The joint estimation of the spectrum, carrier, and direction of arrival (DOA) is significant in radar, sonar, wireless communications, and cognitive radio systems. The traditional parameter measurement methods based on the Shannon–Nyquist theorem require very high sampling rates, which put a lot of pressure on sampling, processing, and storage devices. In this article, novel beamforming modulated wideband converter (BMWC) system for joint estimation of the spectrum, carrier, and DOA is proposed to improve the robustness of estimation and reduce structural complexity. From the spatial signal model of array MWC, combined with the spatial filtering and signal enhancement characteristics of adaptive beamforming, the spatial target signals are focused and separated to enhance the robustness of the system. Due to the spatial filtering of beamforming, the MWC structure only needs to reconstruct one signal at a time. The number of channels of MWC connected to each antenna gets rid of the dependence on the number of signals. We utilize the MWC channel expansion technology, which makes it possible to reconstruct the signal well even when each receiving antenna is only connected to a single MWC channel. Compared with previous works, the proposed system enhances the sparsity property of the signals and greatly simplifies the MWC structure. Simulation and hardware experimental results demonstrate the effectiveness and robustness of the proposed method.

Measurement of multiple sinusoidal signals is significant in instrumentation and measurement, radar, communications, and many other electric systems. Measurement methods based upon Shannon sampling theory require very high sampling rates and heavy processing to estimate the frequencies and amplitudes. In this paper, we propose a multichannel time-staggered sampling system to measure multiple sinusoidal signals with short-observation sub-Nyquist samples. The sampling scheme is composed of N' time-staggered sampling channels, where the staggered time is allowed to be greater than the Nyquist sampling interval. The estimation method is based on the frequency domain sparse common support (SCS) model and the Chinese remainder theorem (CRT). To estimate K frequency components in the signal without the image frequency aliasing, N'≥2 sampling channels and N ≥ K + K/N' samples for each channel are enough. In the situation when the image frequency aliasing exists, N ' ≥ 2K,N ≥ 2K samples are sufficient. We further explore the analysis of noisy signals and generalize our proposal to real-valued signals. Simulation and hardware experimental results demonstrate the effectiveness and robustness of the proposed method.

Measurement of linear frequency modulation (LFM) signal is significant for radar, communication, and electronic reconnaissance fields. An LFM signal is a wideband signal whose frequency varies linearly with time, and traditional measurement methods require very high sampling rates and heavy processing to estimate parameters of the LFM signal. In this article, we propose a multichannel cooperative sampling (MCS) system based on the finite rate of innovation (FRI) theory to sample and estimate the parameters of the real-valued LFM pulse sequence (LFMPS). The MCS system consists of three parts: the autocorrelation sampling structure (ACSS), the time-delayed ACSS, and the quadrature time-staggered sampling structure (QTSS). These three parts can sample the LFMPS with sub-Nyquist sampling rate, and using the subspace method in time or frequency domain, the discontinuity locations (DLs), chirp rates, and initial frequencies (IFs) of the LFMPS can be estimated with the sub-Nyquist samples, respectively. The sampling rate of the MCS system is determined by the rate of innovation of the LFMPS, instead of signal bandwidth (BW). The minimum number of samples required for parameter estimation is proven by theoretical analysis. In addition, a nuclear norm denoising algorithm is proposed based on the low-rank property of the signal subspace, which significantly improved the performance of the measurement system in the noise environment. Simulation and hardware experimental results demonstrate the effectiveness and robustness of the proposed method.

With aggressive scaling and multilevel cell technology, the reliability of NAND flash continuously degrades. The lifetime of NAND flash is highly restricted by the bit error rate (BER), and error-correcting codes (ECCs) can provide only limited error correction capability to tolerate increasing bit errors. To cope with this issue, a novel page endurance variance aware (PEVA) strategy is proposed to extend the lifetime of NAND flash based on the experimental observations from our hardware-software codesigned experimental platform. The experimental observations indicate that the BER distribution of retention error shows distinct variances in different pages. The key purpose of PEVA is to exploit the lifetime potency of every page in a block by introducing fine-grained bad page management instead of coarse-grained bad block management (BBM). The experimental results show that the PEVA can extend the lifetime of 2×-nm NAND flash by 9.8× compared with the conventional BBM and that there is at most an 8.7% degradation in writing speed compared with the traditional sector mapping technology. In addition, the maximum writing response time increased by at most 5.9% during the operation of the PEVA strategy.

Flash memory has gradually become the dominant storage device in the consumer market and data centers since the storage capacity increases and production costs decline. Unfortunately, as the bit density of flash memory increased, the severity of reliability issues has escalated. Read retry is necessary to recover high bit-error-rate flash data; however, read retry requires the flash to perform sequential read operations, which significantly increases read latency. To improve the flash memory read performance, a reliable adaptive optimization strategy for flash memory read reference voltage (RRV) is urgently needed. In this paper, we performed a full range of error characterization tests on three-dimensional (3-D) triple-level cell (TLC) flash memory, focusing on the effects of retention leakage, P/E wear, and interlayer variation on the threshold voltage. Finally, a lightweight flash memory RRV calibration strategy was constructed. The experiment results show that the predicted RRV using the proposed strategy is very close to the actual optimal RRV, reducing the raw bit error rate (RBER) of the same model of flash memory by up to 93.2%.

Measurement of parameters of M -ary phase shift keying (MPSK) signals is significant for radar and communication systems. Traditional parameter measurement methods require very high sampling rates and heavy processing to estimate the key parameters of amplitude, carrier frequency, phases, and discontinuity locations. We propose a multichannel cooperative sampling system using the finite rate of innovation sampling theorem to address this problem. In our two-channel system, the main channel estimates the MPSK amplitude and carrier frequency using a nonlinear process and time-staggered sampling structure, while the cooperative channel determines phases and discontinuity locations with an annihilating filter using the main channel's estimated carrier frequency. Our system enables recovery of these parameters from as few as 2K+6 samples from MPSK signals with K segments. We also present a hardware platform implementing the structure. The simulation and experimental results demonstrate the effectiveness and robustness of the proposed method.