Well-working Internet connectivity is a fundamental citizen right and a necessity in modern digital societies. Nevertheless, the digital divide persists and often affects rural or remote areas. To bridge the digital divide, we need to understand the specific rural use cases and challenges. This would increase understanding about problems weak Internet connectivity causes, what is required from the connectivity technology and what is needed from policymakers and regulation. The goal of this paper is to identify rural use cases and analyze consequences to future connectivity technology through a mixed-methods approach: we investigated the divide and its consequences by a questionnaire and interviews conducted in northern Europe. The study found that the main issues faced by rural internet users are related to capacity, availability, and vulnerability of internet services. These issues hinder their daily life, work activities, and expose them to system-level risks. The article discusses how these findings can inform the development of more inclusive and resilient internet connectivity solutions.

Beam-steering techniques using directional antennas are expected to play an important role in wireless network capacity expansion through ubiquitous small-cell deployment. However, integrating directional antennas into the existing wireless PHY and MAC stack of small cells has been challenging due to the added protocol overhead and lack of a robust antenna beam selection technique that can adapt well to environmental changes. This paper presents the design, implementation, and evaluation of LinkPursuit, a novel learning protocol for distributed antenna state selection in directional small-cell networks. LinkPursuit relies on reconfigurable antennas and a synchronous TimeDivision Multiple Access (TDMA) MAC to achieve simultaneous directional transmission and reception. Further, the system employs a practical antenna selection protocol based on the well known adaptive pursuit algorithm from the reinforcement learning literature. We implement a realtime prototype of LinkPursuit on the WARP platform and conduct extensive experiments to evaluate its performance. The empirical results show that appropriate use of directionality in LinkPursuit can result in higher network sum rates than omnidirectional transmission under various degrees of cross-link interference.

With the increasing programmability and fast-paced dynamics of modern wireless systems, it has become more difficult to gain timely insights into wireless network operations. In this demonstration1 we present WiART, an augmented reality framework to help visualize and interact with wireless network activities in real time. WiART collects real-time radio and network statistics from participating network devices and depicts them on users' mobile devices in an intuitive way, leveraging the virtual information overlay of augmented reality. Specifically in our current implementation, WiART takes inputs from a cognitive radio link controlling beam-steerable reconfigurable antennas and annotates on a live mobile screen the active pre-measured radiation patterns. In the reverse flow, WiART enables users to select desired antenna radiation patterns directly in the mobile app and observe their effects on link performance in real time. These capabilities add an unprecedented level of instant visualization and interaction with wireless activities and provides valuable insights into the dynamics of a reconfigurable antenna-based cognitive radio network.

This paper describes a new software-defined radio (SDR) platform targeted for rapid prototyping of small-cell systems. The SDR hardware combines the signal processing power of Xilinx ML605 Virtex-6 FPGA board with the Nutaq Radio420X frequency-agile transceiver and reconfigurable antennas to form a highly versatile platform for spectrum sensing, spectrum access, and cooperative communications. We evaluate the platform with two example applications: an offline OFDM physical processing flow based on WARPLab, and a real-time online automatic gain control mechanism. The results show that our SDR platform can reliably handle both offline and online processing demands with the added benefit of frequency agility offered by a state-of-the-art radio transceiver.

This paper investigates several maximum selection and serial search based code acquisition techniques for direct sequence spread spectrum receivers, which utilize either a single or multiple antenna elements. The techniques are studied with different combinations of threshold comparison and verification. Paper includes large number of analytical results calculated in static, fast and slow fading channels to obtain an insight of the performances of these methods. Numerical results will give an overview of the methods relative performance in different channels.

A localization algorithm based on double-thresholding (LAD) has been recently proposed for localizing concentrated signal(s) in the frequency or time domain. The LAD method blindly detects and separates concentrated signals and estimates their characteristics. This letter presents a theoretical performance analysis of the LAD method and an enhancement of the LAD method: the LAD with adjacent cluster combining (ACC). The good detection performance of the LAD ACC method is confirmed both theoretically and numerically.

This paper investigates three code acquisition methods for direct sequence spread spectrum systems (DS/SS) utilizing smart antennas. The methods are suitable especially for receivers that consist of a smart antenna followed by a single correlator or a matched filter (IMF). The first method is the known fixed beam strategy where the whole angular uncertainty region is divided into small cells using conventional beamforming techniques. Therein, the receiver searches through all angular and delay cells via a serial search procedure. In the second method, the fixed division is made using advanced beamforming techniques, which provide improved tolerance against interference. In the third strategy, the direction-of-arrival (DOA) of incoming signals are estimated and utilized in the acquisition process. An advantage of this DOA estimation-based strategy, when compared to fixed beamforming methods, is a decrease in the region of uncertainty. Disadvantages are increased computational complexity and signal-to-noise ratio (SNR) limitations. The acquisition strategies are compared when the serial search acquisition of the code phase is made using either the correlator or the matched filter. The results indicate that a single antenna receiver gives the best acquisition performance when SNR is high. However, single antenna methods are sensitive to interference. On the other hand, DOA estimation-based methods offer shorter mean acquisition times than fixed beam methods, especially when the number of arriving signals is small.

Matched filter (MF) time and frequency synchronization method for orthogonal frequency division multiplexing (OFDM) systems is presented. The proposed method uses the same pseudo-noise (PN)-preamble generation as was used in [1], but signal processing in the receiver is different. The performance of the proposed method is investigated using theoretical and simulated synchronization probabilities. The obtained results indicate that the proposed synchronizer attains the optimum theoretical performance.

In this paper, code synchronization probabilities of the direct sequence spread spectrum (DS/SS) system are investigated when the receiver utilizes an adaptive antenna array. Performance studies of three beam forming algorithms in the presence of direction-of-arrival (DOA) errors are presented. The investigated algorithms are the conventional, the minimum variance distortionless response (MVDR), and the MVDR+ADL where the MVDR algorithm is enhanced against DOA error via the adaptive diagonal loading (ADL). The paper includes a large number of analytical and simulation results where the effects of DOA errors are investigated. It can be concluded that the MVDR beam former is more sensitive to DOA errors than the conventional beam former, especially, at large DOA errors and high signal-to-noise-ratio (SNR) values. However, this sensitivity can be reduced notably by using the ADL.

This paper focuses on the cleaning of radio channel measurements using interference suppression (IS) methods. The investigated radio channel was measured in a sub-urban environment at 2.45 GHz with 200 MHz bandwidth. The measurements contain badly corrupted data, where the wideband measurement signal coexists with several "narrowband" (ca. 10-20 MHz) interfering signals. Interference suppression was performed using the backward consecutive mean excision (CME), forward CME (FCME) and limiter CME (LCME) algorithms. The performance of the CME algorithms was of interest. The results verify that it is possible to clean the corrupted channel measurement data with reasonable computational costs

This paper introduces a method used for code synchronization in direct sequence spread spectrum (DS/SS) systems when the receiver is equipped with a smart antenna followed by the matched filter (MF). The presented method first estimates the direction-of-arrival (DOA) of the DS-signal, then performs beamforming, and finally makes synchronization decision based on the maximum output of the MF. Because the amount of data needed in DOA estimation depends on the prevailing signal-to-noise ratio (SNR), the proposed method operates iteratively. The method starts by collecting a piece of data for DOA estimation. Due to the inaccurate DOA estimation, the main beam of the radiation pattern may be steered to erroneous direction and code acquisition may be failed. After a fail more data is collected and the accuracy of DOA estimate improves. This process is repeated until DOA and delay estimation succeeds. The results show that it is advantageous to start by collecting only a small amount of data for DOA estimation because the shortest mean acquisition times are achieved in that case

The channelized radiometer is a well-known intercept receiver. We analyze its performance when different constant false alarm rate (CFAR) strategies are used to set a detection threshold based on values of some reference cells. The studied conventional methods are cell-averaging (CA) and order statistics. The proposed iterative methods for setting the detection threshold are forward consecutive mean excision (FCME) with the CA scaling factors in (final) detection decision (FCME+CA), backward consecutive mean excision (BCME) with the CA scaling factors in detection (BCME+CA) and a method that uses the CA scaling factors in both censoring and detection (CA+CA). The results show that iterative CFAR methods can improve detection performance compared to the baseline methods.

We analyze the impact of a uniform quantizer on the false-alarm probability of a total power radiometer. Different possibilities to set the detection threshold are discussed. The main emphasis is on methods that use the estimated noise level. In particular, we analyze the cell-averaging (CA) constant false-alarm rate threshold setting strategy. The numerical results show that the CA strategy offers the desired false-alarm probability.

This letter introduces diagnostic impulse-detection methods in general, and, based on those, presents three iterative impulse detectors for communication receivers with an antenna array. These detectors are implemented either in a backward or forward search mode. The forward methods are shown to perform better. They can detect all the impulses, even though 90% of all the samples are corrupted.

Computation of the minimum output energy (MOE) detector and estimator is considered. Different ways to compute the detector and estimator are reviewed. Emphasis is on square-root factorization based methods, which compute the detector and estimator iteratively, and are numerically robust. In particular, explicit algorithms based on the Householder transformation are derived. As an intermediate step, the iterative square-root algorithm to update the inverse of the sample correlation matrix is derived. This algorithm has a complexity N/sup 2/ operations per N/spl times/1 sample vector, and it avoids divisions and square-roots almost completely.

The Huber (1964) m-estimation principle is applied, in a simple way, to improve the interference mitigation capability of the recursive least squares (RLS) whitening interpolation filter, implemented either in the basic or linear phase form. The simulation results show that in the code phase estimation the robust linear phase RLS interpolation filter mitigates interference more than the regular RLS and linear phase RLS interpolation filters, especially if the bandwidth of the interference is narrow (<23%) when compared to the bandwidth of the direct sequence signal used. It is also shown that whitening does not significantly decrease the code phase estimation accuracy of the matched filter estimator.