Wide-bandwidth high-resolution search for extraterrestrial intelligence

Research accomplished during the third 6-month period is summarized. Research covered the following: dual-horn antenna performance; high electron mobility transistors (HEMT) low-noise amplifiers; downconverters; fast Fourier transform (FFT) array; and backend 'feature recognizer' array

Baseband Processing for 5G and Beyond: Algorithms, VLSI Architectures, and Co-design

In recent years the number of connected devices and the demand for high data-rates have been significantly increased. This enormous growth is more pronounced by the introduction of the Internet of things (IoT) in which several devices are interconnected to exchange data for various applications like smart homes and smart cities. Moreover, new applications such as eHealth, autonomous vehicles, and connected ambulances set new demands on the reliability, latency, and data-rate of wireless communication systems, pushing forward technology developments. Massive multiple-input multiple-output (MIMO) is a technology, which is employed in the 5G standard, offering the benefits to fulfill these requirements. In massive MIMO systems, base station (BS) is equipped with a very large number of antennas, serving several users equipments (UEs) simultaneously in the same time and frequency resource. The high spatial multiplexing in massive MIMO systems, improves the data rate, energy and spectral efficiencies as well as the link reliability of wireless communication systems. The link reliability can be further improved by employing channel coding technique. Spatially coupled serially concatenated codes (SC-SCCs) are promising channel coding schemes, which can meet the high-reliability demands of wireless communication systems beyond 5G (B5G). Given the close-to-capacity error correction performance and the potential to implement a high-throughput decoder, this class of code can be a good candidate for wireless systems B5G. In order to achieve the above-mentioned advantages, sophisticated algorithms are required, which impose challenges on the baseband signal processing. In case of massive MIMO systems, the processing is much more computationally intensive and the size of required memory to store channel data is increased significantly compared to conventional MIMO systems, which are due to the large size of the channel state information (CSI) matrix. In addition to the high computational complexity, meeting latency requirements is also crucial. Similarly, the decoding-performance gain of SC-SCCs also do come at the expense of increased implementation complexity. Moreover, selecting the proper choice of design parameters, decoding algorithm, and architecture will be challenging, since spatial coupling provides new degrees of freedom in code design, and therefore the design space becomes huge. The focus of this thesis is to perform co-optimization in different design levels to address the aforementioned challenges/requirements. To this end, we employ system-level characteristics to develop efficient algorithms and architectures for the following functional blocks of digital baseband processing. First, we present a fast Fourier transform (FFT), an inverse FFT (IFFT), and corresponding reordering scheme, which can significantly reduce the latency of orthogonal frequency-division multiplexing (OFDM) demodulation and modulation as well as the size of reordering memory. The corresponding VLSI architectures along with the application specific integrated circuit (ASIC) implementation results in a 28 nm CMOS technology are introduced. In case of a 2048-point FFT/IFFT, the proposed design leads to 42% reduction in the latency and size of reordering memory. Second, we propose a low-complexity massive MIMO detection scheme. The key idea is to exploit channel sparsity to reduce the size of CSI matrix and eventually perform linear detection followed by a non-linear post-processing in angular domain using the compressed CSI matrix. The VLSI architecture for a massive MIMO with 128 BS antennas and 16 UEs along with the synthesis results in a 28 nm technology are presented. As a result, the proposed scheme reduces the complexity and required memory by 35%–73% compared to traditional detectors while it has better detection performance. Finally, we perform a comprehensive design space exploration for the SC-SCCs to investigate the effect of different design parameters on decoding performance, latency, complexity, and hardware cost. Then, we develop different decoding algorithms for the SC-SCCs and discuss the associated decoding performance and complexity. Also, several high-level VLSI architectures along with the corresponding synthesis results in a 12 nm process are presented, and various design tradeoffs are provided for these decoding schemes

Digital signal processing waveform aggregation and its experimental demonstration for next generation mobile fronthaul

L'abstract è presente nell'allegato / the abstract is in the attachmen

Experimental study of cognitive radio test-bed using USRP

Cognitive Radio is an emerging technology that enables efficient utilization of the spectrum. As such, it has created great interests in industrial and research fields. Many people have proposed test-bed models for the performance analysis of primary and secondary users in a real-time noise environment. However, these test-beds are generally lacking in their range of capabilities as well as accurate implementation of the proposed models. In this thesis, we develop our test-bed on USRP to achieve the spectrum sensing and co-existence of primary and secondary users, while implementing the rendezvous protocols for secondary traffic coordination. We first demonstrate the spectrum sensing on the primary users using an energy detector(Average periodogram analysis) to obtain the average power of the primary channel under two different channel conditions (busy or idle). The focus is extended on developing the Markov traffic model and the Coded OFDM transceivers, while discussing the practical limitations for Markov traffic and viable solutions for reducing the burst errors for Coded OFDM. Finally, a four-node test-bed model of primary and secondary users is analyzed with the interference metrics (packet loss and error rate) for different scenarios. Also, the throughput and the interference metrics are compared for different rendezvous protocols of the secondary users

SIMD-Swift: Improving Performance of Swift Fault Detection

The general tendency in modern hardware is an increase in fault rates, which is caused by the decreased operation voltages and feature sizes. Previously, the issue of hardware faults was mainly approached only in high-availability enterprise servers and in safety-critical applications, such as transport or aerospace domains. These fields generally have very tight requirements, but also higher budgets. However, as fault rates are increasing, fault tolerance solutions are starting to be also required in applications that have much smaller profit margins. This brings to the front the idea of software-implemented hardware fault tolerance, that is, the ability to detect and tolerate hardware faults using software-based techniques in commodity CPUs, which allows to get resilience almost for free. Current solutions, however, are lacking in performance, even though they show quite good fault tolerance results. This thesis explores the idea of using the Single Instruction Multiple Data (SIMD) technology for executing all program\'s operations on two copies of the same data. This idea is based on the observation that SIMD is ubiquitous in modern CPUs and is usually an underutilized resource. It allows us to detect bit-flips in hardware by a simple comparison of two copies under the assumption that only one copy is affected by a fault. We implemented this idea as a source-to-source compiler which performs hardening of a program on the source code level. The evaluation of our several implementations shows that it is beneficial to use it for applications that are dominated by arithmetic or logical operations, but those that have more control-flow or memory operations are actually performing better with the regular instruction replication. For example, we managed to get only 15% performance overhead on Fast Fourier Transformation benchmark, which is dominated by arithmetic instructions, but memory-access-dominated Dijkstra algorithm has shown a high overhead of 200%

Affordable techniques for dependable microprocessor design

As high computing power is available at an affordable cost, we rely on microprocessor-based systems for much greater variety of applications. This dependence indicates that a processor failure could have more diverse impacts on our daily lives. Therefore, dependability is becoming an increasingly important quality measure of microprocessors.;Temporary hardware malfunctions caused by unstable environmental conditions can lead the processor to an incorrect state. This is referred to as a transient error or soft error. Studies have shown that soft errors are the major source of system failures. This dissertation characterizes the soft error behavior on microprocessors and presents new microarchitectural approaches that can realize high dependability with low overhead.;Our fault injection studies using RISC processors have demonstrated that different functional blocks of the processor have distinct susceptibilities to soft errors. The error susceptibility information must be reflected in devising fault tolerance schemes for cost-sensitive applications. Considering the common use of on-chip caches in modern processors, we investigated area-efficient protection schemes for memory arrays. The idea of caching redundant information was exploited to optimize resource utilization for increased dependability. We also developed a mechanism to verify the integrity of data transfer from lower level memories to the primary caches. The results of this study show that by exploiting bus idle cycles and the information redundancy, an almost complete check for the initial memory data transfer is possible without incurring a performance penalty.;For protecting the processor\u27s control logic, which usually remains unprotected, we propose a low-cost reliability enhancement strategy. We classified control logic signals into static and dynamic control depending on their changeability, and applied various techniques including commit-time checking, signature caching, component-level duplication, and control flow monitoring. Our schemes can achieve more than 99% coverage with a very small hardware addition. Finally, a virtual duplex architecture for superscalar processors is presented. In this system-level approach, the processor pipeline is backed up by a partially replicated pipeline. The replication-based checker minimizes the design and verification overheads. For a large-scale superscalar processor, the proposed architecture can bring 61.4% reduction in die area while sustaining the maximum performance

SPEECH RECOGNITION USING SOM AND ACTUATION VIA NETWORK IN MATLAB

This paper proposes a method of Speech recognition using Self Organizing Maps (SOM) and actuation through network in Matlab. The different words spoken by the user at client end are captured and filtered using Least Mean Square (LMS) algorithm to remove the acoustic noise. FFT is taken for the filtered voice signal. The voice spectrum is recognized using trained SOM and appropriate label is sent to server PC. The client and the server communication are established using User Datagram Protocol (UDP). Microcontroller (AT89S52) is used to control the speed of the actuator depending upon the input it receives from the client. Real-time working of the prototype system has been verified with successful speech recognition, transmission, reception and actuation via network