Homogeneous Partitioning of the Surveillance Volume discusses the implementation of the first of three sequentially complementary approaches for increasing the probability of target detection within at least some of the cells of the surveillance volume for a spatially nonGaussian or Gaussian “NOISE” environment that is temporally Gaussian. This approach, identified in the Preface as Approach A, partitions the surveillance volume into homogeneous contiguous subdivisions.
標(biāo)簽： Receivers Adaptive Antennas and
上傳時(shí)間： 2020-05-26
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At the macroscopic level of system layout, the most important issue is path loss. In the older mobile radio systems that are limited by receiver NOISE, path loss determines SNR and the maximum coverage area. In cellular systems, where the limiting factor is cochannel interference, path loss determines the degree to which transmitters in different cells interfere with each other, and therefore the minimum separation before channels can be reused.
標(biāo)簽： Characteristics Channel Mobile
上傳時(shí)間： 2020-05-30
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The ever-increasing demand for private and sensitive data transmission over wireless net- works has made security a crucial concern in the current and future large-scale, dynamic, and heterogeneous wireless communication systems. To address this challenge, computer scientists and engineers have tried hard to continuously come up with improved crypto- graphic algorithms. But typically we do not need to wait too long to find an efficient way to crack these algorithms. With the rapid progress of computational devices, the current cryptographic methods are already becoming more unreliable. In recent years, wireless re- searchers have sought a new security paradigm termed physical layer security. Unlike the traditional cryptographic approach which ignores the effect of the wireless medium, physi- cal layer security exploits the important characteristics of wireless channel, such as fading, interference, and NOISE, for improving the communication security against eavesdropping attacks. This new security paradigm is expected to complement and significantly increase the overall communication security of future wireless networks.
標(biāo)簽： Communications Physical Security Wireless Layer in
上傳時(shí)間： 2020-05-31
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This book is a result of the recent rapid advances in two related technologies: com- munications and computers. Over the past few decades, communication systems have increased in complexity to the point where system design and performance analysis can no longer be conducted without a significant level of computer sup- port. Many of the communication systems of fifty years ago were either power or NOISE limited. A significant degrading effect in many of these systems was thermal NOISE, which was modeled using the additive Gaussian NOISE channel.
標(biāo)簽： Communication Principles Simulation Systems of
上傳時(shí)間： 2020-05-31
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The investigation of the propagation channel is becoming more and more important in mod- ern wireless communication. The demand for spectral efficiency motivates exploitation of all channels that can possibly be used for communications. Nowadays, a common trend for designing physical layer algorithms is to adapt the transceiving strategy, either by maximizing the diversity gains or by utilizing the coherence of the channels to improve the signal-to-NOISE power ratio.
標(biāo)簽： Characterization Propagation Channel
上傳時(shí)間： 2020-05-31
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This paper presents a Hidden Markov Model (HMM)-based speech enhancement method, aiming at reducing non-stationary NOISE from speech signals. The system is based on the assumption that the speech and the NOISE are additive and uncorrelated. Cepstral features are used to extract statistical information from both the speech and the NOISE. A-priori statistical information is collected from long training sequences into ergodic hidden Markov models. Given the ergodic models for the speech and the NOISE, a compensated speech-NOISE model is created by means of parallel model combination, using a log-normal approximation. During the compensation, the mean of every mixture in the speech and NOISE model is stored. The stored means are then used in the enhancement process to create the most likely speech and NOISE power spectral distributions using the forward algorithm combined with mixture probability. The distributions are used to generate a Wiener filter for every observation. The paper includes a performance evaluation of the speech enhancer for stationary as well as non-stationary NOISE environment.
標(biāo)簽： Telecommunications Processing Signal for
上傳時(shí)間： 2020-06-01
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In this thesis several asp ects of space-time pro cessing and equalization for wire- less communications are treated. We discuss several di?erent metho ds of improv- ing estimates of space-time channels, such as temp oral parametrization, spatial parametrization, reduced rank channel estimation, b o otstrap channel estimation, and joint estimation of an FIR channel and an AR NOISE mo del. In wireless commu- nication the signal is often sub ject to intersymb ol interference as well as interfer- ence from other users.
標(biāo)簽： Communications Space-Time Processing Wireless for
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Part I provides a compact survey on classical stochastic geometry models. The basic models defined in this part will be used and extended throughout the whole monograph, and in particular to SINR based models. Note however that these classical stochastic models can be used in a variety of contexts which go far beyond the modeling of wireless networks. Chapter 1 reviews the definition and basic properties of Poisson point processes in Euclidean space. We review key operations on Poisson point processes (thinning, superposition, displacement) as well as key formulas like Campbell’s formula. Chapter 2 is focused on properties of the spatial shot-NOISE process: its continuity properties, its Laplace transform, its moments etc. Both additive and max shot-NOISE processes are studied. Chapter 3 bears on coverage processes, and in particular on the Boolean model. Its basic coverage characteristics are reviewed. We also give a brief account of its percolation properties. Chapter 4 studies random tessellations; the main focus is on Poisson–Voronoi tessellations and cells. We also discuss various random objects associated with bivariate point processes such as the set of points of the first point process that fall in a Voronoi cell w.r.t. the second point process.
標(biāo)簽： Stochastic Geometry Networks Wireless Volume and
上傳時(shí)間： 2020-06-01
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A wireless communication network can be viewed as a collection of nodes, located in some domain, which can in turn be transmitters or receivers (depending on the network considered, nodes may be mobile users, base stations in a cellular network, access points of a WiFi mesh etc.). At a given time, several nodes transmit simultaneously, each toward its own receiver. Each transmitter–receiver pair requires its own wireless link. The signal received from the link transmitter may be jammed by the signals received from the other transmitters. Even in the simplest model where the signal power radiated from a point decays in an isotropic way with Euclidean distance, the geometry of the locations of the nodes plays a key role since it determines the signal to interference and NOISE ratio (SINR) at each receiver and hence the possibility of establishing simultaneously this collection of links at a given bit rate. The interference seen by a receiver is the sum of the signal powers received from all transmitters, except its own transmitter.
標(biāo)簽： Stochastic Geometry Networks Wireless Volume and II
上傳時(shí)間： 2020-06-01
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Recent advances in wireless communication technologies have had a transforma- tive impact on society and have directly contributed to several economic and social aspects of daily life. Increasingly, the untethered exchange of information between devices is becoming a prime requirement for further progress, which is placing an ever greater demand on wireless bandwidth. The ultra wideband (UWB) system marks a major milestone in this progress. Since 2002, when the FCC allowed the unlicensed use of low-power, UWB radio signals in the 3.1–10.6GHz frequency band, there has been significant synergistic advance in this technology at the cir- cuits, architectural and communication systems levels. This technology allows for devices to communicate wirelessly, while coexisting with other users by ensuring that its power density is sufficiently low so that it is perceived as NOISE to other users.
標(biāo)簽： Circuits Wideband Ultra
上傳時(shí)間： 2020-06-01
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