We propose a concept system termed distributed base station (DBS), which enables distributed transmit beamforming at large carrier wavelengths to achieve significant range extension and or increased downlink data rate, providing a low-cost infrastructure for applications such as rural broadband. We consider a frequency division duplexed (FDD) system, using feedback from the receiver to achieve the required phase coherence. At a given range, @math cooperating transmitters can achieve @math -fold increase in received power compared to that for a single transmitters, and feedback-based algorithms with near-ideal performance have been prototyped. In this paper, however, we identify and address key technical issues in translating such power gains into range extension via a DBS. First, to combat the drop in per-node SNR with extended range, we design a feedback-based adaptation strategy that is suitably robust to noise. Second, to utilize available system bandwidth, we extend narrowband adaptation algorithms to wideband channels through interpolation over OFDM subcarriers. Third, we observe that the feedback channel may become a bottleneck unless sophisticated distributed reception strategies are employed, but show that acceptable performance can still be obtained with standard uplink reception if channel time variations are slow enough. We quantify system performance compactly via outage capacity analyses.
A simple example of distributed beamforming with aggregated feedback is the one bit feedback algorithm @cite_4 @cite_3 , in which transmitters use small random phase perturbations to perform stochastic ascent on the received signal strength, based on the receiver feedback, broadcast to all transmitters, of one bit per iteration. This approach is simple and has formed the basis for several prototypes @cite_24 @cite_12 . The relatively slow convergence of the original algorithm (e.g., @math iterations to reach 75 knowledge of previous perturbations @cite_17 , or using knowledge of channel statistics at the receiver @cite_34 . However, the method is fundamentally mismatched to low per-node SNRs @cite_2 , roughly speaking, because noise masks the effect of small phase perturbations. This motivates our approach, in which the transmitters employ large phase perturbations during a training phase, rather than attempting to make small adjustments while beamforming.
@cite_4 @cite_3 @cite_24 @cite_2 @cite_34 @cite_12 @cite_17
1984661114 1644869847 2052709136 1997887828 2033503324
In this paper an improved iterative algorithm is proposed for distributed transmit beamforming to achieve carrier phase alignment at the receiver. The transmitters adjust their phase offsets based on one-bit feedback from the receiver in each time slot. The proposed algorithm has an improvement in the convergence speed of phase alignment compared to a previously proposed algorithm in the literature by exploiting one-bit feedback information more efficiently. Simulation results show that the improved algorithm on average has a 20 faster convergence speed. The minimum number of time slots required to achieve specified beamforming gains and the corresponding perturbation steps are obtained by Monte Carlo simulations. We propose and demonstrate a scalable architecture for distributed receive beamforming. In a receive cluster of N + 1 nodes receiving a message from a distant transmitter, N nodes are designated as amplify-and-forward relays and one node is designated as the receiver. The relay nodes apply a phase shift to their received signal and forward it such that their forwarded signals add up constructively at the receiver, with received SNR scaling linearly with N. This approach transforms a distributed receive beamforming problem on the "long link" from transmitter to receive cluster into a distributed transmit beamforming problem on the "short link" from relays to receiver, so that the number of degrees of freedom on the short link need not scale with N. A key simplification relative to distributed transmit beamforming is that, for stable oscillators, relay frequency synchronization is not required. For oscillators with drift, we provide a simple rule of thumb for when explicit frequency synchronization can be avoided. Explicit timing alignment can also be avoided by exploiting the timing of the message received on the long link. That leaves the problem of phase adjustment at the relays, and we employ an algorithm originally invented for distributed transmit beamforming for this purpose, using one bit (per iteration) feedback from the receiver. Experimental results with software-defined radios (whose oscillators have significant drift) demonstrate that the expected gains in received signal strength are obtained with the proposed architecture. We investigate distributed beamforming from a cluster of N cooperating transmitters to a distant destination over a wideband dispersive channel. Feedback from the destination is critical for enabling this. In order to develop protocols that scale to arbitrarily large numbers of cooperating nodes, we restrict attention to aggregate feedback broadcast from the destination to the entire transmit cluster, rather than per-transmitter channel feedback as in conventional feedback-based MIMO systems. We first show that naive application of a one-bit feedback algorithm developed for narrowband channels to each subcarrier in an OFDM system does achieve beamforming gain on each subcarrier, but results in an effective channel at the destination with severe phase discontinuities across frequency, which is not amenable to standard receive channel estimation algorithms. We then show that it is possible to enforce smoothness of phase across frequency by augmenting the feedback to 2 bits per subcarrier, which enables modeling and estimation of the effective channel as sparse in the time domain. Our preliminary results show that, even when the SNR per node is well below the threshold for reliable demodulation, it is possible to bootstrap using the N-fold power pooling gain obtained from incoherent combining of the signals from multiple transmitters, and to attain a significant fraction of the N2-fold beamforming gain using the proposed algorithm. We also discuss a number of open issues, recognizing that this is only a first step in developing scalable, wideband, distributed MIMO systems. Distributed transmit beamforming with N cooperating nodes, each with fixed transmit power, provides a received power scaling with N2, corresponding to a “power pooling” gain of N and a beamforming gain of N. Prior work has shown that the optimal beamforming solution can be attained using a decentralized, iterative algorithm based on one bit (per iteration) feedback broadcast from the receiver to the transmitters. The algorithm is provably convergent in a noiseless setting, and is the basis for several successful prototypes. In this paper, we develop a framework for providing analytical insight into the effect of receiver noise, with the following key question in mind: can we bootstrap the algorithm from the incoherent power-pooled solution to operate in a regime in which the received SNR per node can be made arbitrarily small as we scale up the number of nodes N? Our analytical computations, validated by simulations, yield a somewhat negative answer: while the power-pooling gain guarantees a linear increase in received power with N, the per-node SNR cannot be scaled down with N if we wish to attain a quadratic increase in received power. Specifically, the fraction of the ideal beamforming gain attained using the one-bit algorithm is asymptotically independent of N, and depends only on the per-node SNR. However, the one-bit algorithm provides significant performance gains in practical regimes with a moderate number of cooperating nodes: the per-node SNR required for attaining a substantial fraction of the beamforming gain is low enough (e.g., − 5dB for 65 of the beamforming gain) to provide significant extension in operation regimes, while providing aggregate SNRs which permit reliable communication at high spectral efficiency: for example, starting from −5 dB per-node SNR, we obtain about 11 dB aggregate SNR with 10 cooperating nodes, and 17 dB SNR with 20 cooperating nodes. We consider distributed transmit beamforming from a cluster of cooperating nodes towards a distant destination, over a wideband dispersive channel. We consider explicit aggregate feedback, with the destination broadcasting its feedback to all nodes in the transmit cluster. Explicit feedback allows for frequency division duplex (FDD) operation, since there is no reliance on channel reciprocity. Aggregate feedback enables scalability, since the destination is agnostic to the number and identity of the transmitters. There are two key contributions. First, it is shown in a narrowband setting that, unlike a well-known one bit aggregate feedback scheme, a training-based approach in which each transmitter learns its channel to the destination based on aggregate feedback, is resilient to noise, even when the feedback is heavily quantized. Second, extending the scheme to wideband settings by using OFDM, training on a subset of subcarriers, we show that interpolation across subcarriers using sparse time domain modeling provides accurate channel estimates. In particular, at low SNR per node, our approach, which exploits the correlation across subcarriers, outperforms independent per- subcarrier channel estimates in a hypothetical benchmark system in which training and feedback is applied to all subcarriers. Our simulation results show that the beamforming performance obtained by our approach is a substantial fraction of the ideal beamforming gain, even for typical received SNRs per node as low as −20 dB, and coarse 4-phase feedback quantization. In general, the method requires training time linearly proportional to the number of cooperating nodes and inversely proportional to the per-node SNR. We describe a fully-wireless prototype of distributed transmit beamforming on a software-defined radio platform. Distributed beamforming is a cooperative transmission technique that can achieve orders of magnitude increases in range or energy efficiency of wireless communication systems. However, this technique requires precise synchronization of the radio frequency signal from each transmitter. The significance of our prototype is in demonstrating that this requirement can be satisfied using digital signal processing methods on commodity hardware with low-quality oscillators. Our synchronization approach scales to large numbers of transmitters: each transmitter runs independent algorithms based on periodically transmitted feedback packets from the receiver. A key simplification is the decoupling of the algorithms for frequency locking and beamsteering at each transmitter, even though both processes use the same feedback packets. Frequency locking employs an Extended Kalman filter to track the local oscillator offset between a transmitter and the receiver, using frequency offset measurements based on the feedback packet waveform, while the phase adjustments for beamsteering are determined using a one-bit feedback algorithm based on the feedback packet it payload. Our prototype demonstrates that distributed transmit beamforming can be incorporated into wireless networks without requiring hardware innovations, and provides open-source building blocks for future research and development. In multiple antenna wireless systems, beamforming is a simple technique for guarding against the negative effects of fading. Unfortunately, beamforming requires the transmitter to have knowledge of the forward-link channel which is often not available a priori. One way of overcoming this problem is to design the beamforming vector using a limited number of feedback bits sent from the receiver to the transmitter. In limited feedback beamforming, the beamforming vector is restricted to lie in a codebook that is known to both the transmitter and receiver. Random vector quantization (RVQ) is a simple approach to codebook design that generates the vectors independently from a uniform distribution on the complex unit sphere. This correspondence presents performance analysis results for RVQ limited feedback beamforming Block diagonalization is a linear preceding technique for the multiple antenna broadcast (downlink) channel that involves transmission of multiple data streams to each receiver such that no multi-user interference is experienced at any of the receivers. This low-complexity scheme operates only a few dB away from capacity but requires very accurate channel knowledge at the transmitter. We consider a limited feedback system where each receiver knows its channel perfectly, but the transmitter is only provided with a finite number of channel feedback bits from each receiver. Using a random quantization argument, we quantify the throughput loss due to imperfect channel knowledge as a function of the feedback level. The quality of channel knowledge must improve proportional to the SNR in order to prevent interference-limitations, and we show that scaling the number of feedback bits linearly with the system SNR is sufficient to maintain a bounded rate loss. Finally, we compare our quantization strategy to an analog feedback scheme and show the superiority of quantized feedback. We consider a communication system where two transmitters wish to exchange information through a central relay. The transmitter and relay nodes exchange data over synchronized, average power constrained additive white Gaussian noise channels with a real input with signal-to-noise ratio (SNR) of snr. An upper bound on the capacity is 1 2 log(1 + snr) bits per transmitter per use of the multiple access phase and broadcast phase of the bidirectional relay channel. We show that, using lattice codes and lattice decoding, we can obtain a rate of 1 2 log(1 2 + snr) bits per transmitter, which is essentially optimal at high SNR. The main idea is to decode the sum of the codewords modulo a lattice at the relay followed by a broadcast phase which performs Slepian-Wolf coding. We also show that if the two transmitters use identical lattices with minimum angle decoding, we can achieve the same rate of 1 2 log(1 2 + snr). The proposed scheme can be thought of as a joint physical-layer network-layer code which outperforms other recently proposed analog network coding schemes. Distributed transmit beamforming using an ad-hoc network of 10 RF transmitters was demonstrated using radio nodes developed from off-the-shelf components and modules. A time-slotted protocol allowed carrier phases from each transmitter to be measured at a receiver and fed back to the transmitters where Kalman filters were used to predict the offset phases and frequencies. Offsets were digitally compensated for during beamforming intervals. Beamforming gain within 0.1dB of ideal was demonstrated across 1 km at 910MHz. This is the first report (to our knowledge) of a successful outdoor RF distributed transmit beamforming experiment using independent clocks at this scale. We consider the problem of two transmitters wishing to exchange information through a relay in the middle. The channels between the transmitters and the relay are assumed to be synchronized, average power constrained additive white Gaussian noise channels with a real input with signal-to-noise ratio (SNR) of snr. An upper bound on the capacity is 1 2 log(1+ snr) bits per transmitter per use of the medium-access phase and broadcast phase of the bi-directional relay channel. We show that using lattice codes and lattice decoding, we can obtain a rate of 1 2 log(0.5 + snr) bits per transmitter, which is essentially optimal at high SNRs. The main idea is to decode the sum of the codewords modulo a lattice at the relay followed by a broadcast phase which performs Slepian-Wolf coding with structured codes. For asymptotically low SNR's, jointly decoding the two transmissions at the relay (MAC channel) is shown to be optimal. We also show that if the two transmitters use identical lattices with minimum angle decoding, we can achieve the same rate of 1 2 log(0.5 + snr). The proposed scheme can be thought of as a joint physical layer, network layer code which outperforms other recently proposed analog network coding schemes. Citation relationship between scientific publications has been successfully used for scholarly bibliometrics, information retrieval and data mining tasks, and citation-based recommendation algorithms are well documented. While previous studies investigated citation relations from various viewpoints, most of them share the same assumption that, if paper1 cites paper2 (or author1 cites author2), they are connected, regardless of citation importance, sentiment, reason, topic, or motivation. However, this assumption is oversimplified. In this study, we employ an innovative "context-rich heterogeneous network" approach, which paves a new way for citation recommendation task. In the network, we characterize 1) the importance of citation relationships between citing and cited papers, and 2) the topical citation motivation. Unlike earlier studies, the citation information, in this paper, is characterized by citation textual contexts extracted from the full-text citing paper. We also propose algorithm to cope with the situation when large portion of full-text missing information exists in the bibliographic repository. Evaluation results show that, context-rich heterogeneous network can significantly enhance the citation recommendation performance. This paper presents a new deterministic closed-loop phase-alignment algorithm based on quantized feedback from the receiver for distributed beamforming. In contrast with previously proposed methods, which entailed repeated transmissions from all the nodes in the network, this new algorithm requires each node to transmit only once during the synchronization cycle. This drastically reduces the amount of power consumed to achieve phase alignment, yet the new algorithm converges at least as fast as all other existing schemes. In contrast with previous analyses of distributed beamforming based on random phase updates, where noise had been disregarded, here it is explicitly included in the models and shown to have a considerable effect that cannot be ignored. With and without noise, analytical expressions that characterize the performance of the new algorithm are provided, with emphasis on various limiting regimes of interest. A citing sentence is one that appears in a scientific article and cites previous work. Citing sentences have been studied and used in many applications. For example, they have been used in scientific paper summarization, automatic survey generation, paraphrase identification, and citation function classification. Citing sentences that cite multiple papers are common in scientific writing. This observation should be taken into consideration when using citing sentences in applications. For instance, when a citing sentence is used in a summary of a scientific paper, only the fragments of the sentence that are relevant to the summarized paper should be included in the summary. In this paper, we present and compare three different approaches for identifying the fragments of a citing sentence that are related to a given target reference. Our methods are: word classification, sequence labeling, and segment classification. Our experiments show that segment classification achieves the best results. Historically, papers have been physically bound to the journal in which they were published; but in the digital age papers are available individually, no longer tied to their respective journals. Hence, papers now can be read and cited based on their own merits, independently of the journal's physical availability, reputation, or impact factor (IF). We compare the strength of the relationship between journals' IFs and the actual citations received by their respective papers from 1902 to 2009. Throughout most of the 20th century, papers' citation rates were increasingly linked to their respective journals' IFs. However, since 1990, the advent of the digital age, the relation between IFs and paper citations has been weakening. This began first in physics, a field that was quick to make the transition into the electronic domain. Furthermore, since 1990 the overall proportion of highly cited papers coming from highly cited journals has been decreasing and, of these highly cited papers, the proportion not coming from highly cited journals has been increasing. Should this pattern continue, it might bring an end to the use of the IF as a way to evaluate the quality of journals, papers, and researchers. © 2012 Wiley Periodicals, Inc. Multiple transmit antennas in a downlink channel can provide tremendous capacity (i.e., multiplexing) gains, even when receivers have only single antennas. However, receiver and transmitter channel state information is generally required. In this correspondence, a system where each receiver has perfect channel knowledge, but the transmitter only receives quantized information regarding the channel instantiation is analyzed. The well-known zero-forcing transmission technique is considered, and simple expressions for the throughput degradation due to finite-rate feedback are derived. A key finding is that the feedback rate per mobile must be increased linearly with the signal-to-noise ratio (SNR) (in decibels) in order to achieve the full multiplexing gain. This is in sharp contrast to point-to-point multiple-input multiple-output (MIMO) systems, in which it is not necessary to increase the feedback rate as a function of the SNR Distributed beamforming is a form of cooperation among nodes in a wireless network to efficiently deliver a common message to a distant receiver. The critical requirement to achieve electromagnetic coherence is to synchronize the initial phases of all local oscillators, introducing minimal overhead and complexity. In the paper we introduce random, deterministic and hybrid algorithms, all based on feedback from the common receiver as the driving force, but with different phase update strategies. Our numerical results show that these algorithms achieve faster convergence time than previously proposed approaches. Purpose – The purpose of this paper is to suggest an alternative to the widely used Times Cited criterion for analysing citation networks. The approach involves taking account of the natures of the papers that cite a given paper, so as to differentiate between papers that attract the same number of citations.Design methodology approach – ArticleRank is an algorithm that has been derived from Google's PageRank algorithm to measure the influence of journal articles. ArticleRank is applied to two datasets – a citation network based on an early paper on webometrics, and a self‐citation network based on the 19 most cited papers in the Journal of Documentation – using citation data taken from the Web of Knowledge database.Findings – ArticleRank values provide a different ranking of a set of papers from that provided by the corresponding Times Cited values, and overcomes the inability of the latter to differentiate between papers with the same numbers of citations. The difference in rankings between Times Cited ... The pilot spoofing attack is one kind of active eavesdropping conducted by a malicious user during the channel estimation phase of the legitimate transmission. In this attack, an intelligent adversary spoofs the transmitter on the estimation of channel state information (CSI) by sending the identical pilot signal as the legitimate receiver, in order to obtain a larger information rate in the data transmission phase. The pilot spoofing attack could also drastically weaken the strength of the received signal at the legitimate receiver if the adversary utilizes large enough power. Motivated by the serious problems the pilot spoofing attack could cause, we propose an efficient detector, named energy ratio detector (ERD), by exploring the asymmetry of received signal power levels at the transmitter and the legitimate receiver when there exists a pilot spoofing attack. Our analysis shows that by setting the ratio of received signal power levels at the transmitter and the legitimate receiver as the test statistic, the detecting threshold is derived without using the knowledge of the CSI of the legitimate channel as well as the illegitimate channel. Furthermore, we study the performance of the proposed ERD in various special cases in order to obtain useful insights. Numerical results are presented to further demonstrate the performance of our proposed ERD. This paper investigates the noncoherent detection in a two-way relay channel operated with physical-layer network coding (PNC), assuming FSK modulation and short-packet transmissions. For noncoherent detection, the detector has access to the magnitude but not the phase of the received signal. For conventional communication in which a receiver receives the signal from a transmitter only, the phase does not affect the magnitude, and hence the performance of the noncoherent detector is independent of the phase. PNC, on the other hand, is a multiuser system in which a receiver receives signals from multiple transmitters simultaneously. The relative phase of the signals from different transmitters affects the received signal magnitude through constructive-destructive interference. In particular, for good performance, the noncoherent detector of a multiuser system such as PNC must take into account the influence of the relative phase on the signal magnitude. Building on this observation, this paper delves into the fundamentals of PNC noncoherent detector design. To avoid excessive overhead, we assume a set-up in which the short packets in the PNC system do not have preambles. We show how the relative phase can be deduced directly from the magnitudes of the received data symbols, and that the knowledge of the relative phase thus deduced can in turn be used to enhance performance of noncoherent detection. Our overall detector design consists of two components: 1) a channel gains estimator that estimates channel gains without preambles; and 2) a detector that builds on top of the estimated channel gains to jointly estimate relative phase and detect data using a belief propagation algorithm. Numerical results show that our detector performs nearly as well as a “fictitious” optimal detector that has perfect knowledge of the channel gains and relative phase. Although this paper focuses on PNC with FSK modulation, we believe that the insight of this paper applies generally to noncoherent detection in other multiuser systems with other modulations. Specifically, our insight is that the relative phase of overlapped signals affects the signal magnitude in multiuser systems, but fortunately the relative phase can be deduced from the magnitudes and this knowledge can be used to improve the detection performance.