Square-rich fixed point polynomial evaluation on FPGAs

Polynomial evaluation is important across a wide range of application domains, so significant work has been done on accelerating its computation. The conventional algorithm, referred to as Horner's rule, involves the least number of steps but can lead to increased latency due to serial computation. Parallel evaluation algorithms such as Estrin's method have shorter latency than Horner's rule, but achieve this at the expense of large hardware overhead. This paper presents an efficient polynomial evaluation algorithm, which reforms the evaluation process to include an increased number of squaring steps. By using a squarer design that is more efficient than general multiplication, this can result in polynomial evaluation with a 57.9% latency reduction over Horner's rule and 14.6% over Estrin's method, while consuming less area than Horner's rule, when implemented on a Xilinx Virtex 6 FPGA. When applied in fixed point function evaluation, where precision requirements limit the rounding of operands, it still achieves a 52.4% performance gain compared to Horner's rule with only a 4% area overhead in evaluating 5th degree polynomials

Coverage Analysis of Relay Assisted Millimeter Wave Cellular Networks with Spatial Correlation

We propose a novel analytical framework for evaluating the coverage performance of a millimeter wave (mmWave) cellular network where idle user equipments (UEs) act as relays. In this network, the base station (BS) adopts either the direct mode to transmit to the destination UE, or the relay mode if the direct mode fails, where the BS transmits to the relay UE and then the relay UE transmits to the destination UE. To address the drastic rotational movements of destination UEs in practice, we propose to adopt selection combining at destination UEs. New expression is derived for the signal-to-interference-plus-noise ratio (SINR) coverage probability of the network. Using numerical results, we first demonstrate the accuracy of our new expression. Then we show that ignoring spatial correlation, which has been commonly adopted in the literature, leads to severe overestimation of the SINR coverage probability. Furthermore, we show that introducing relays into a mmWave cellular network vastly improves the coverage performance. In addition, we show that the optimal BS density maximizing the SINR coverage probability can be determined by using our analysis

Analysis and Design of Millimeter Wave Cellular Networks

Millimeter wave (mmWave) communications has been widely acknowledged as an attractive strategy for the rapidly growing data rate requirements of cellular user equipments (UEs), due to the vast amounts of available frequencies at the mmWave band. However, the unique propagation characteristics of mmWave, including 1) high path loss, 2) extreme sensitivity to blockage, and 3) rapid channel fluctuations, bring serious challenges to the deployment of mmWave cellular networks. Against this background, this thesis focuses on the analysis and design of mmWave cellular networks. In Chapter 1, the motivation of the studies presented in this thesis is described. Moreover, a literature review of several key research topics is presented, including mmWave channel models, mmWave-enabled heterogeneous networks (HetNets), mmWave precoding, mmWave-based non-orthogonal multiple access (NOMA), and mmWave prototypes. Furthermore, an overview of this thesis is provided. In Chapter 2, a two-tier mmWave cellular HetNet is considered. As pointed out by the 3rd Generation Partnership Project (3GPP), a major issue in the HetNet is that high-power BSs are often heavily loaded, while low-power BSs are always lightly loaded and therefore not fully exploited. This load disparity inevitably leads to suboptimal resource allocation across the network, where a large number of UEs may be associated with one high-power BS but experience poor date rates. To increase the load of low-power BSs and strike a load balance between high-power BSs and low-power BSs, an association bias factor needs to be added to increase the possibility that UEs are associated with low-power BSs. In this chapter, we conduct novel analysis to assess the impact of the bias factor on the rate coverage performance of the considered network. In order to obtain tractable analytical results on the rate coverage probability, we model the considered network using a stochastic geometry based approach. We first analyze the loads of high-power BSs and low-power BSs, based on which we derive a new expression for the rate coverage probability of the network. Through numerical results, we demonstrate the correctness of our analysis. In addition, we thoroughly examine the impact of load balancing and various network parameters on the rate coverage probability, offering valuable guidelines on the design of practical mmWave HetNets. In Chapter 3, a relay assisted mmWave cellular network is considered. In this network, the BS adopts either the direct mode to transmit to the destination UE, or the relay mode if the direct mode fails, where the BS transmits to the relay and then the relay transmits to the destination UE. To address the drastic rotational movements of destination UEs in practice, we propose to adopt selection combining at destination UEs. Similar to Chapter 2, in order to obtain tractable analytical results on the system-level coverage probability, we model the system using a stochastic geometry based approach. New expression is derived for the signal-to-interference-plus-noise ratio (SINR) coverage probability of the network. Using numerical results, we first demonstrate the accuracy of our new expression. Then we show that ignoring spatial correlation, which has been commonly adopted in the literature, leads to severe overestimation of the SINR coverage probability. Furthermore, we show that introducing relays into a mmWave cellular network vastly improves the coverage performance. In addition, we show that the optimal BS density maximizing the SINR coverage probability can be determined by using our analysis. In Chapter 4, a summary of the conclusions drawn from this thesis is presented. Moreover, a number of future research directions are identified, including integrated mmWave/sub-6 GHz cellular networks, the mobility support in mmWave cellular networks, ultra-low latency mmWave cellular networks, and the transport layer design of mmWave cellular networks

Will Sentiment Analysis Need Subculture? A New Data Augmentation Approach

The renowned proverb that "The pen is mightier than the sword" underscores the formidable influence wielded by text expressions in shaping sentiments. Indeed, well-crafted written can deeply resonate within cultures, conveying profound sentiments. Nowadays, the omnipresence of the Internet has fostered a subculture that congregates around the contemporary milieu. The subculture artfully articulates the intricacies of human feelings by ardently pursuing the allure of novelty, a fact that cannot be disregarded in the sentiment analysis. This paper strives to enrich data through the lens of subculture, to address the insufficient training data faced by sentiment analysis. To this end, a new approach of subculture-based data augmentation (SCDA) is proposed, which engenders six enhanced texts for each training text by leveraging the creation of six diverse subculture expression generators. The extensive experiments attest to the effectiveness and potential of SCDA. The results also shed light on the phenomenon that disparate subculture expressions elicit varying degrees of sentiment stimulation. Moreover, an intriguing conjecture arises, suggesting the linear reversibility of certain subculture expressions. It is our fervent aspiration that this study serves as a catalyst in fostering heightened perceptiveness towards the tapestry of information, sentiment and culture, thereby enriching our collective understanding.Comment: JASIS

SNPHunter: a bioinformatic software for single nucleotide polymorphism data acquisition and management

BACKGROUND: Single nucleotide polymorphisms (SNPs) provide an important tool in pinpointing susceptibility genes for complex diseases and in unveiling human molecular evolution. Selection and retrieval of an optimal SNP set from publicly available databases have emerged as the foremost bottlenecks in designing large-scale linkage disequilibrium studies, particularly in case-control settings. RESULTS: We describe the architectural structure and implementations of a novel software program, SNPHunter, which allows for both ad hoc-mode and batch-mode SNP search, automatic SNP filtering, and retrieval of SNP data, including physical position, function class, flanking sequences at user-defined lengths, and heterozygosity from NCBI dbSNP. The SNP data extracted from dbSNP via SNPHunter can be exported and saved in plain text format for further down-stream analyses. As an illustration, we applied SNPHunter for selecting SNPs for 10 major candidate genes for type 2 diabetes, including CAPN10, FABP4, IL6, NOS3, PPARG, TNF, UCP2, CRP, ESR1, and AR. CONCLUSION: SNPHunter constitutes an efficient and user-friendly tool for SNP screening, selection, and acquisition. The executable and user's manual are available at