A compact cost-effective Narrowband Internet-of-Things (NB-IoT) System-in-Package (SiP) in mass production is implemented in 55nm CMOS and Integrated Passive Device (IPD) process. The RF front-end components, i.e., inductors and capacitors, are integrated into an IPD die to reduce the Bill of Material (BOM) cost. Notably, the design eliminated the necessity of the antenna switches (ANTSW). On the IPD die, a diplexer is employed to separate the low-band (LB) and high-band (HB) paths, while in each band, the transmitter (TX) and the receiver (RX) share a common RF low pass filter through a co-matching network. To ensure robust performance, CMOS switches are placed at the PA’s drain and the LNA’s input, protecting the LNA core devices from breaking down and tuning essential impedance matching for both TX and RX. The built-in self-calibration scheme enables the chip to calibrate its TX/RX gain autonomously and flexibly, eliminating the use of external equipment therefore reducing the cost at the module production line. The NB-IoT SoC is integrated with the IPD die in a$7\times 7$QFN package. The system operates across the NB-IoT bands from 699MHz to 2200MHz (the CMOS chip supports 450MHz to 2200MHz), with transmitter’s Psatover +26dBm and achieving the HD2/HD3 below −36dBm when transmitting at +23dBm. The self-calibration scheme improves TX LO leakage and image by more than 15dB and ensures TX/RX gain accuracy within +/−0.5dB across the band and gain states.

This brief presents a high-throughput low-complexity 512-point fast Fourier transform (FFT)/inverse fast Fourier transform (IFFT) processor for IEEE 802.11ad standard aiming at the wireless personal area network applications. To reduce the complexity of twiddle factor multiplication, the radix-24-22-23FFT algorithm is devised. To achieve the throughput of 1.76 GS/s (which is normalized as eight samples/clock) and meet the frame format of single carrier as well as orthogonal frequency division multiplexing physical layer that no interval is inserted between any two 512-length data blocks in a frame, the mixed-radix multipath delay feedback structure is adopted to support the continuous data How. Moreover, we propose a novel reorder scheme to support parallel normal-order output data How continuously, which demands only a single-RAM-group, i.e., 512-word memory size with very simple control logic. Overall, the whole FFT/IFFT processor is high throughput and area efficient, and the back-end simulation results show that the core area of the FFT processor is 1.69 mm2in Silterra 0.13 μm process.

As the sizes of supercomputers and data centers grow towards exascale, failures become normal. System logs play a critical role in the increasingly complex tasks of automatic failure prediction and diagnosis. Many methods for failure prediction are based on analyzing event logs for large scale systems, but there is still neither a widely used one to predict failures based on both non-fatal and fatal events, nor a precise one that uses fine-grained information (such as failure type, node location, related application, and time of occurrence). A deeper and more precise log analysis technique is needed. We propose a three-step approach to draw out event dependencies and to identify failure-event generating processes. First, we cluster frequent event sequences into event groups based on common events. Then we infer causal dependencies between events in each event group. Finally, we extract failure rules based on the observation that events of the same event types, on the same nodes or from the same applications have similar operational behaviors. We use this rich information to improve failure prediction. Our approach semi-automates diagnosing the root causes of failure events, making it a valuable tool for system administrators.

Failure mode and effects analysis (FMEA) is a widely used technique for designing, identifying and eliminating known and/or potential failures from system, design and process. In the traditional FMEA, for each failure mode, risk factors of Occurrence, Severity and Detection are evaluated and simply multiplied to obtain a risk priority number. Besides, the weights of three risk factors are also ignored. To overcome these shortcomings of traditional FMEA, we propose a novel FMEA approach for obtaining a more rational ranking of failure modes by integrating entropy weighting method with 'Technique for Order Performance by Similarity to Ideal Solution'(TOPSIS). Finally, a case study about purchasing website is provided to demonstrate the feasibility and benefits of the proposed approach. A plugin in our tool-Breeze is developed to support the proposed approach.

This paper presents a set of innovative algorithms and a system, named Log Master, for mining correlations of events that have multiple attributions, i.e., node ID, application ID, event type, and event severity, in logs of large-scale cloud and HPC systems. Different from traditional transactional data, e.g., supermarket purchases, system logs have their unique characteristics, and hence we propose several innovative approaches to mining their correlations. We parse logs into an n-ary sequence where each event is identified by an informative nine-tuple. We propose a set of enhanced apriori-like algorithms for improving sequence mining efficiency, we propose an innovative abstraction-event correlation graphs (ECGs) to represent event correlations, and present an ECGs-based algorithm for fast predicting events. The experimental results on three logs of production cloud and HPC systems, varying from 433490 entries to 4747963 entries, show that our method can predict failures with a high precision and an acceptable recall rates.

We address joint estimation of frequency offsets and channel responses in OFDMA uplink. A cyclically equal-spaced, equal-energy interleaved pilot preamble is proposed by which two iterative estimators are developed. In the first estimator, we develop a modified SAGE (space alternating generalized expectation-maximization) method by incorporating multiuser interference cancellation in both time and frequency domains into the SAGE method. The proposed modified SAGE method yields a faster convergence rate, a better estimation performance, and a lower complexity than the existing conventional SAGE method from [10]. In the second method, we propose a very low complexity ad hoc method to replace the high complexity frequency offset estimator of the first method. The proposed ad hoc method is developed based on the time-domain characteristics of the pilot preamble and the frequency-domain power concentration property of OFDMA systems. It achieves almost the same estimation performance as the first proposed method but requires significantly lower complexity. Both proposed methods are not only better in estimation performance, convergence rate, and complexity, but also more robust to the number of active uplink users than the existing method while requiring only one OFDM training symbol and no restriction of the data subcarrier assignment scheme.

Broadband wireless access technology is developed very fast in recent years. The IEEE 802.16 and 802.11a are two broadband wireless access system standards for metropolitan and local areas respectively. The IEEE 802.11a works in the license-exempt (LE) band, and the IEEE 802.16 is designed such that it can operate in the same LE spectrum too. Although the two systems work in different environments, interference can exist under some scenario. In this paper, the coexistence issues of the two types of networks are investigated and a simple and accurate way for bit-error-ratio (BER) calculation is given. The analysis is also verified by Monte Carlo simulations. Furthermore, in our work, we also show how our research production is used to configure the coexisting IEEE 802.16 and 802.11a systems to mitigate the interference.

We present a new initial ranging method for OFDMA systems such as IEEE 802.16-2004. First, a new orthogonal ranging signal design is proposed by which an efficient, low-complexity multi-user ranging signal detection is developed. Based on the ranging signal detector results, power estimation for the detected ranging subscriber stations is performed. Then, by utilizing the proposed orthogonal ranging signal design together with the redundancy introduced by cyclic prefixes, a new iterative multi-user timing offset estimator is presented. Compared with the existing methods utilizing the CDMA-type ranging codes (in frequency-domain) defined in IEEE 802.16-2004, the proposed method achieves a better performance and greater robustness against multi-user interference and multi-path fading channels

In data-pilot-multiplexed OFDM schemes, data-interference to pilot tones causes degradation in frequency offset and channel estimation. This paper derives the best data-pilot-multiplexed scheme in terms of minimizing data-interference on pilot tones. This design gives a correlated data insertion scheme (CD) (data on the left and right adjacent tones of each pilot are correlated) and a null data insertion scheme (ND) (no data are transmitted on the left and right adjacent tones of each pilot). Both schemes outperform conventional data-pilot-multiplexed schemes (CV) significantly (over 7 dB SNR advantage at the uncoded BER of 2 times 10-2and pilot-to-data energy ratio (PDER) of 5 dB). With the BLUE frequency offset estimator, the CD scheme yields a better performance than the ND scheme while having a slight advantage in data throughput. A modified CD scheme is also presented which transmits the same data rate at similar complexity as the CV scheme does while achieving a significant BER improvement (over 3 dB SNR advantage at the uncoded BER of 2 times 10-2and PDER of 5 dB)

We address joint estimation of frequency offsets and channel responses in OFDMA uplink. A cyclically equal-spaced, equal-energy interleaved pilot preamble is proposed by which two iterative estimators are developed. In the first estimator, we develop a modified SAGE (space alternating generalized expectation-maximization) method by incorporating multiuser interference cancellation in both time and frequency domains into the SAGE method. The proposed modified SAGE method yields a faster convergence rate, a better estimation performance, and a lower complexity than the existing conventional SAGE method. In the second method, we propose a very low complexity ad-hoc method to replace the high complexity frequency offset estimator of the first method. The proposed ad-hoc method is developed based on the time-domain characteristics of the pilot preamble and the frequency-domain power concentration property of OFDMA systems. It achieves almost the same estimation performance as the first proposed method but requires significantly lower complexity. Both proposed methods are not only better in estimation performance, convergence rate, and complexity, but also more robust to the number of active uplink users than the existing method while requiring only one OFDM training symbol and no restriction of the data subcarrier assignment scheme.

This paper addresses an optimal periodic training signal design for frequency offset estimation in frequency-selective multipath Rayleigh fading channels. For a fixed transmitted training signal energy within a fixed-length block, the optimal periodic training signal structure (the optimal locations of identical training subblocks) and the optimal training subblock signal are presented. The optimality is based on the minimum Cramer-Rao bound (CRB) criterion. Based on the CRB for joint estimation of frequency offset and channel, the optimal periodic training structure (optimality only in frequency offset estimation, not necessarily in joint frequency offset and channel estimation) is derived. The optimal training subblock signal is obtained by using the average CRB (averaged over the channel fading) and the received training signal statistics. A robust training structure design is also presented in order to reduce the occurrence of outliers at low signal-to-noise ratio values. The proposed training structures and subblock signals achieve substantial performance improvement.

We present a new initial ranging method for OFDMA systems such as IEEE 802.16a. First, a new orthogonal ranging signal design is proposed by which an efficient, low-complexity multi-user ranging signal detection is developed. Based on the ranging signal detector results, power estimation for the detected ranging subscriber stations is performed. Then, by utilizing the proposed orthogonal ranging signal design together with the redundancy introduced by cyclic prefixes, a new iterative multi-user timing offset estimator is presented. Compared with the existing methods utilizing the CDMA-type ranging codes (in frequency-domain) defined in IEEE 802.16a, the proposed method achieves a better performance and greater robustness against multi-user interference and multi-path fading channels.

We address the initial ranging process in OFDMA systems such as IEEE 802.16a. The proposed ranging method includes three main tasks - timing estimation, multi-user ranging code detection, and power estimation. All tasks are performed based on a bank of correlators corresponding to ranging codes. The timing estimation scheme is based on the peak of correlator outputs. The multi-user ranging code detection is based on the correlator outputs and an adaptive threshold. A novel adaptive threshold setting is proposed. A simple user-power estimator is derived based on the correlator outputs. A scheme of initial power adjustment at the random access users is also proposed which brings in a significant improvement in ranging code detection performance. The simulation results show that the proposed method works well even in the presence of several simultaneous random-access users and is robust to other data-users' interference. The simplicity of the proposed method is also quite appealing.