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Abstract

network channel scheme

Appazova S.S. Course on a subject «Systems, channels and communication networks». Project manager is Aslanov M.T. After collecting and processing the literature on a given topic in the course work, you need to identify the underlying problem, think about how it can be solved. To answer the question that needs to be done to resolve it, you actually get the goal of the course work, it will be based on the theoretical and practical part and formed a project plan.

In the first part of course work describes systems, channels and communication networks, block diagram, general immunity of radio, the passage of noise through the path of the receiving device. And also made the choice and justification of the structural scheme and the circuit diagram. The second part consists of part of the settlement, where calculated the necessary data transmission speed and the duration of single elements, bandwidth filters transmission and reception, the effective value of interference in the channel, time of entry into synchronism and synchronization reference time fluctuations.

The project is implemented in the program Word 2010 environment . This course work consists pages, figures and basic material from books.

Introduction

The actuality of the Internet is boundless. Networks in Our Daily Lives is very important part. Among all of the essentials for human existence, the need to interact with others ranks just below our need to sustain life. Communication is almost as important to us as our reliance on air, water, food, and shelter.

The scientific value and novelty of the project are as important. Technology Then and Now is different. Imagine a world without the Internet. No more Google, YouTube, instant messaging, Facebook, Wikipedia, online gaming, Netflix, iTunes, and easy access to current information. No more price comparison websites, avoiding lines by shopping online, or quickly looking up phone numbers and map directions to various locations at the click of a finger. How different would our lives be without all of this? That was the world we lived in just 15 to 20 years ago. But over the years, data networks have slowly expanded and been repurposed to improve the quality of life for people everywhere.

The aim of subjects is to describe the principles and methods of transmission of digital signals, the scientific foundations of the current state of technology and digital communications; give an idea of the possibilities and limits of the natural implementation of digital transmission systems and processing, to understand the laws that determine the properties of the data devices and objectives of their operation. It extends and develops the training of telecommunication engineers, master modern technology, construction and transmission of digital information.

The practical importance of the project is the creation and interconnection of robust data networks has had a profound effect on communication, and has become the new platform on which modern communications occur.

1. Signals, channels and communication networks

In telecommunications and computer networking, a communication channel or channel, refers either to a physical transmission medium such as a wire, or to a logical connection over a multiplexed medium such as a radio channel. A channel is used to convey an information signal, for example a digital bit stream, from one or several senders (or transmitters) to one or several receivers. A channel has a certain capacity for transmitting information, often measured by its bandwidth in Hz or its data rate in bits per second.

Communicating data from one location to another requires some form of pathway or medium. These pathways, called communication channels, use two types of media: cable (twisted-pair wire, cable, and fiber-optic cable) and broadcast (microwave, satellite, radio, and infrared). Cable or wire line media use physical wires of cables to transmit data and information. Twisted-pair wire and coaxial cables are made of copper, and fiber-optic cable is made of glass.

In information theory, a channel refers to a theoretical channel model with certain error characteristics. In this more general view, a storage device is also a kind of channel, which can be sent to (written) and received from (read).

A channel can take many forms. Examples of communications channels include:

1. A connection between initiating and terminating nodes of a circuit.

2. A single path provided by a transmission medium via either

· physical separation, such as by multipair cable or

· electrical separation, such as by frequency-division or time-division multiplexing.

3. A path for conveying electrical or electromagnetic signals, usually distinguished from other parallel paths.

· A storage which can communicate a message over time as well as space

· The portion of a storage medium, such as a track or band, that is accessible to a given reading or writing station or head.

· A buffer from which messages can be 'put' and 'got'. See Actor model and process calculi for discussion on the use of channels.

4. In a communications system, the physical or logical link that connects a data source to a data sink.

5. A specific radio frequency, pair or band of frequencies, usually named with a letter, number, or codeword, and often allocated by international agreement.Examples:

· Marine VHF radio uses some 88 channels in the VHF band for two-way FM voice communication. Channel 16, for example, is 156.800 MHz. In the US, seven additional channels, WX1 - WX7, are allocated for weather broadcasts.

· Television channels such as North American TV Channel 2 = 55.25 MHz, Channel 13 = 211.25 MHz. Each channel is 6 MHz wide. Besides these "physical channels", television also has "virtual channels".

·

· Wi-Fi consists of unlicensed channels 1-13 from 2412 MHz to 2484 MHz in 5 MHz steps.

· The radio channel between an amateur radio repeater and a ham uses two frequencies often 600 kHz (0.6 MHz) apart. For example, a repeater that transmits on 146.94 MHz typically listens for a ham transmitting on 146.34 MHz. [1]

All of these communications channels share the property that they transfer information. The information is carried through the channel by a signal.

A channel can be modelled physically by trying to calculate the physical processes which modify the transmitted signal. For example in wireless communications the channel can be modelled by calculating the reflection off every object in the environment. A sequence of random numbers might also be added in to simulate external interference and/or electronic noise in the receiver.

Statistically a communication channel is usually modelled as a triple consisting of an input alphabet, an output alphabet, and for each pair (i, o) of input and output elements a transition probability p(i, o). Semantically, the transition probability is the probability that the symbol o is received given that i was transmitted over the channel.

Statistical and physical modelling can be combined. For example in wireless communications the channel is often modelled by a random attenuation (known as fading) of the transmitted signal, followed by additive noise. The attenuation term is a simplification of the underlying physical processes and captures the change in signal power over the course of the transmission. The noise in the model captures external interference and/or electronic noise in the receiver. If the attenuation term is complex it also describes the relative time a signal takes to get through the channel. The statistics of the random attenuation are decided by previous measurements or physical simulations.

Channel models may be continuous channel models in that there is no limit to how precisely their values may be defined. [2]

Communication channels are also studied in a discrete-alphabet setting. This corresponds to abstracting a real world communication system in which the analog->digital and digital->analog blocks are out of the control of the designer. The mathematical model consists of a transition probability that specifies an output distribution for each possible sequence of channel inputs. In information theory, it is common to start with memoryless channels in which the output probability distribution only depends on the current channel input.

A channel model may either be digital (quantified, e.g. binary) or analog.

Types of communications channels

· Digital (discrete) or analog (continuous) channel

· Baseband and passband channel

· Transmission medium, for example a fibre channel

· Multiplexed channel

· Computer network virtual channel

· Simplex communication, duplex communication or half duplex communication channel

· Return channel

· Uplink or downlink (upstream or downstream channel)

· Broadcast channel, unicast channel or multicast channel

Communication keeps a weather forecaster informed of conditions measured by a multitude of sensors. Indeed, the list of applications involving the use of communication in one way or another is almost endless.

In the most fundamental sense, communication involves implicitly the transmission of information from one point to another through a succession of processes, as described here:

1. The generation of a message signal: voice, music, picture, or computer data.

2. The description of that message signal with a certain measure of precision, by a set of symbols: electrical, aural, or visual.

3. The encoding of these symbols in a form that is suitable for transmission over a physical medium of interest.

4. The transmission of the encoded symbols to the desired destination.

5. The decoding and reproduction of the original symbols.

6. The re-creation of the original message signal, with a definable degradation in quality; the degradation is caused by imperfections in the system.

There are, of course, many other forms of communication that do not directly involve the human mind in real time. For example, in computer communications involving communication between two or more computers, human decisions may enter only in setting up the programs or commands for the computer, or in monitoring the results.

Irrespective of the form of communication process being considered, there are three basic elements to every communication system, namely, transmitter, channel, and receiver, as depicted in Figure 1. The transmitter is located at one point in space, the receiver is located at some other point separate from the transmitter, and the channel is the physical medium that connects them. The purpose of the transmitter is to convert the message signal produced by the source of information into a form suitable for transmission over the channel. However, as the transmitted signal propagates along the channel, it is distorted due to channel imperfections. Moreover, noise and interfering signals (originating from other sources) are added to the channel output, with the result that the received signal is a corrupted version of the transmitted signal. The receiver has the task of operating on the received signal so as to reconstruct a recognizable form of the original message signal for a user.

There are two basic modes of communication:

1. Broadcasting, which involves the use of a single powerful transmitter and numerous receivers that are relatively inexpensive to build. Here information-bearing signals flow only in one direction.

2. Point-to-point communication, in which the communication process takes place over a link between a single transmitter and a receiver. In this case, there is usually a bidirectional flow of information-bearing signals, which requires the use of a transmitter and receiver at each end of the link.

3. Communication System

Figure 1. Elements of a communication system.

The broadcasting mode of communication is exemplified by radio and television, and the ubiquitous telephone provides the means for one form of point-to-point communication. Another example of point-to-point communication is the link between an Earth station and a robot navigating the surface of a distant planet.

All these different communication systems as well as others not mentioned here share a common feature: The underlying communication process in each and every one of them is statistical in nature. Indeed, it is for this important reason that much of this book is devoted to the statistical underpinnings of communication systems. In so doing, we develop an exposition of the fundamental issues involved in the study of different communication methodologies and thereby provide a natural forum for their comparative evaluations.

Communications is the study of the transmission of various data through different systems. We can transfer the information from one region to another with out any loss of the data. A communication system is a collection of network systems which includes transmission system, encoder, noisy channel, decoder and receiving system. All these components perform effectively in a good communication system. The block diagram representing the communication system is given below.

Figure 2. Digital Communication Model

The functions of the each systems are described here. Transmitter. Transmitter is the first component in this block diagram. Using this system we can generate the messages which is to be sent through this system. Encoder. Encoder is the second element in the communication system. It performs the encoding of the given data, which means that this system converts the messages in the form of symbols for transmission purpose. In this system, a sequence of characters are created in a special format for an effective transmission. This encoding system is used for security purpose. Noisy Channel:This is the third block in the block diagram of communication system. Noisy channel is nothing but the medium through which the message is transmitted. Messages are conveyed through this channel. Different channels have different strengths and weaknesses. Each channel has its own frequency and different applications have different operating frequencies. Decoder. Decoder is used to decode the encoded message and retrieve the actual message. Decoding must be done correctly . If this part is not performed well then the message which is received might not be correctThis encoding and decoding will be very help full in military and mobile communications. Receiver. This is the final block in block diagram of communication system. This can be said as the target to which the information need to be delivered.

2. Enabling Any-to-Any Communication for Next-Generation Mobile Networks

2.1 Next-Generation Mobile Networks

The mobile cellular telecommunications industry closed the 2009 calendar year with 3.6 billion global customers and generating approximately $700 billion in revenues. The cellular telecommunications industry is poised to grow to more than $850 billion by 2012 and serve an estimated 5 billion customers worldwide¹. And while the global economic downturn is serious business, it doesn't appear that its impact will be as serious for the mobile cellular telecommunications industry as some might have expected.

The cellular telecommunications industry as a whole is expected to continue to grow, which is good news for all members of the wireless service domain. There is, however, a caveat: While strong growth in the sector is expected, that growth will occur in one specific area: mobile data. This growth is largely due to the flattening of the voice and Short Message Service (SMS) markets in the developed world as those markets saturate.

Prior to making significant investments to upgrade the mobile telecommunications infrastructure, it is important to analyse technology trends and determine the most effective use of investment resources. Therefore, it is necessary to identify which processors will best support future growth demands. New processor architectures must offer single software support, while incorporating heightened levels of communication security.

One solution is an advanced communication processor architecture, which enables equipment manufacturers and service providers to overcome the challenges associated with future mobile networks.

The solution in question will incorporate a communication processor built on proven, programmable, and scalable elements, and will enable communication companies to increase their share of the estimated $850 billion market.

Market Impact Analysis. Two of the largest forces driving the cellular communications industry are demand for mobile services and mobile broadband access. By analysing mobile applications from two parameters with regard to the underlying processor or CPU, one can see associated trends. One parameter is the CPU core performance based on the application demands. The other parameter is the number of cores or threads that are demanded by the application.

Plotting these two parameters against each other reveals several underlying trends in the processor market. For instance, when the performance-per-core is plotted against the number of cores required for a broad range of devices it reveals that some applications are CPU-bound and require more CPU power.

These CPU-bound applications tend to be the pure control plane applications, such as an xGSN control plane card; however, other applications are threads-bound and require more threads-per-processor. Threads-bound devices tend to be classic data plane-centric applications, such as transport cards in an RNC.

A set of applications that demand a balance of both core performance and number of cores is key to the market. For example, to meet the demands of mobile broadband, an RNC user-plane application requires the right mix of subscriber density, the demand for four to eight cores in a processor, and subscriber peak throughput (with CPU performance greater than 1.5 GHz).

Therefore, future communications processors must incorporate the correct balance of multicore processors and powerful CPU cores.

2.2 Challenges of Reinventing the Networking Infrastructure

The mobile communications market requires multicore processors to meet consumer trends. However, today's multicore solutions are narrowly focused and do not provide the performance and flexibility needed to adequately address future communication demands.



Figure 3. Any-to-any next generation mobile network

What we are seeing is that the capabilities of current communication processors are either control plane-centric or data plane-centric and, therefore, do not effectively meet consumer demand for both mobile services and data-intensive applications.

Security is another challenge facing the mobile industry. Previous generation cell phones transmitted data over private networks using Asynchronous Transfer Mode (ATM) communication. However, mobile communication is transitioning to use public, unprotected, all-IP-based networks.

Therefore, equipment manufacturers and service providers must develop new methods to ensure privacy for their customers. Furthermore, silicon designers must also contribute by incorporating security engines into their designs to protect data transmission over public networks.

2.3 Leading the Way by Providing Innovative Solutions

Vendors need to innovate and should be looking at the networking space to address the challenges facing the mobile communication industry. A solution is needed that incorporates proven high-performance computing cores and has processor cores that are built on standardised Instruction Set Architecture (ISA) so that equipment manufacturers can use industry-standard development tools.

The cores need to be compatible with a widely deployed software base and enable a Symmetric Multiprocessing (SMP) architecture, which further supports the development of a portable software architecture.

As well as this the solution should use a system-on-chip (SOC) architecture, which is an ultra-efficient message-passing architecture for intra- and inter- processor communications.

This type of architecture provides the deterministic behaviour essential in next-generation networking applications. Deterministic performance is needed in order to comply with service level agreements (SLAs) where network operators must be able to predict the overall system performance of the networking node irrespective of packet size, system loading, or the type of protocol. Finally, the processors need to be scalable enabling equipment manufacturers to implement the solution on a broad range of network applications.

The asymmetric multicore approach enables the processors not only to complete data and control plane operations but also provides solutions for gateway offloads and enterprise routers that require both multicore and high-performance-per-core capabilities. Working together, all the key sub-components create synergies, which enable equipment manufacturers and service providers to excel in the dynamic mobile communication.

Analysing the communication industry reveals that mobile consumers are stretching the traditional data plane and control plane capabilities of today's networks. Equipment manufacturers and service providers must develop and install a more robust infrastructure to offer mobile services and virtually unlimited access to online content.

Unfortunately, many existing silicon solutions fall short in supporting future network operator requirements of achieving cost reductions while meeting and exceeding performance targets. Technology providers need to provide solutions that incorporate proven cores, an innovative SOC architecture, and a scalable platform to simplify the transition as the communication market changes - ultimately enabling service providers and equipment manufacturers to excel in the future mobile communications market.

3. The review of similar schemes

Filters are frequency-selective devices, which will allow or delay the signals, lying in certain frequency bands.

Filters can be classified according to their frequency characteristics:

1. Filters low frequency (LPF) - miss all of oscillations with frequencies do not above a certain cut-off frequency and constant component.

2. Filters high frequency (LPF) - miss all the fluctuations not below a certain cut-off frequency.

3. Band-pass filter (PF) - miss fluctuations in a particular frequency band, which is determined by a certain level of frequency response.

4. Band-suppressing filters (PPF) - detained fluctuations in a particular frequency band, which is determined by a certain level of frequency response.

5. Rejector filters (Russian Federation) - a type of PPF, which has a narrow strip of delay and also called the filter-stopper.

6. Phase filters (FF) - of a permanent in the ideal case of a transfer coefficient at all frequencies and designed to change the phase of the input signal (in particular for temporary delay of signals).

Figure 4. Basic filter types

The choice and justification of the filter circuit

With the help of active RC filter cannot be the ideal form of frequency characteristics in the form shown in figure 1.1 rectangles with a strictly constant coefficient of transmission in bandwidth, the infinite weakening in the suppression and infinite steep decline in the transition from bandwidth to the suppression. The design of the active filter is a search for a compromise between the ideal form of the characteristics and the complexity of its implementation. This is called “the problem of approximation“. In many cases, the requirements to the quality of filtration allow to do the simplest filters of the first and second orders of magnitude. Some of the schemes such filters are presented below. The design of the filter in this case be limited to the choice of the scheme with the most appropriate configuration and subsequent calculation of the values of nominal values of the elements for the specific frequencies.However, there are situations, when the requirements for filtering may be much more stringent and may be required schemes of higher order than the first and the second. The design of the filters high-order is a more complex task, which is devoted to the course work.Below are some of the basic scheme of the first of the second order with a description of the advantages and disadvantages of each of them.

HPF-I and LPF-I on the basis of non-inverting amplifier.

Figure 5. Filters on the basis of a noninverting amplifier: a) HPF-I, b) LPF-I.

The advantages of schemes filters can be attributed mainly ease of implementation and adjustment, disadvantages of low - slope of frequency characteristics,

LPF-II and the HPF-II with a lot of loop feedback.

Figure 6. Filters with feedback: a) LPF-II, b) HPF-II.

Advantages: You can build a low pass filter withRelatively low sensitive adhering to the deviation of the values of the elements (almost always less than 1)

Disadvantages: A relatively small input resistance easy adjustment of only two parameters and a large range of nominal values of elements, especially in the large and the rate of transmission.

4. Implementation of the normalization HPF

Butterworth had a reputation for solving "impossible" mathematical problems. At the time, filter design required a considerable amount of designer experience due to limitations of the theory then in use. The filter was not in common use for over 30 years after its publication. Butterworth stated that:

"An ideal electrical filter should not only completely reject the unwanted frequencies but should also have uniform sensitivity for the wanted frequencies".

Such an ideal filter cannot be achieved but Butterworth showed that successively closer approximations were obtained with increasing numbers of filter elements of the right values. At the time, filters generated substantial ripple in the passband, and the choice of component values was highly interactive. Butterworth showed that a low pass filter could be designed whose cutoff frequency was normalized to 1 radian per second and whose frequency response (gain) was

(1)

where щ is the angular frequency in radians per second and n is the number of reactive elements (poles) in the filter. If щ = 1, the amplitude response of this type of filter in the passband is 1/v2 ? 0.707, which is half power or ?3 dB. Butterworth only dealt with filters with an even number of poles in his paper. He may have been unaware that such filters could be designed with an odd number of poles. He built his higher order filters from 2-pole filters separated by vacuum tube amplifiers. His plot of the frequency response of 2, 4, 6, 8, and 10 pole filters is shown as A, B, C, D, and E in his original graph.

Definition of the required filter order

Butterworth solved the equations for two- and four-pole filters, showing how the latter could be cascaded when separated by vacuum tube amplifiers and so enabling the construction of higher-order filters despite inductor losses. In 1930, low-loss core materials such as molypermalloy had not been discovered and air-cored audio inductors were rather lossy. Butterworth discovered that it was possible to adjust the component values of the filter to compensate for the winding resistance of the inductors.

He used coil forms of 1.25? diameter and 3? length with plug in terminals. Associated capacitors and resistors were contained inside the wound coil form. The coil formed part of the plate load resistor. Two poles were used per vacuum tube and RC coupling was used to the grid of the following tube.

Definition of the polynomial Butterworth

Butterworth also showed that his basic low-pass filter could be modified to give low-pass, high-pass, band-pass and band-stop functionality.

Figure 7. The resonant response of a physical system

0

Figure 8. The typical response of a resonant low-pass filter and high -pass filter

The frequency response of the Butterworth filter is maximally flat (i.e. has no ripples) in the passband and rolls off towards zero in the stopband.^[2] When viewed on a logarithmic Bode plot the response slopes off linearly towards negative infinity. A first-order filter's response rolls off at ?6 dB per octave (?20 dB per decade) (all first-order lowpass filters have the same normalized frequency response). A second-order filter decreases at ?12 dB per octave, a third-order at ?18 dB and so on. Butterworth filters have a monotonically changing magnitude function with щ, unlike other filter types that have non-monotonic ripple in the passband and/or the stopband.

3.4 the Reverse transition from a fixed to a planned HPFCompared with a Chebyshev Type I/Type II filter or an elliptic filter, the Butterworth filter has a slower roll-off, and thus will require a higher order to implement a particular stopband specification, but Butterworth filters have a more linear phase response in the pass-band than Chebyshev Type I/Type II and elliptic filters can achieve.

A third-order low-pass filter (Cauer topology). The filter becomes a Butterworth filter with cutoff frequency щ_c=1 when (for example) C₂=4/3 farad, R₄=1 ohm, L₁=3/2 henry and L₃=1/2 henry.

A simple example of a Butterworth filter is the third-order low-pass design shown in the figure on the right, with C₂ = 4/3 F, R₄ = 1 Щ, L₁ = 3/2 H, and L₃ = 1/2 H.^[3] Taking the impedance of the capacitors C to be 1/Cs and the impedance of the inductors L to be Ls, where s = у + jщ is the complex frequency, the circuit equations yield the transfer function for this device:

(2)

The magnitude of the frequency response (gain) G(щ) is given by

(3)

and the phase is given by

(4)

Gain and group delay of the third-order Butterworth filter with щ_c=1

The group delay is defined as the derivative of the phase with respect to angular frequency and is a measure of the distortion in the signal introduced by phase differences for different frequencies. The gain and the delay for this filter are plotted in the graph on the left. It can be seen that there are no ripples in the gain curve in either the passband or the stop band.

the Transition from the transfer function of the circuitThe log of the absolute value of the transfer function H(s) is plotted in complex frequency space in the second graph on the right. The function is defined by the three poles in the left half of the complex frequency plane.

Log density plot of the transfer function H(s) in complex frequency space for the third-order Butterworth filter with щ_c=1. The three poles lie on a circle of unit radius in the left half-plane.

These are arranged on a circle of radius unity, symmetrical about the real s axis. The gain function will have three more poles on the right half plane to complete the circle.

By replacing each inductor with a capacitor and each capacitor with an inductor, a high-pass Butterworth filter is obtained.

Selecting the active HPF of the third orderA band-pass Butterworth filter is obtained by placing a capacitor in series with each inductor and an inductor in parallel with each capacitor to form resonant circuits. The value of each new component must be selected to resonate with the old component at the frequency of interest.

A band-stop Butterworth filter is obtained by placing a capacitor in parallel with each inductor and an inductor in series with each capacitor to form resonant circuits. The value of each new component must be selected to resonate with the old component at the frequency to be rejected.

Solution

Initial data of the project

Input voltage, U_in = 0,2 мВ 0,0002

Amplification factor, К_U= 10000 10000

Input resistance, R_in = 10 кОм 10000

The range of amplifi frequency, f_Н .. f_В =100…10000000Гц 100

The recession of the amplitude-frequency characteristics on the bottom,

f_Н = 40 дб/дек

Тhe upper frequency, f_В =40 дб/дек

Type of filter = the Butterworth filter

Output current I_out, = 10мА 0,01

Power supply voltage U_ps, = ± 15 В

Proceeding from the formula of determining the coefficient of the gain:

found R2 = 100Ч100000 = 10 МОм.1000000

To reduce the dependence of the offset of the input current is found resistance R3:

Selected resistance R3 = 100 кОм.

The calculation of the filter high frequency.

As the HPF chosen the filter on ИНУН. This scheme allows you to build a filter in the minimum number of elements. It has low-impedance output, the small dispersion of the values of elements and the possibility to receive relatively high values of the coefficient of amplification. [4]

For the Butterworth filter of the second order, from the application A[1], selected coefficients:В = 1,414214; С = 1,000000

The gain for the HPF took K_U = 10;

Choose the value of capacitance of C1 and C2 according to the formula:

С1 = С2 = 10 / f_C = 10 / 1 = 10 мкФ0,1

Took C1 = C2 =10 мкФ.

Calculated the value of the resistors where:

wc = 2ЧpЧf = 2Ч3,14Ч1 = 6,283 рад/с

Chosen R5 = 6.2 кОм.

Chosen R4 = 39 кОм.

Chosen R7 = 6.8 кОм и R6 = 62 кОм.

The gain level shall be determined by the formula [1]:

The resulting gain HPF K_U = 10;

The calculation of the low-frequency filter.

To obtain the total gain to the voltage, satisfying job, from the condition

of the KU preamplifier =100, and the KU HPF= 10, calculated the required

HP-KU

Ratios: В = 1,414214; С = 1,000000;

The gain for the LPF took K_U = 10;

Choose the value of capacitance C3 according to the formula:C3=

С3 = 10 / f_C = 10 / 1000 = 0,01 мкФ

Took С3 = 10 нФ.

Found C4, satisfies the condition:

Took С4 = 91 нФ.

Calculated value сопротивленй by the formulas [1]:

wc = 2ЧpЧf = 2Ч3,14Ч1000 = 6,283Ч10³ рад/с.6280000

Chosen R8 = 12 кОм.

Chosen R9 = 2.4 кОм.

Ом

505,2618357

The gain level shall be determined by the formula [1]:

Chosen R10 = 150 кОм R11 = 16 кОм. Ом

The resulting gain LPF K_U = 10;

Chip selects.

To simplify the calculations take some assumption - operational amplifier will be considered ideal.

Take marginal input parameters: U_in = 0,2 •10^-3 В и f = 1000 Hz.

The voltage at the output of the first stage is:

U_out1 = К_U1 * U_in = 100 • 0,2•10^-3 = 0,02 V.0,02Eoy1

The output voltage of the second stage as well:

U_out2 = К_U2 * U_out1 = 10 • 0,02 = 0,2 V.0,2Eoy2

The output voltage of the third cascade as well:

U_out3 = К_U3 * U_out2 = 10 • 0,2 = 2 V.2Eoy3

Load resistance is defined from the following expression:

For determining the loads were scheme of replacement (Annex 2). For this input voltage presented voltage source Евх = 0,2 •10-3 In, OA replaced voltage sources Eoy1 = 0.02 V Eoy2 = 0.2 V, Еоу3 = 2 V equal to voltage on their output, the input current of the op neglected, but capacitors replaced capacitive resistance

where f is the upper frequency range bandwidth.1,59236E-06

According to the scheme of substitution, using Kirchhoff's laws, amounted to a system of equations:15923,56688

I₁ + I_oy1 - I₂ = 0

I₂ + I₃ - I₄ = 0

I₄ + I_oy2 - I₅ =0

I₅+ I₆ - I₇ = 0

I₇ + I_oy3 = I_н I₁·(R1 + R2) = Eвх - Eoy1

I₂·(- j·Xc1) - I₃·(R5 - j·

Xc2) = Eoy1 I₃·(R5 - j·Xc2) + I₄

R4 = -Eoy2 I₅·R8 - I₆·(R9 - j·Xc4) = Eoy2

I₆·(R9 - j·Xc4) + I₇·(- j·Xc3) = -Eoy3(6)

I11,9604E-08

As a result of solution of the system were the currents in the branches of the system

I₁ = 2 нА, I₂ = 3,77 мкА, I₃ = 1,81 мкА, I₄ = 5,58 мкА, I₅ = 1,07 нА

I₆ = 0,114 мкА, I₇ = 0,113 мкА, I_oy1 = 3,77 мкА, I_oy2 = 5,58 мкА,I_oy3 = 10мА

Select from the directory of the op type К140УД6А with the following parameters:

The nominal value of the supply voltage U_ps = ±15 В.

Amplification factor К_U = 70000

Input offset voltage U_ВХ.СМ. = 5 мВ.

Input bias current I_ВХ.СМ. = 30 нА.

Differential input resistance R_ВХ.ДИФ = 3 MOhm.

Maximum output current I_ВЫХ.MAX. = 25 мА.

Slew rate output voltage V_UВЫХ = 2,5 В/mcs.

That is, the maximum output current of the circuit does not exceed the permissible values for the op-amp, the gain to the voltage of the op-much more than the gain of the cascades and the input resistance many times more than the resistance of a resistor R1.2,5

The procedure of setting adjustment developed filterSetting the filter is not of great complexity. The parameters of the response characteristics of the “adjusted” with the help of resistors, both the first and the second stages independently of each other, with the setting up of a single parameter filter does not affect the values of other parameters.Setting is performed as follows:1. Gain set resistors R2 first and R5 the second stage.2. Frequency pole of the first stage programmable resistor R1, pole frequency of the second stage - resistor R4.3. The quality of the second stage is regulated by the resistor R8, and the quality of the first stage is not regulated by the (constant in all resistor values of the elements).

Conclusions

I considered the main tasks of this course work. Exactly I do independently carry out a mathematical analysis of physical processes in both analog and digital display devices, conversion and signal processing, choose methods of transmitting and receiving signals, work with the hardware generation and signal conversion, control and measuring equipment, measure key parameters of the signals and process results of measurements.

There is a leading provider of innovative silicon, systems and software technologies for products which bring people, information and digital content together.

The methods that we use to communicate are constantly changing and evolving. Whereas we were once limited to face-to-face interactions, breakthroughs in technology have significantly extended the reach of our communications. From cave paintings to the printing press to radio and television, each new development has improved and enhanced our ability to connect and communicate with others.

Networks connect people and promote unregulated communication. Networks are the platforms on which to run businesses, to address emergencies, to inform individuals, and to support education, science, and government. The Internet is the largest network in existence. In fact, the term Internet means a network of networks. It is actually a collection of interconnected private and public networks. It is incredible how quickly the Internet has become an integral part of our daily routines.

In the course of a day, resources that are available through the Internet can help you post and share your photographs, home videos, and experiences with friends or with the world; access and submit school work; communicate with friends, family, and peers using email, instant messaging, or video applications; watch videos, movies, or television episodes on demand, play online games with friends; decide what to wear using online current weather conditions, find the least congested route to your destination by displaying weather and traffic video from webcams; check your bank balance and pay bills electronically.

The list of library

1. Steven W. Smith The Scientist and Engineer's Guide to Digital Signal Processing. -- Second Edition. -- San-Diego: California Technical Publishing, 2008.

2. Britton C. Rorabaugh Approximation Methods for Electronic Filter Design. -- New York: McGraw-Hill, 2007.

3. B. Widrow, S.D. Stearns Adaptive Signal Processing. -- Paramus, NJ: Prentice-Hall, 2012.

4. S. Haykin Adaptive Filter Theory. -- 4rd Edition. -- Paramus, NJ: Prentice-Hall, 2009.

5. Бесчетнова Л.В., Кузьмин Ю.И., Малинин С.И. Схемотехника аналоговых электронных устройств: Письменные лекции. - СПб.: СЗТУ, 2010.

6. Граф Р.Ф., Шиитс В.И. Энциклопедия электронных схем. Том 7.Часть 1. - М.: ДМК, 2010. - 299с.

7. Павлов В.Н., Ногин В.Н. Схематехника аналоговых электронных устройств. - М.: Горячая линия - Телеком, 2001. - 322с.

8. Сапаров В.Е., Максимов Н.А. Системы стандартов в электросвязи и радиоэлектронике: Учебное пособие для вузов. - М.: Радио и Связь, 2008. - 248с.

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