construction

Polar codes are the first proven capacity-achieving codes. Recently, they are adopted as the channel coding scheme for 5G due to their superior performance.A polar code for encoding length-K information bits in length-N codeword could be specified by the polar code construction method. Most construction methods define a polar code related to channel parameter set, e.g. designed signal-to-noise ratio. Polarization weight (PW) is a channel-independent approximation method, which estimates the subchannel reliability as a function of its index. In this paper, we generalize the PW method by including higher-order bases or extended bases. The proposed methods have robust performance while preserving the computational and mathematical simplicity as PW.

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Performance Evaluation of Channel Decoding With Deep Neural Networks

With the demand of high data rate and low latency in fifth generation (5G), deep neural network decoder (NND) has become a promising candidate due to its capability of one-shot decoding and parallel computing. In this paper, three types of NND, i.e., multi-layer perceptron (MLP), convolution neural network (CNN) and recurrent neural network (RNN), are proposed with the same parameter magnitude. The performance of these deep neural networks are evaluated through extensive simulation. Numerical results show that RNN has the best decoding performance, yet at the price of the highest computational overhead. Moreover, we find there exists a saturation length for each type of neural network, which is caused by their restricted learning abilities.

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Reed-Muller Sequences for 5G Grant-free Massive Access

We propose to use second order Reed-Muller (RM) sequence for user identification in 5G grant-free access. The benefits of RM sequences mainly lie in two folds, (i) support of much larger user space, hence lower collision probability and (ii) lower detection complexity. These two features are essential to meet the massive connectivity ($10^7$ links/km$^2$), ultra-reliable and low-latency requirements in 5G, e.g., one-shot transmission ($\leq 1$ms) with $\leq 10^{-4}$ packet error rate. However, the non-orthogonality introduced during sequence space expansion leads to worse detection performance. In this paper, we propose a noise-resilient detection algorithm along with a layered sequence construction to meet the harsh requirements. Link-level simulations in both narrow-band and OFDM-based scenarios show that RM sequences are suitable for 5G.

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Parity-Check Polar Coding for 5G and Beyond

In this paper, we propose a comprehensive Polar coding solution that integrates reliability calculation, rate matching and parity-check coding. Judging a channel coding design from the industry's viewpoint, there are two primary concerns: (i) low-complexity implementation in application-specific integrated circuit (ASIC), and (ii) superior \& stable performance under a wide range of code lengths and rates. The former provides cost- \& power-efficiency which are vital to any commercial system; the latter ensures flexible and robust services. Our design respects both criteria. It demonstrates better performance than existing schemes in literature, but requires only a fraction of implementation cost. With easily-reproducible code construction for arbitrary code rates and lengths, we are able to report "1-bit" fine-granularity simulation results for thousands of cases. The released results can serve as a baseline for future optimization of Polar codes.

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Progressive Bit-Flipping Decoding of Polar Codes Over Layered Critical Sets

In successive cancellation (SC) polar decoding, an incorrect estimate of any prior unfrozen bit may bring about severe error propagation in the following decoding, thus it is desirable to find out and correct an error as early as possible. In this paper, we first construct a critical set $S$ of unfrozen bits, which with high probability (typically $>99\%$) includes the bit where the first error happens. Then we develop a progressive multi-level bit-flipping decoding algorithm to correct multiple errors over the multiple-layer critical sets each of which is constructed using the remaining undecoded subtree associated with the previous layer. The \emph{level} in fact indicates the number of \emph{independent} errors that could be corrected. We show that as the level increases, the block error rate (BLER) performance of the proposed progressive bit flipping decoder competes with the corresponding cyclic redundancy check (CRC) aided successive cancellation list (CA-SCL) decoder, e.g., a level 4 progressive bit-flipping decoder is comparable to the CA-SCL decoder with a list size of $L=32$. Furthermore, the average complexity of the proposed algorithm is much lower than that of a SCL decoder (and is similar to that of SC decoding) at medium to high signal to noise ratio (SNR).

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Delay-aware Fountain Codes for Video Streaming with Optimal Sampling Strategy

The explosive demand of on-line video from smart mobile devices poses unprecedented challenges to delivering high quality of experience (QoE) over wireless networks. Streaming high-definition video with low delay is difficult mainly due to (i) the stochastic nature of wireless channels and (ii) the fluctuating videos bit rate. To address this, we propose a novel delay-aware fountain coding (DAF) technique that integrates channel coding and video coding. In this paper, we reveal that the fluctuation of video bit rate can also be exploited to further improve fountain codes for wireless video streaming. Specifically, we develop two coding techniques: the time-based sliding window and the optimal window-wise sampling strategy. By adaptively selecting the window length and optimally adjusting the sampling pattern according to the ongoing video bit rate, the proposed schemes deliver significantly higher video quality than existing schemes, with low delay and constant data rate. To validate our design, we implement the protocols of DAF, DAF-L (a low-complexity version) and the existing delay-aware video streaming schemes by streaming H.264/AVC standard videos over an 802.11b network on CORE emulation platform. The results show that the decoding ratio of our scheme is 15% to 100% higher than the state of the art techniques.

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Differential Modulation Exploiting the Spatial-Temporal Correlation of Wireless Channels With Moving Antenna Array

Provisioning reliable wireless services for railway passengers is becoming an increasingly critical problem to be addressed with the fast development of high speed trains (HST). In this paper, exploiting the linear mobility inherent to the HST communication scenario, we discover a new type of spatial-temporal correlation between the base station and moving antenna array on the roof top of the train. Capitalizing on the new spatial-temporal correlation structure and properties, an improved differential space-time modulation (DSTM) scheme is proposed. Analytical expressions are obtained for the pairwise error probability of the system. It is demonstrated that, the proposed approach achieves superior error performance compared with the conventional DSTM scheme. In addition, an adaptive method which dynamically adjusts the transmission block length is proposed to further enhance the system performance. Numerical results are provided to verify the performance of the proposed schemes.

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Virtual-MIMO-Boosted Information Propagation on Highways

In vehicular communications, traffic-related information should be spread over the network as quickly as possible to maintain a safer transportation system. This motivates us to develop more efficient information propagation schemes. In this paper, we propose a novel virtual-MIMO-enabled information dissemination scheme, in which the vehicles opportunistically form virtual antenna arrays to boost the transmission range and therefore accelerate information propagation along the highway. We model the information propagation process as a renewal reward process and investigate in detail the \emph{Information Propagation Speed} (IPS) of the proposed scheme. The corresponding closed-form IPS is derived, which shows that the IPS increases cubically with the vehicle density but will ultimately converge to a constant upper bound. Moreover, increased mobility also facilitates the information spreading by offering more communication opportunities. However, the limited network density essentially determines the bottleneck in information spreading. Extensive simulations are carried out to verify our analysis. We also show that the proposed scheme exhibits a significant IPS gain over its conventional counterpart.

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Large-Scale MIMO Relaying Techniques for Physical Layer Security: AF or DF?

In this paper, we consider a large scale multiple input multiple output (LS-MIMO) relaying system, where an information source sends the message to its intended destination aided by an LS-MIMO relay, while a passive eavesdropper tries to intercept the information forwarded by the relay. The advantage of a large scale antenna array is exploited to improve spectral efficiency and enhance wireless security. In particular, the challenging issue incurred by short-distance interception is well addressed. Under very practical assumptions, i.e., no eavesdropper channel state information (CSI) and imperfect legitimate CSI at the relay, this paper gives a thorough secrecy performance analysis and comparison of two classic relaying techniques, i.e., amplify-and-forward (AF) and decode-and-forward (DF). Furthermore, asymptotical analysis is carried out to provide clear insights on the secrecy performance for such an LS-MIMO relaying system. We show that under large transmit powers, AF is a better choice than DF from the perspectives of both secrecy performance and implementation complexity, and prove that there exits an optimal transmit power at medium regime that maximizes the secrecy outage capacity.

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Enhancing Wireless Information and Power Transfer by Exploiting Multi-Antenna Techniques

This paper reviews emerging wireless information and power transfer (WIPT) technique with an emphasis on its performance enhancement employing multi-antenna techniques. Compared to traditional wireless information transmission, WIPT faces numerous challenges. First, it is more susceptible to channel fading and path loss, resulting in a much shorter power transfer distance. Second, it gives rise to the issue on how to balance spectral efficiency for information transmission and energy efficiency for power transfer in order to obtain an optimal tradeoff. Third, there exists a security issue for information transmission in order to improve power transfer efficiency. In this context, multi-antenna techniques, e.g., energy beamforming, are introduced to solve these problems by exploiting spatial degree of freedom. This article provides a tutorial on various aspects of multi-antenna based WIPT techniques, with a focus on tackling the challenges by parameter optimization and protocol design. In particular, we investigate the WIPT tradeoffs based on two typical multi-antenna techniques, namely limited feedback multi-antenna technique for short-distance transfer and large-scale multiple-input multiple-output (LS-MIMO, also known as massive MIMO) technique for long-distance transfer. Finally, simulation results validate the effectiveness of the proposed schemes.

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Faster Information Propagation on Highways: a Virtual MIMO Approach

In vehicular communications, traffic-related information should be spread over the network as quickly as possible to maintain a safe and reliable transportation system. This motivates us to develop more efficient information propagation schemes. In this paper, we propose a novel cluster-based cooperative information forwarding scheme, in which the vehicles opportunistically form virtual antenna arrays to boost one-hop transmission range and therefore accelerate information propagation along the highway. Both closed-form results of the transmission range gain and the improved Information Propagation Speed (IPS) are derived and verified by simulations. It is observed that the proposed scheme demonstrates the most significant IPS gain in moderate traffic scenarios, whereas too dense or too sparse vehicle density results in less gain. Moreover, it is also shown that increased mobility offers more contact opportunities and thus facilitates information propagation.

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Enhancing User Experience for Multi-Screen Social TV Streaming over Wireless Networks

Recently, multi-screen cloud social TV is invented to transform TV into social experience. People watching the same content on social TV may come from different locations, while freely interact with each other through text, image, audio and video. This crucial virtual living-room experience adds social aspects into existing performance metrics. In this paper, we parse social TV user experience into three elements (i.e., inter-user delay, video quality of experience (QoE), and resource efficiency), and provide a joint analytical framework to enhance user experience. Specifically, we propose a cloud-based optimal playback rate allocation scheme to maximize the overall QoE while upper bounding inter-user delay. Experiment results show that our algorithm achieves near-optimal tradeoff between inter-user delay and video quality, and demonstrates resilient performance even under very fast wireless channel fading.

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Exploiting Delay Correlation for Multi-Antenna-Assisted High Speed Train Communications

In High Speed Train Communications (HSTC), the most challenging issue is coping with the extremely fast fading channel. Compared with its static counterpart, channel estimation on the move consumes excessive energy and spectrum to achieve similar performance. To address this issue, we exploit the delay correlation inherent in the linear spatial-temporal structure of multi-antenna array, based on which the rapid fading channel may be approximated by a virtual slow-fading channel. Subsequently, error probability and spectral efficiency are re-examined for this staticized channel. In particular, we formulate the quantitative tradeoff between the two metrics of interest, by adjusting the pilot percentage in each frame. Numerical results verify the good performance of the proposed scheme and elucidate the tradeoff.

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