The journal encourages articles that are multidisciplinary, especially in areas, such as bioinformatics, computational biology, molecular biology, and organismic biology, that are of interest to the community of systematic and evolutionary biologists. In addition, presentations of new findings on or insights into evolutionary processes and mechanisms as expressed at the molecular level are welcome, as are those that deal with the methodology of reconstructing evolutionary history from molecular data (such as descriptions of new or more powerful computer algorithms for constructing phylogenetic trees from orthologous nucleotide or aminoacid sequences). A deeper understanding of the mechanisms and processes of molecular evolution should lead to more accurate models of molecular evolution, which in turn should facilitate the development of better algorithms for reconstructing evolutionary history from sequence data.
history of data communication pdf download
The journal encourages articles that are multidisciplinary, especially in areas, such as bioinformatics, computational biology, molecular biology, and organismic biology, that are of interest to the community of systematic and evolutionary biologists. In addition, presentations of new findings on or insights into evolutionary processes and mechanisms as expressed at the molecular level are welcome, as are those that deal with the methodology of reconstructing evolutionary history from molecular data (such as descriptions of new or more powerful computer algorithms for constructing phylogenetic trees from orthologous nucleotide or aminoacid sequences). A deeper understanding of the mechanisms and processes of molecular evolution should lead to more accurate models of molecular evolution, which in turn should facilitate the development of better algorithms for reconstructing evolutionary history from sequence data. Papers based on few taxa and single molecular markers (for example, including only mitochondrial or chloroplast genes or genomes) will not be considered for publication. In addition to regular articles, Review papers are also accepted. Review papers do not necessarily contain new data; rather, they are a status report of a specific field within molecular phylogenetics. There are no page limits to regular articles or Review papers.
In this brief introduction we provided our view on the importance and impact of Wi-Fi technology. In the remainder of this paper we provide a holistic overview of the evolution of Wi-Fi technology and its applications. This is a huge area and it is very difficult to write a paper that includes every aspect of its history. As members of a pioneering research center in this field [6], we provide a historical perspective of evolution of Wi-Fi in the way that we experienced it in the past few decades (and the paper is driven by this personal lens). We approach this challenging task from three angles. First, how the physical (PHY) and medium access control (MAC) for wireless communications with Wi-Fi technology evolved and what were the novel wireless transmission technologies that were introduced in this endeavor. Second, how Wi-Fi positioning emerged as the most popular positioning technology in indoor and urban areas and how it has impacted our daily lives. Third, how other cyberspace applications, such as motion and gesture detection as well as authentication and security, are emerging to revolutionize human computer interfacing with the RF cloud of Wi-Fi devices.
The main obstacle for commercial implementation of the early WLANs were interference and availability of a low cost wideband spectrum in which the WLAN could operate. Indoor optical WLANs did not need to consider regulation by the Federal Communications Commission (FCC) and they could potentially provide extremely wide bandwidths. However, optical communications cannot penetrate walls or other obstacles and thus, the operation becomes restricted to open areas, which are often small inside buildings. Spread spectrum was an anti-interference technology, which at that time could potentially manage the interference problem allowing multiple users to share a wideband spectrum [9, 10, 13]. In the summer of 1985, Mike Marcus, the chief engineer at FCC at that time, released the unlicensed Industrial, Scientific, and Medical (ISM) bands with restrictions of having to use spread spectrum technology for interference management [14]. For WLANs to become a commercial product, there was need for large bandwidths (at that time) and modem technologies that could overcome the challenges of indoor RF multipath propagation to achieve data rates beyond 1 Mbps required to be considered by the IEEE 802 committee as a LAN. The ISM bands and spread spectrum technology could address both issues.
The first academic research in the physical layer of WLANs began at the Worcester Polytechnic Institute, Worcester, MA in Fall of 1985 [6]. The early academic research literature in this area began with the empirical modeling of the multipath radio propagation in indoor areas [20,21,22,23,24,25], examining decision feedback equalization (DFE) [26], and M-ary orthogonal coding [27] to achieve data rates beyond the 2 Mbps rates studied by the IEEE 802.11, to achieve rates on the orders of 20 Mbps, and the integration of voice and data for WLAN [28]. A form of M-ary orthogonal signaling was adopted by IEEE802.11b standard, DFE was adopted by the Pan European HIgh PERformance LAN (HIPERLAN)-I standard, and a form of OFDM was implemented in HIPERLAN-2 and IEEE 802.11a standards. A breakthrough, patented in this era, was the application of OFDM to WLANs, first filed by the Commonwealth Scientific and Industrial Research Organization (CSIRO), Sydney, Australia [29]. The origins of equalization, quadrature amplitude modulation (QAM), and OFDM transmission technologies were first implemented for commercial voice band communications [30]. The use of DFE was first adopted for wireless data communications over multipath troposcatter channels in military applications [31] and M-ary orthogonal coding was an extension to Code Division Multiple Access (CDMA) to increase the capacity for military applications [32]. The novelty of these technologies in this later time was in their application in commercial WLANs in non-wired and non-military applications.
The HIPERLAN was another WLAN standardization activity, sponsored by the European Telecommunications Standards Institute (ETSI), which began its work in 1992. The HIPERLAN-1 standard was the first attempt to achieve data rates above 10Mbps using DFE technology and in the 5 GHz unlicensed bands [35]. This standard was also completed in 1997, but it failed in developing a market for itself. Another more popular but extensive standardization activity for wireless indoor networking in this era was Wireless Asynchronous Transfer Mode (W-ATM), which aimed to integrate local wireless traffic with an ATM backbone wired technology [36, 37]. A comparison of this technology with Wi-Fi is available in [38].
Another major hype in physical layer technologies for wireless communications was mmWave pulse transmission technology. The IEEE 802.11ad group adopted mmWave pulse transmission technology in the 60 GHz band with utra-wideband (UWB) transmission bandwidth exceeding 2 GHz to achieve data rates on the order of Gbps. Although mmWave technology became an important part of the 5G cellular networking industry [19], IEEE 802.11ad and 802.11ay, as the first completed standards using these technologies have not been successful in attracting a huge share of the WLAN market. As we explained earlier, mmWaves in indoor areas has coverage restriction that does not apply to outdoor antenna deployments.
If the bandwidth of the system is wide enough so that the width of the transmitted communication symbols, the inverse of the bandwidth, is less than the inter-arrival time of the paths, a sensitive enough receiver can isolate each path and measure the features precisely. If the bandwidth of the channel is not wide enough, a receiver can only detect a cluster of paths as one path. In wireless communications we can categorize device receivers into three categories, ultra-wideband (UWB),Footnote 3 wideband (WB), and narrowband (NB). UWB systems are capable of measuring most individual paths, WB receivers measure multipath arrivals but each path is in reality an aggregate of a cluster of paths, and NB receivers receive the signal from many paths as essentially a single path that combines all multipath arrivals (see Fig. 7). When a receiver detects a path that is indeed the combination of several neighboring paths, due to fast variations of the phases of the original path, the amplitude of the detected path experiences Rayleigh or Rician fading and the TOA of the detected path obviously is something very different from any of the individual paths in wireless communication applications, fading causes huge degradation of the maximum achievable data rate, and to compensate for that the research community have discovered equalization, spread spectrum, OFDM, and MIMO technologies in the past several decades [39]. The popular TOA-based location related applications measure the distance from the delay of the TOA of the direct path between the transmitters and the receiver and integration of multiple paths in a single path at the receiver causes huge errors in distance estimation (1 m error for every 3 ns error in delay).
The most popular Wi-Fi devices at the time of this writing, IEEE802.11n and IEEE 802.11ac, use MIMO-OFDM technology with three transmitters and two receiver antennas, shown in Fig. 6. The OFDM signal has 64 sub-carriers, using 52 of these carriers for communication data. In addition, to the magnitude and phase of the carriers they also provide the frequency off-set from the center frequency as well as six streams of magnitude and phases of the CSI data. Depending on the quality of the beam forming algorithm to sharpen the beam, the CSI data can represent a single path or a cluster of paths arriving from a direction. If it is a cluster, the amplitude samples have a Rayleigh distribution and if it is a single path the amplitudes should be more stable with a lognormal fading behavior. The number of paths in the cluster also governs the accuracy of delay of the path measurement using the phase of the received CSI stream [72]. Recently, these data streams have been paired with artificial intelligence (AI) algorithms to initiate research in several cyberspace applications. 2ff7e9595c
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