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Applications in engineering and biology. Introduction to finite-dimensional, continuous, and discrete-time linear dynamical systems. Exploration of the basic properties and mathematical structure of the linear systems used for modeling dynamical processes in robotics, signal and image processing, economics, statistics, environmental and biomedical engineering, and control theory.

Introduction to the fundamental theory underlying modern digital communication.

Quantitative measures of information and data compression: the Huffman and Lempel-Ziv algorithms, scalar and vector quantization. Representations of signal waveforms: sampling, orthonormal expansions, waveforms as vectors in signal space. Transmission of signals through noisy channels; pulse amplitude and quadrature amplitude modulation, orthogonal signaling, signal design, noise processes, optimal detection, and error probability analysis. Applications to practical systems such as CD players, telephone modems, and wireless networks. This course aims to weave together fundamental theory of wireless communications, its application, and the design and implementation of wireless network architectures.

Particular emphasis is placed on the interplay between concepts and their implementation in real systems. Students can expect to learn background knowledge of some everyday wireless technologies and how to design systems based on the fundamental communications concepts. The aim of the course is to introduce the basic Internet protocols and architectures. The basic architectural concepts of packet switching networks will be studied extensively, including important operating algorithms.

A study of stochastic processes and estimation, including fundamentals of detection and estimation.

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Vector space representation of random variables, Bayesian and Neyman-Pearson hypothesis testing, Bayesian and nonrandom parameter estimation, minimum-variance unbiased estimators, and the Cramer-Rao bound. Stochastic processes. Linear prediction and Kalman filtering. Poison counting process and renewal processes, Markov chains, branching processes, birth-death processes, and semi-Markov processes.

Applications from communications, networking, and stochastic control. For a long time now there has been ongoing interest in distributed computation anddecision making problems of all types. Among these are consensus and flocking problems, the multi-agent rendezvous problem, distributed averaging, localization of sensors in a multi-sensor network, distributed algorithms for solving linear equations, opinion dynamics, distributed state estimation, and the distributed management of multi-agent formations.

The aim of this course isto explain what these problems are and to discuss their solutions. Related concepts from spectral graph theory, rigid graph theory, non-homogeneous Markov chain theory, stability theory, and linear system theory will be covered. Although most of the mathematics need will be covered in the lectures, students taking this course should have a working understanding of basic linear algebra.

The course is open to all students. Undergraduates interested in taking the course should first contact the course instructor. This is an interdisciplinary course with a focus on the emerging science of complex networks and their mathematical models. Students learn about the recent research on the structure and analysis of such networks, and on models that abstract their basic properties. Topics include random graphs and their properties, probabilistic techniques for link analysis, centralized and decentralized search algorithms, random walks, diffusion and epidemic processes, and spectral methods.

This seminar provides an introduction to a rapidly growing and promising area of social scientific research that has accompanied the explosion of data in our digital age, as nearly every aspect of life is now connected e. Students are introduced to various techniques and software for collecting, cleaning, and analyzing data at large scales, especially text data e.

Strong emphasis is placed on integrating these methods into actual research, in hopes of moving new or ongoing student papers toward publication. The course is in a seminar format, with a focus on reading and discussing cutting-edge research, as well as interacting with invited guests from industry e. Google and academia. An overarching goal of the course is to incubate and launch new interdisciplinary collaborative projects at Yale that integrate data science techniques to solve important problems. Global and transregional developments in visual arts from the mid-twentieth century to the present.

Attention to differences masked by stylistic similarities. The emergence of international networks and the possibility of an international style that closely follows worldwide liberalization of economic markets. Basic concepts and results in discrete mathematics: graphs, trees, connectivity, Ramsey theorem, enumeration, binomial coefficients, Stirling numbers.

Properties of finite set systems. The course examines the nature of the intricate networks of macromolecular interactions that underlie the functioning of every cell and the modern biophysical methods available for their study across multiple length, time, and energy scales. Counts as 0. This course aims to expose graduate students to main stochastic modeling methods and solution concepts used to study problems in operations research and management.

The first half of the class will cover analysis of queuing models such as Markovian queues, networks of queues, and queues with general arrival or service distributions, as well as approximation techniques such as heavy traffic approximation. The second part will focus on control of stochastic processes; it will cover finite- and infinite-horizon dynamic programming problems, and special classes such as linear quadratic problems, optimal stopping, and multi-armed bandit problems. Applications of these methods in a broad range of disciplines will be covered in the sequel course MGMT Modeling Operational Processes offered in spring by Professor Rudi.

Each week will focus on one set of network concepts applied in different organizational settings. Basic concepts of Neural-Computing, Learning processes, Single-layer perceptrons, Multilayer perceptrons, Radial-basis function networks, Strategies for avoiding over fitting, Support vector machines, Committee machines, Principal components analysis using neural networks, Self-organizing maps, Information-theoretic models, Stochastic machines, Neurodynamic programming, Temporal processing using feed forward networks, Neurodynamics, Recurrent neural networks. Intelligent control strategies: Expert systems, Fuzzy logic control, neural networks Optimization control techniques: genetic algorithms, simulated annealing, Tabu search Hybrid systems, Applications.

Basic concepts of robotics.

Mathematical description of industrial manipulator. Homogeneous transformation and the Denavit-Hartenberg notationTransformation between framesforward, and inverse kinematics and dynamics Newton - Euler and Lagrange formulations Joint space, and Cartesian space trajectories and dynamic controlTrajectory planning Advance control schemes. Performance specifications.

Stability and performance of feedback systems. Performance limitations. Model uncertainty and robustness. Parameterization of stabilizing controllers Loop transfer recovery robust design control and filtering. Modern Trends in Intelligent Systems and Controls will be covered in this course. Estimation of continuous waveforms, linear estimation, nonlinear modulation theory, detection of Gaussian signals, general binary detection: Gaussian processes, special categories of detection problems.

Preface; Standard notation; Space-time coding notation; Abbreviations; 1Introduction; 2Capacity of multiple-input multiple-output channels; 3Space-time code design criteria; 4Orthogonal space-time block codes; 5Quasi-orthogonal space-time block codes; 6Space-time trellis codes; 7Super-orthogonal space-time trellis codes; 8Differential space-time modulation; 9Spatial multiplexing and receiver design; 10Non-orthogonal space-time block codes; 11Additional topics in space-time coding; Bibliography. Adaptive Wireless Transceivers provides the reader with a broad overview of near instantaneously adaptive transceivers in the context of TDMA, CDMA and OFDM systems The adaptive transceivers examined employ powerful turbo codecs, turbo equalizers and space-time codecs, equipping the reader with a future-proof technological road map It demonstrates that adaptive transceivers are capable of mitigating the channel quality fluctuations of the wireless channel as a lower-complexity alternative to space-time coding By contrast, if the higher complexity of multiple transmitters and multiple receiver-assisted systems is deemed acceptable, the advantages of adaptability erode.

Introduction to nonlinear dynamics and control Overview of phase plane analysis, describing function and limit cycles. Stabilization and control of nonlinear systems. Synthesis and implementation of digital control systems for complex systems; control configurations; process modeling and identification; Multivariable Control; dynamic matrix control and internal model control; adaptive control systems; Supervisory and optimizing control; applications and case studies for distillation, combustion, heat exchangers, and flow reactors; recent developments in computer process control.

Theoretical foundations of Genetic Algorithms GA , Evolution strategies, Applications of GA in constrained nonlinear optimization problems, Diploid Genetic Algorithms, Recent advances in Genetic Programming GP , Survey of representative applications of evolutionary algorithms in multi-objective optimization problems, Immune inspired systems and their performance comparison with GA and GP, Reading of Recent Journal papers related to evolutionary computation, Implementation of application of Evolutionary, Computation in some applications.

Modern Trends in Intelligent Systems and Control will be covered in this course. Toggle navigation Quick Links. Courses Description Under Graduate Courses EE Electric Circuit Analysis This course covers a variety of topics described as follow: System of units, circuit variables and elements, simple resistive circuits, techniques of circuit analysis, Thevenin and Norton Theorem, inductors and capacitors, transient response of first order RL and RC circuits, natural and step response of RLC circuits, sinusoidal and complex forcing functions, phasors.

EE Network Analysis Network Analysis includes the following areas of studyPhasor Algebra, AC impedance, frequency domain analysis, AC Power, Complex Power, polyphase circuits, power in polyphase systems, AC resonance, Complex frequency, network functions, magnetically coupled networks, frequency characteristics, resonant circuits, two-port networks, the Laplace transform, application of Laplace transform to circuit analysis.

EE Semiconductor Devices Properties of materials that are used for the manufacture of semiconductor devices and how these can be engineered to form functional devices are discussed That includes, general material properties, crystal structure, semiconductor lattices, Miller indices, quantization concept, bond and band energy models, band gap and material classification, intrinsic, n-type, p-type semiconductors and energy levels, carrier generation and properties, density of states, Fermi function, equilibrium carrier concentrations, drift and diffusion concepts with mathematical derivations, constancy of Fermi level, Einstein relationship, pn junction diodes, depletion region and built-in potential vbi , diode biasing, avalanching and zener processes, bjts and other junction devices also the J-FET, MESFET and MOSFET their structures, band diagrams, carrier injection and transport equations.

EE Digital Logic Design Number systems, Boolean and switching algebra, combinational logic, minimization, and programmable logic devicesSequential system fundamentalsArithmetic operations and circuits, MemoryHierarchical structuresDesign and applications Counters and registers, sequential logic applications, memory and storage elements. EE Electrical Machines for Mechanical The Course Covers introduction to machinery principles, Faradays Law, production of induced force on a wire, induced voltage on a conductor moving in a magnetic field, transformers, the equivalent circuit of a transformer, AC machinery fundamentals, synchronous generators and motors, induction motors, DC machinery fundamentals, DC motors and generators, special purpose motors.

EE Electrical Machines Introduction to machinery Principles, for motor, generator and transformer action, Faraday's and Lenz's law, production of induced force, induced voltage on a wire moving in a magnetic field Transformers, Types and construction of transformer, approximate and exact equivalent circuit, open and short-circuit tests, voltage regulation and efficiency DC machinery fundamentals, Commutation in DC machine, power flow and losses in real dc machine DC machine as a motor, Equivalent circuit, Magnetization curve, separately excited dc motor, series dc motor, compounded dc motor, DC machine as a generator, separately excited, shunt and cumulative compounded dc generator, the differentially compounded DC generator Introduction to speed control of single phase and special-purpose motors and their types.

EE Power Generation Systems Power Generation Economics and Steam cycle analysis; Rankin cycle, Carnot cycle, regeneration of feed water heaters, super critical pressure cycle Combined cycle in power generation; Gas-steam turbine, energy analysis of combined cycles Fuels and combustion; energy balance of a steam generator, draught or draft system, fans, heat of combustion, heating values: enthalpy of combustion. EE Power Electronics I Operating characteristics of power semiconductor devices such as Bipolar Junction Transistors, IGBTs, MOSFETs and Thyristors The gate drives circuit characteristics, functional requirements and implementation techniques Understand the operation and characteristics of single and three phase rectifiers with resistive and inductive loads This includes un-controlled, semi controlled and fully controlled rectifiers Switching techniques, analysis and design for dc-dc conversion and types of dc-dc converters Operating techniques and analysis of dc-ac conversion, and pulse width modulation schemes to eliminate harmonics.

EE Industrial Automation Industrial Automation, its hierarchy, control systems and measurement systems are introduced The characteristics of op amps, different types of amplifiers using op amps, and wheatstone bridges are discussed for application in signal conditioning circuits The basics of sensors like rotation, displacement, temperature, force, pressure, level and flow are familiarized The actors like actuators, switches, relays, and motors deliberated The Programmable Logic Controllers PLC , SCADA and communication are studied in detail The principles of developing PLC programs and practical examples of control systems will be also presented The course provides individual hands-on experience in PLC programming.

EE Information and Coding Theory Mathematical analysis of discrete and continuous information sources and communication channels, concepts of mutual information and entropy as mathematical measures for sources and channels, channel capacity, source and channel coding theorems Linear block codes with particular emphasis on cyclic codes Convolutional codes.

EE Power System Analysis Review of basic concepts including transformers, transmission lines and generators Transmission-line parameters, steady-state operation of transmission lines and power flows including the Newton—Raphson method for balanced three-phase steady-state and normal operating conditions Symmetrical faults, symmetrical components, unsymmetrical faults Short-circuit protection, transient stability using swing equation, the equal-area criterion, and multi-machine stability Transient operation of transmission lines including power system over voltages and surge protection.

EE Probabilistic Methods in Electrical Engineering Set-theoretic basis of probability Probabilistic modeling of practical problems. EE Electromagnetic Fields Review of vector analysis, electrostatics in free space, electrostatic fields in matter, solution techniques and boundary value problems, steady electric current, magnetostatics in free space, magnetostatic fields in matter, time-varying electromagnetic fields, propagation of electromagnetic waves, wave reflection and transmission, simple waveguides, simple antennas and radiation. EE Antennas and Antenna Systems Basic antenna theory, dipoles, loops, arrays, the method of moments, antenna measurements, aperture antennas, frequency independent antennas, receiving antennas, optimization, propagation.

EE Stochastic Processes Basic antenna theory, dipoles, loops, arrays, the method of moments, antenna measurements, aperture antennas, frequency independent antennas, receiving antennas, optimization, propagation. EE Advanced Coding Theory Theory and practice of advanced error-control coding techniques Topics include trellis codes, multidimensional codes, Leech lattice, rotationally invariant codes, spectral analysis and transform coding Applications of contemporary coding theory in mobile communications, magnetic and optical recording, high-speed modem, and high-density data storage design are presented.

EE Satellite Communications Introduction to the theory and applications of modern satellite communications Topics include satellite channel characterization, channel impairments and transmission degradation, link calculations, modulation, coding, multiple access, broadcasting, random access schemes, demand assignment, synchronization, satellite switching and onboard processing, integrated service digital satellite networks, and satellite transponder, ground stations, packet switching, optical satellite communications.

EE Advanced Mobile Communications Overview of mobile communications, characterization and modeling of wireless fading dispersive channels, optimum receiver structure, transmission performance in fading channels, diversity and performance improvement, co-channel interference, spread spectrum and multiple access, capacity analysis in cellular environments. EE Lasers and Optical Sources Optical radiation generation and spectral distribution, line-width and probability of transitions.

EE Digital Control Systems Sample-and-hold Discretization of analog systemsDiscrete-time systems analysis and designPole-assignment design and state-estimation Sampled-data transformation of Analog filters Digital filter structures. EE System Identification Introduction to dynamic systems, models, and identification process, Models of linear time invariant systems, Models of time-varying and nonlinear systems, Parametric estimation methods, Convergence and consistency of solutions, Asymptotic distribution, Recursive and non-recursive computation methods, Model selection and validation.

EE Adaptive Control Introduction, Real-time parameter estimation, Auto-tuning, Gain scheduling, Self-tuning, regulators, Model-reference adaptive systems, Stability, convergence, and robustness, Stochastic adaptive control, Alternatives to adaptive control, Implementation, Applications and case studies. Each stream is used to modulate one of the subchannels. Ideally, the subchannel bandwidths are narrow enough that the fading on each subchannel is flat as opposed to frequency selective, thereby eliminating ISI.

The simplest approach is to. This is called orthogonal frequency division multiplexing, which can be implemented efficiently using the fast Fourier transform invertible mapping from the time domain to the frequency domain to separate the subchannels in the receiver. In this case the entire signal bandwidth experiences frequency-selective fading because wideband channels tend to have different fading characteristics at different frequencies, and so some of the subchannels will have weak SNRs.

Their performance can be improved by coding across subchannels, frequency equalization, or adding more bits in subchannels with high SNRs. Multicarrier modulation offers an advantage in that less training is required for frequency equalization than for time equalization. However, time-varying fading, frequency offset, and timing mismatch impair the separation of the subchannels, resulting in self-interference. Moreover, multicarrier signals tend to have a large peak-to-average signal-power ratio, which severely degrades the power efficiency when nonlinear amplifiers are used.

Each channel is spread over the larger bandwidth by a pseudo-noise sequence, which is used by receivers to invert the spreading operation and recover the original data. Spread-spectrum techniques first achieved widespread use in military applications because they ''hide" the signal below the noise floor during transmission, reduce the effects of narrowband jamming, and reduce multipath fading. There are two common forms of this technique: direct sequence, in which the data sequence is multiplied by the pseudo-noise sequence, and frequency hopping, in which the carrier frequency is varied by the sequence.

During the demodulation process, multipath signal components and interference are reduced in two stages: First the spectrum-spreading modulation is removed, and then the remaining signal is demodulated using conventional frequency- or phase-shift techniques to obtain the original data signal. In direct-sequence systems, the received signal is multiplied with an exact copy of the code sequence, perfectly synchronized in time. When narrowband interference and delayed multipath signal components are multiplied by the spreading sequence, their signal power is spread over the bandwidth of the spread-spectrum code.

A narrowband filter can be used in the demodulator to remove most of their power. Alternatively, a RAKE receiver can be used to combine all multipath components coherently. In many modern wireless systems, multiple users share the same bandwidth, creating a need for a protocol that ensures efficient, equitable channel access.

Wireless-channel access issues are complicated by the variability and statistical nature of user traffic: Voice traffic typically requires a 40 percent duty cycle i. All traffic generally varies depending on how many transmitters are active. In addition, many new applications do not exhibit the symmetric two-way flow of voice data that is characteristic of standard telephone service.

In typical surfing of the World Wide Web, for example, to 1, times more data flows to the user than from the user. This variability and asymmetry are creating a need for new access strategies for digital integrated networks. Channel sharing through fixed-allocation, demand-assigned, or random-allocation modes is called multiple access.

Fixed-allocation multiple-access techniques assign dedicated channels to multiple users through some type of channel resource division. The assignments are made by a protocol for the duration of a single transmission. In TDMA time is divided into orthogonal slots that are allocated to different users. In CDMA which is the same as direct sequence spread spectrum time and bandwidth are used simultaneously by different users, modulated by different spreading signals, or codes.

The spreading codes allow receivers to separate the signal of interest from the CDMA channel. The three primary competing U. The debates over multiple access among standards committees and equipment providers have led to numerous analytical studies claiming the superiority of one technique or another e. However, there is no widespread agreement as to which access technique is the best.

Theoretical analysis indicates that under heavy traffic conditions CDMA combined with some form of detecting all users simultaneously 9 using knowledge. The TDMA and FDMA techniques place hard limits on the number of users sharing a given bandwidth because each time or frequency slot can support a maximum of one user less than one if multiple slots are assigned to the same user. In general FDMA is the simplest technique to implement, TDMA is slightly more complex because of the requirement for time synchronization among all the users, and CDMA is the most complex because of the need for code synchronization.

Another consideration with respect to CDMA is the need for stringent power control to prevent the "near-far problem," which arises when signals from mobile units close to the base station overwhelm those of units farther away. Such control is difficult to maintain in a fading environment and is one of the major challenges of spread-spectrum multiple access. Fixed-allocation multiple-access techniques are inefficient for many voice and data applications because the variability in traffic from a single transmitter limits throughput on dedicated channels.

For example, a single channel in a two-way voice conversation usually occupies less than half of the available bandwidth; for many data applications the traffic is even more intermittent. Cellular and satellite systems generally serve a slowly changing set of active terminals with a relatively fixed traffic pattern. The inability to predict terminal traffic requirements accurately and the need to handle a dynamic set of active terminals create a need for more flexible forms of multiple access.

One method of providing flexibility is the assignment of network channels to remote terminals on demand. In these systems a common signaling channel is assigned to handle requests from transmitters for network capacity. Demand-assigned multiple access DAMA is very efficient as long as the "overhead" traffic required to assign channels is a small percentage of the message traffic and as long as the message traffic is fairly steady. Otherwise two types of problems can arise.

First there is a set-up delay, or latency period. For transmissions of sufficient length this is not a serious limitation, but for networks with a considerable amount of short, interactive messages the delay and overhead of each message make demand-based assignment impractical. When networks serve a wide variety of data rates and the traffic consists of small messages that are roughly the same size as the overhead messages of the access protocol, DAMA is not an efficient use of channel resources.

The random-access CDMA approach requires complex receivers that can demodulate all possible spreading codes. In ALOHA random access, channel packets are stored at each terminal and transmitted over a common channel to the hub station; no attempt is made to synchronize transmissions from the various users. This technique has high reliability in moderate network traffic, but the probability of a collision between packets from different users increases with the traffic.

Therefore, such channels are usually sized to operate at about 10 percent of the peak data rate. In wireless networks, ALOHA channels rarely operate at more than 10 kbps or 20 kbps in terrestrial systems and 56 kbps in satellite systems. Throughput is not necessarily the most appropriate performance measure for a multiple-access channel. In the case of power-limited satellite channels or battery-operated transmitters, access efficiency is a more appropriate measure.

The access efficiency of an ALOHA random-access channel is the ratio of spectral link efficiency using the ALOHA protocol to the spectral link efficiency of a continuously transmitting channel with the same average power and total bandwidth. The access efficiency of an ALOHA channel approaches 1 meaning no restrictions are needed on throughput when most users are idle and transactions are brief, as can be the case for some data communications systems.

In other words, this technique offers the highest throughput of any random-access protocol under these conditions. It is much easier to design an access protocol for a single type of network traffic rather than for a range of traffic types. All the major. The resulting throughput is adequate for voice applications, but when a network handles data as well as voice the connection-oriented architecture limits the channel throughput. It is difficult to size channels that are assigned on demand for a wide and unpredictable range of user data rates.

New, highly flexible random-access structures will probably be needed to enable the seamless integration of data service within a voice network as promised in some new personal communications networks. The choice of an architecture for a two-way wireless network involves numerous issues dealing with the most fundamental aspects of network design. The primary issue is whether to use a peer-to-peer or a base-station-oriented network configuration. In a peer-to-peer architecture, communication flows directly among the nodes in the network and the end-to-end process consists of one or more individual communication links.

In a base-station-oriented architecture, communication flows from network nodes to a single central hub. The choice of a peer-to-peer or base-station-oriented architecture depends on many factors. Peer-to-peer architectures are more reconfigurable and do not necessarily have a single point of failure, enabling a more dynamic topology.

The multiple hops in the typical end-to-end link offer the advantage of extended communication range, but if one of the nodes fails then the localized link path needs to be reestablished. Base-station-oriented architectures tend to be more reliable because there is only one hop between the network node and central hub. In addition, this design tends to be more cost-efficient because centralized functions at the hub station can control access, routing, and resource allocation.

The wireless base-station-oriented architecture is exemplified by cellular telephone systems, whereas the most common peer-to-peer architecture for wireless systems is a multihop packet radio. Fundamental differences between the two types of systems are indicated in Table One of the biggest challenges in providing multimedia wireless services is to maximize efficient use of the limited available bandwidth. Cellular systems, which exploit the falloff in power at increased distances, reuse the same frequency channel at spatially separated locations.

Frequency reuse increases spectral efficiency but introduces co-channel interference, which affects the achievable BER and data rate of each user. The interference is small if the users operating at the same frequency are far enough apart; however, area spectral efficiency i.

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Thus, good cellular system design places users that share the same channel at a separation distance such that the co-channel interference is just below the maximum tolerable level for the required BER and data rate. Because co-channel interference is subject to shadowing and multipath fading, the design of a static cellular system needs to assume worst-case propagation conditions in determining this separation distance. System performance can be improved through dynamic resource allocation, which involves allocating power and bandwidth based on propagation conditions, user demands, and system traffic; however, the increases in spectral and power efficiency are achieved at the price of increased system complexity.

In cellular systems, a given geographical area such as a city is divided into nonoverlapping cells see Figure and different frequencies are assigned to the cells. In CDMA, interference can be introduced from all users within the same cell as well as from users in other cells. FIGURE In cellular systems each cell has a central hub the base-station-oriented design and is assigned different frequencies, time slots, or codes, depending on how users access the system.

The received SNR for each user is determined by the amount of interference at the receiver; if the system is not interference limited, then spectral efficiency could be further increased by allowing additional users on the system or reusing the frequencies at reduced distances. The transmitter in each cell is connected to a base station and switching office, which allocates channels and controls power. In analog cellular systems, the switching office also coordinates handoffs to neighboring cells when a mobile terminal traverses a cell boundary.

In digital cellular systems and low-tier systems, base stations and terminals play a more active role in coordinating handoffs. The spectral efficiency can be increased by dividing each existing cell into several smaller cells because more users can then be accommodated in the system. However, reducing the cell size increases the rate at which handoffs occur, sometimes affecting higher-level protocols. In general, if the rate of handoff increases, then the rate of call dropping will increase proportionally. Routing is also more dynamic with small cells because routes need to be reestablished whenever a handoff takes place.

A packet radio system provides communications to fixed and mobile network nodes that use radios to form the physical links Lauer, ; Leiner et al. Commercial packet radio networks have been built around single-hop base-station-oriented architectures, as in the Ardis or Mobitex systems, and multihop peer-to-peer architectures, as in the Metricom system see Chapter 1, Section 1. These networks can be constructed with fixed-location infrastructure elements as in Metricom or can achieve connectivity in a completely ad hoc manner.

In general, multihop ad hoc packet-radio networks can be set up, deployed, and redeployed rapidly. These characteristics are important to military operations. However, multihop ad hoc packet radio networks can pose difficulties in defense applications, because a peer-to-peer architecture does not correspond to the military command structure. Many of the challenges in packet radio system design are the same as those for any wide-area wireless communications system.

These issues include how-best to deal with the fading characteristics of RF propagation and whether to use a random or reservation access strategy. Packet radio networks also pose special challenges related to the dynamic nature of the network topology. The terrain, distance between nodes, antenna height, and antenna directionality all influence whether network connectivity can be established and maintained.

Physical connectivity in ad hoc packet radios is more complex than in cellular systems because cell sites cannot be surveyed in advance and may be situated in locations that are difficult to access. Furthermore, it is not economical commercially at least to use large antennas or extensive antenna processing and directionality at each peer-to peer node; the network nodes are all more or less identical, highly portable, and always moving, although additional repeaters can be added within the system to improve performance.

Repeaters demodulate packets, remodulate them, and send them again. Military packet radio systems typically operate at lower frequencies than do cellular systems so as to cover large areas within the battlefield. Active interference needs to be considered in system design, and transmitter power is chosen not only to ensure successful reception at the receiver but also to hide the network from adversaries.

Military packet radio systems make extensive use of spread-spectrum methods for channel access and in general require a higher degree of flexibility in coding. Preamble spreading codes simple versions of the data spreading codes used for synchronization or header information may be different from the codes used during the data portion of the packet, and codes can be changed on a bit-by-bit basis to reduce the probability of interference a feature of second-generation DARPA packet radios. All transmitters use either a common preamble code or a receiver-directed preamble code that directs the transmission to a single node that is tuned to the specific code.

The latter approach makes it possible for multiple packets to be in the air yet have a low probability of interference. Any system using a fixed assignment of network resources needs to be designed based on worst-case signal propagation and interference assumptions. A more efficient strategy is dynamic resource allocation, in which channels, data rates, and power levels are assigned depending on the current interference, propagation, and traffic conditions.

For cellular systems, dynamic resource allocation includes assignment of channels to base stations. Dynamic channel allocation in cellular systems improves channel efficiency by a factor of two or more, even when using simple algorithms Katzela and Naghshineh, However, analyses of dynamic resource allocation to date have been based on fairly simplistic system assumptions, such as fixed traffic intensity, homogenous user demands, fixed reuse constraints, and static channels and users. Little work has been done on resource allocation strategies that consider simultaneous, random variations in traffic, propagation, and user mobility.

The extent to which system performance can be improved under realistic conditions remains an open and challenging research problem with respect to both cellular and packet-radio architectures. Previous research has focused primarily on cellular systems; little attention has been devoted to peer-to-peer networks. An emerging and important research area focuses on reducing the complexity of dynamic resource allocation, particularly in systems with small cells and rapidly changing propagation conditions and user demands.

Even under simplistic assumptions of fixed conditions, optimizing channel allocation is highly complex. Current allocation procedures are not easily generalized to incorporate power control, traffic classes e. In addition, the efficiency of dynamic resource allocation is most pronounced under light loading conditions.

Thus, the optimal dynamic resource allocation strategy is also dependent on traffic conditions. For elements of a system to communicate, they must be compatible. One way to achieve compatibility is to mandate a "point design" in which all devices conform to the same standard. As described in Chapter 1, this approach was taken for first-generation cellular systems in the United States and in second-generation systems in Europe.

As used in this report, the term "interoperability" refers to the capability of network elements that do not conform to the same standard to communicate.


Interoperability can be achieved in two ways using different enabling devices: gateways and adapters. In the compatibility context, a gateway is a device that conforms to more than one standard, whereas an adapter translates information formats between two standards. A cable-ready television set is an example of a gateway, and a set-top box is an example of an adapter.

With respect to military wireless communications systems, there will be no convergence to a single technology in the foreseeable future, for many reasons. The number of incompatible systems will remain high, and yet evolving military missions will require increasing communications between individuals and machines using different systems.

As a consequence, interoperability among these systems will be essential. In sophisticated multimedia networks such as the ones required for military operations in the next century, interoperability is necessary at all layers of a communication protocol. The Internet approach to interoperability is a narrow-waist protocol suite with compatibility at the middle layers TCP and IP and diversity at higher i.

Although this approach can be adopted in all types of communications systems, there are several physical-layer problems unique to wireless communications. For example, wireless systems may operate in different frequency bands and use different modulation and coding techniques. Multimode radios are gateways that address these problems. The commercial dual-mode cellular telephone is an example of this type of radio. The software radio is a promising means of achieving interoperability at the physical layer. Software radio receivers digitize the RF signal and implement most receiver functions by means of software running on general-purpose hardware see Section 2.

Similarly, transmitters synthesize waveforms in digital format and convert them to analog prior to amplification. A software radio can be programmed to be compatible with a number of communications systems and provide interoperability across the required data encoding, transmit waveforms and bandwidths, timing, and clock accuracy of the individual modes. Chapter 3 Section. However, current-generation software radios are limited in terms of the range of radio waveforms they can handle. There are various possibilities depending on network architecture.

In peer-to-peer networks, the terminals need to be capable of implementing all coexisting technologies. In this case any terminal would be capable of communicating with any other terminal within range; the disadvantage would be the added cost, weight, and power drain relative to single-mode terminals.

On the other hand, in base-station-oriented networks, it may be possible to concentrate the tasks of interoperability in base stations. This approach has the disadvantage of disabling communications between terminals when base stations are out of service. This issue could be addressed in research on network architectures see Chapter 4. The routing of messages through a multihop packet-radio network requires the identification of existing communication links and an assessment of their relative quality.

Routing protocols perform these tasks. The best route is the one with the smallest number of hops providing acceptable connectivity; the link quality can be determined by measuring signal strength, SNR, or BER. Poor link quality can be improved to some extent through the use of higher transmission power, wider spreading codes, aggressive hop-by-hop error correction, or retransmission schemes. However, link capacity is also a function of the traffic on nearby links; it may be necessary to route around nodes experiencing heavy congestion. In general, network topologies vary rapidly in mobile packet radio networks, with links constantly being lost and new ones established.

Therefore, the network management component needs to disseminate connectivity information more rapidly than is necessary in wired networks. The network also needs to be able to handle gracefully any network partitions caused by link outages, which are more likely to occur in mobile packet radio networks than in a conventional wired network. Routing algorithms choose a hop-by-hop path based on information about link connectivity. The simplest scheme is flooding, in which a packet is transmitted on all links from the source to neighboring nodes, which then repeat the process.

Flooding is inefficient but can be the best strategy when a network topology changes rapidly. Another scheme,. Given rapid topology changes, network partitions, and large numbers of nodes, keeping this information updated and available to all nodes is difficult at best. A third scheme is connectionless routing, which requires no knowledge of end-to-end connections.

Packets are forwarded toward their destination, with local nodes adapting to changes in network topology. Connection-oriented and connectionless approaches require that routing information be distributed throughout the network. In small networks this distribution was originally accomplished by a centralized routing server; by now, distributed algorithms with improved scaling behavior have largely replaced centralized servers, especially in large networks.

Each node independently determines the best hop in the direction of the destination, and updated routing tables are periodically exchanged among neighboring nodes. Routing schemes have also been used that combine elements of the centralized and distributed approaches. For very large multihop packet radio networks, such schemes impose a hierarchy on the network topology, hiding changes in the distant parts of the network from local nodes the next-hop routes to distant network nodes are not likely to change as rapidly as are routes within each cluster.

A combined strategy is to use a centralized route server, known as a cluster head, to maintain routes between clusters in the direction of ''border radios. A final routing issue relates to packet forwarding, which is initiated when several transmission attempts fail to deliver a message to the next node. In these cases a node engages in localized rerouting, broadcasting the message to any node that can complete the route. Packet forwarding can cause flooding if multiple nodes hear the request and choose to forward the packet. The process can be optimized by filtering based on overheard traffic: If a node has a packet in its send queue and "hears" the same packet being forwarded from a second node, then the first node assumes that the packet has been sent and removes it from the queue.

The mobile internetworking routing protocols Mobile IP were designed to accommodate the mobility of Internet users. There is some disagreement concerning whether Mobile IP was originally designed for an individual user moving from one fixed location to another Myles et al. Mobile IP has to circumvent the association of IP addresses with specific networks because mobile nodes can attach to and detach from multiple networks as they roam. Changing an IP address on the fly is not always possible.

If the node requires an accurate Domain Name System DNS entry, then the entry will need to be updated as the address changes, and in today's implementation of DNS such an update can be very slow. Communications take place between a sender and receiving mobile host MH. A router called the home agent, which resides in the MH's home network, is responsible for intercepting each packet destined for the home address of a roaming MH. The packet is usually sent "in care of" another agent, the foreign agent, which resides in the network in which the MH is roaming.

The packet is sent by conventional IP routing to the foreign agent, where the contents i. The MH can transmit information directly to the sender but the sender always directs its own communications to the home network.

Air University Home

The MH can also request a locally assigned care-of IP address in its roaming domain by invoking the dynamic host configuration protocol; this address could be used by the home agent directly, eliminating the foreign agent. When an MH enters a new mobile subnetwork it needs to obtain a care-of address. It can find a foreign agent using a process built on top of the existing Internet control message protocol capabilities for router discovery. Once accepted by the local network, the MH registers its new care-of address with its home agent.

All registration attempts need to be carefully authenticated to prevent a malicious user from hijacking the packets simply by furnishing another care-of address. The Mobile IP specifications use a message authentication code similar to a digital signature based on a secret key shared by the MH and home agent, typically using a secure one-way function called MD5.

Only the MH that knows the secret key can provide the digital signature expected by the home agent. Replay protection is required to prevent a malicious user from falsely registering an MH with a stale care-of address. The major performance challenge is to circumvent the indirect routing among the sender, home agent, and foreign agent. This path can be eliminated if the sender caches bindings between the MH's home and care-of addresses. The management of these bindings is called route optimization.


Until the binding expires because of a time-out, the sender can use the care-of address directly. If the MH moves to a new subnetwork, then it can ask its former foreign agent to forward packets to the new care-of address while also alerting senders of that new address. No single network technology can simultaneously offer wide-area coverage, high bandwidth, and low latency.

In general, networks that span small geographical areas e. To yield flexible connectivity over wide areas, a wireless internetwork needs to be formed from multiple wide-, medium-, and local-area networks interconnected by wired or wireless segments Katz and Brewer, This internetwork is called a wireless overlay network because the WANs are laid on top of the medium- and local-area networks to form a multilayered network hierarchy.

A user operating within the LAN enjoys high bandwidth and low latency, but when communicating outside the local coverage area the user accesses a wider-area network within the hierarchy, typically sacrificing some bandwidth or latency in the process. Future mobile information systems will be built on heterogeneous wireless overlay networks, extending traditional wired and internetworked processing "islands" to hosts on the move over a wide area.

Overlay technologies are used in buildings wireless LANs , in metropolitan areas packet radio , and regional areas satellite. The software radio, with its capability to change frequencies and waveforms as needed, is a critical enabling technology for overlay networks. Handoffs may take place not only "horizontally" within a single network but also "vertically" between overlays. If each overlay network assigns the MH a different IP address, then Mobile IP needs to be extended to correlate all the addresses for one user.

Alternatively, the mobile node can treat each new IP address as a new care-of address. The home agent maintains a table of bindings between the home and locally assigned addresses. The applications running on the MH may participate in the choice of route. For example, an application might specify that high-priority traffic traverse an overlay with low latency.

Less-critical traffic might travel over higher-latency connections. Signal quality, BER, and packet loss and retransmission need to be considered. Under certain conditions such as the transmission of urgent data, a slow-speed overlay with a strong signal strength might be preferred to one with a higher bandwidth but a weaker signal. New protocols are being developed to support convenient operations by mobile users. One example is the service location protocol, which allows user agents to determine access information for generic network services such as printing, faxing, schedule management, file system access, and backup.

A directory agent delivers universal resource locators URLs to user agents, which use the URLs to access service agents. New service agents can register or withdraw their URLs as needed. Much of the protocol research is geared toward enabling the identification of directory agents in unfamiliar environments. Other strategies based on modifications to directory services have been proposed as well. Network performance analysis can take three forms: mathematical analysis, experimental trials, or system simulation.

Mathematical analyses can incorporate only a limited range of realistic phenomena, and field trials are expensive as well as difficult to set up under repeatable conditions. Consequently simulation is often the best tool for optimizing system design and predicting performance. Network-level simulation tools are used to simulate the dynamic behavior of routing, flow, and congestion-mitigation schemes in packet-switched data networks.

These tools can model arbitrary network topologies, link-error models, router scheduling algorithms, and traffic. Performance tools can also help troubleshoot problems in real networks by collecting statistics about the throughput of the various nodes and links. This information can be used to identify bottlenecks and develop remedial strategies such as changing the topology of the network. Debugging tools enable the protocol designer to capture detailed traces of network activity McCanne and Jacobson, ; these tools are invaluable for tracking down errors in protocol implementation.

To model mobile networks accurately, simulators require special features, some of which have yet to be developed. They need to model the nature of errors on the wireless link precisely because errors are not uniformly distributed but rather tend to cluster Nguyen et al. They also need to model node mobility, especially in the case of packet radio networks.

Existing simulation technology consists of good models of radio propagation at microwave frequencies but only standard teletraffic. Some proprietary tools integrate geographical modeling, propagation, and cellular networking behavior, but no integrated tools are available commercially to predict the performance of the next generation of wireless technologies, such as smart radios.

Similarly, existing tools can simulate the creation of relatively narrowband waveforms at the transmitter and analyze the effects of radio propagation on the received signal, but they cannot model the antenna radiation or reception properties of a signal that spans more than 1 GHz of spectrum. No existing tool can model the propagation performance of urban, suburban, rural, or free-space radiation of wideband signal-containing components with diverse propagation characteristics. No tool can analyze the effects of the motion of network elements on the received signal's multipath characteristics, such as spectral nulls and Doppler shift over wide bandwidths.