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72-565: If Y {\displaystyle Y} is a Gaussian random variable with mean μ {\displaystyle \mu } and variance σ 2 {\displaystyle \sigma ^{2}} , then X = Y − μ σ {\displaystyle X={\frac {Y-\mu }{\sigma }}} is standard normal and where x = y − μ σ {\displaystyle x={\frac {y-\mu }{\sigma }}} . Other definitions of

144-603: A normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable . The general form of its probability density function is f ( x ) = 1 2 π σ 2 e − ( x − μ ) 2 2 σ 2 . {\displaystyle f(x)={\frac {1}{\sqrt {2\pi \sigma ^{2}}}}e^{-{\frac {(x-\mu )^{2}}{2\sigma ^{2}}}}\,.} The parameter μ {\textstyle \mu }

216-418: A QPSK symbol can allow the phase of the signal to jump by as much as 180° at a time. When the signal is low-pass filtered (as is typical in a transmitter), these phase-shifts result in large amplitude fluctuations, an undesirable quality in communication systems. By offsetting the timing of the odd and even bits by one bit-period, or half a symbol-period, the in-phase and quadrature components will never change at

288-429: A base signal, the carrier wave (usually a sinusoid ), in response to a data signal. In the case of PSK, the phase is changed to represent the data signal. There are two fundamental ways of utilizing the phase of a signal in this way: A convenient method to represent PSK schemes is on a constellation diagram . This shows the points in the complex plane where, in this context, the real and imaginary axes are termed

360-413: A finite number of phases, each assigned a unique pattern of binary digits . Usually, each phase encodes an equal number of bits. Each pattern of bits forms the symbol that is represented by the particular phase. The demodulator , which is designed specifically for the symbol-set used by the modulator, determines the phase of the received signal and maps it back to the symbol it represents, thus recovering

432-405: A fixed collection of independent normal deviates is a normal deviate. Many results and methods, such as propagation of uncertainty and least squares parameter fitting, can be derived analytically in explicit form when the relevant variables are normally distributed. A normal distribution is sometimes informally called a bell curve . However, many other distributions are bell-shaped (such as

504-758: A generic normal distribution with density f {\textstyle f} , mean μ {\textstyle \mu } and variance σ 2 {\textstyle \sigma ^{2}} , the cumulative distribution function is F ( x ) = Φ ( x − μ σ ) = 1 2 [ 1 + erf ⁡ ( x − μ σ 2 ) ] . {\displaystyle F(x)=\Phi \left({\frac {x-\mu }{\sigma }}\right)={\frac {1}{2}}\left[1+\operatorname {erf} \left({\frac {x-\mu }{\sigma {\sqrt {2}}}}\right)\right]\,.} The complement of

576-546: A known approximate solution, x 0 {\textstyle x_{0}} , to the desired Φ ( x ) {\textstyle \Phi (x)} . x 0 {\textstyle x_{0}} may be a value from a distribution table, or an intelligent estimate followed by a computation of Φ ( x 0 ) {\textstyle \Phi (x_{0})} using any desired means to compute. Use this value of x 0 {\textstyle x_{0}} and

648-542: A variance of ⁠ 1 2 {\displaystyle {\frac {1}{2}}} ⁠ , and Stephen Stigler once defined the standard normal as φ ( z ) = e − π z 2 , {\displaystyle \varphi (z)=e^{-\pi z^{2}},} which has a simple functional form and a variance of σ 2 = 1 2 π . {\textstyle \sigma ^{2}={\frac {1}{2\pi }}.} Every normal distribution

720-411: Is a digital modulation process which conveys data by changing (modulating) the phase of a constant frequency carrier wave . The modulation is accomplished by varying the sine and cosine inputs at a precise time. It is widely used for wireless LANs , RFID and Bluetooth communication. Any digital modulation scheme uses a finite number of distinct signals to represent digital data. PSK uses

792-424: Is a normal deviate with parameters μ {\textstyle \mu } and σ 2 {\textstyle \sigma ^{2}} , then this X {\textstyle X} distribution can be re-scaled and shifted via the formula Z = ( X − μ ) / σ {\textstyle Z=(X-\mu )/\sigma } to convert it to

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864-730: Is a version of the standard normal distribution, whose domain has been stretched by a factor σ {\textstyle \sigma } (the standard deviation) and then translated by μ {\textstyle \mu } (the mean value): f ( x ∣ μ , σ 2 ) = 1 σ φ ( x − μ σ ) . {\displaystyle f(x\mid \mu ,\sigma ^{2})={\frac {1}{\sigma }}\varphi \left({\frac {x-\mu }{\sigma }}\right)\,.} The probability density must be scaled by 1 / σ {\textstyle 1/\sigma } so that

936-778: Is advantageous because of a much simpler and easier-to-remember formula, and simple approximate formulas for the quantiles of the distribution. Normal distributions form an exponential family with natural parameters θ 1 = μ σ 2 {\textstyle \textstyle \theta _{1}={\frac {\mu }{\sigma ^{2}}}} and θ 2 = − 1 2 σ 2 {\textstyle \textstyle \theta _{2}={\frac {-1}{2\sigma ^{2}}}} , and natural statistics x and x . The dual expectation parameters for normal distribution are η 1 = μ and η 2 = μ + σ . The cumulative distribution function (CDF) of

1008-394: Is also used quite often. The normal distribution is often referred to as N ( μ , σ 2 ) {\textstyle N(\mu ,\sigma ^{2})} or N ( μ , σ 2 ) {\textstyle {\mathcal {N}}(\mu ,\sigma ^{2})} . Thus when a random variable X {\textstyle X}

1080-862: Is below a chosen acceptably small error, such as 10 , 10 , etc.: x n + 1 = x n − Φ ( x n , x 0 , Φ ( x 0 ) ) − Φ ( desired ) Φ ′ ( x n ) , {\displaystyle x_{n+1}=x_{n}-{\frac {\Phi (x_{n},x_{0},\Phi (x_{0}))-\Phi ({\text{desired}})}{\Phi '(x_{n})}}\,,} where Φ ′ ( x n ) = 1 2 π e − x n 2 / 2 . {\displaystyle \Phi '(x_{n})={\frac {1}{\sqrt {2\pi }}}e^{-x_{n}^{2}/2}\,.} Quadrature phase-shift keying Phase-shift keying ( PSK )

1152-417: Is called a normal deviate . Normal distributions are important in statistics and are often used in the natural and social sciences to represent real-valued random variables whose distributions are not known. Their importance is partly due to the central limit theorem . It states that, under some conditions, the average of many samples (observations) of a random variable with finite mean and variance

1224-428: Is defined as Thus, where Φ ( x ) {\displaystyle \Phi (x)} is the cumulative distribution function of the standard normal Gaussian distribution . The Q -function can be expressed in terms of the error function , or the complementary error function, as An alternative form of the Q -function known as Craig's formula, after its discoverer, is expressed as: This expression

1296-838: Is described by this probability density function (or density): φ ( z ) = e − z 2 2 2 π . {\displaystyle \varphi (z)={\frac {e^{\frac {-z^{2}}{2}}}{\sqrt {2\pi }}}\,.} The variable z {\textstyle z} has a mean of 0 and a variance and standard deviation of 1. The density φ ( z ) {\textstyle \varphi (z)} has its peak 1 2 π {\textstyle {\frac {1}{\sqrt {2\pi }}}} at z = 0 {\textstyle z=0} and inflection points at z = + 1 {\textstyle z=+1} and z = − 1 {\textstyle z=-1} . Although

1368-412: Is equivalent to saying that the standard normal distribution Z {\textstyle Z} can be scaled/stretched by a factor of σ {\textstyle \sigma } and shifted by μ {\textstyle \mu } to yield a different normal distribution, called X {\textstyle X} . Conversely, if X {\textstyle X}

1440-491: Is functionally equivalent to 2-QAM modulation. The general form for BPSK follows the equation: This yields two phases, 0 and π. In the specific form, binary data is often conveyed with the following signals: where f is the frequency of the base band. Hence, the signal space can be represented by the single basis function where 1 is represented by E b ϕ ( t ) {\displaystyle {\sqrt {E_{b}}}\phi (t)} and 0

1512-437: Is itself a random variable—whose distribution converges to a normal distribution as the number of samples increases. Therefore, physical quantities that are expected to be the sum of many independent processes, such as measurement errors , often have distributions that are nearly normal. Moreover, Gaussian distributions have some unique properties that are valuable in analytic studies. For instance, any linear combination of

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1584-409: Is more general than that of BPSK and also indicates the implementation of higher-order PSK. Writing the symbols in the constellation diagram in terms of the sine and cosine waves used to transmit them: This yields the four phases π/4, 3π/4, 5π/4 and 7π/4 as needed. This results in a two-dimensional signal space with unit basis functions The first basis function is used as the in-phase component of

1656-457: Is normally distributed with mean μ {\textstyle \mu } and standard deviation σ {\textstyle \sigma } , one may write X ∼ N ( μ , σ 2 ) . {\displaystyle X\sim {\mathcal {N}}(\mu ,\sigma ^{2}).} Some authors advocate using the precision τ {\textstyle \tau } as

1728-406: Is one of the most spread modulation schemes in application to LEO satellite communications. This variant of QPSK uses two identical constellations which are rotated by 45° ( π / 4 {\displaystyle \pi /4} radians, hence the name) with respect to one another. Usually, either the even or odd symbols are used to select points from one of the constellations and

1800-437: Is only one bit per symbol, this is also the symbol error rate. Sometimes this is known as quadriphase PSK , 4-PSK, or 4- QAM . (Although the root concepts of QPSK and 4-QAM are different, the resulting modulated radio waves are exactly the same.) QPSK uses four points on the constellation diagram, equispaced around a circle. With four phases, QPSK can encode two bits per symbol, shown in the diagram with Gray coding to minimize

1872-463: Is represented by − E b ϕ ( t ) {\displaystyle -{\sqrt {E_{b}}}\phi (t)} . This assignment is arbitrary. This use of this basis function is shown at the end of the next section in a signal timing diagram. The topmost signal is a BPSK-modulated cosine wave that the BPSK modulator would produce. The bit-stream that causes this output

1944-428: Is shown above the signal (the other parts of this figure are relevant only to QPSK). After modulation, the base band signal will be moved to the high frequency band by multiplying cos ⁡ ( 2 π f c t ) {\displaystyle \cos(2\pi f_{c}t)} . The bit error rate (BER) of BPSK under additive white Gaussian noise (AWGN) can be calculated as: Since there

2016-402: Is the mean or expectation of the distribution (and also its median and mode ), while the parameter σ 2 {\textstyle \sigma ^{2}} is the variance . The standard deviation of the distribution is σ {\textstyle \sigma } (sigma). A random variable with a Gaussian distribution is said to be normally distributed , and

2088-414: Is the simplest form of phase shift keying (PSK). It uses two phases which are separated by 180° and so can also be termed 2-PSK. It does not particularly matter exactly where the constellation points are positioned, and in this figure they are shown on the real axis, at 0° and 180°. Therefore, it handles the highest noise level or distortion before the demodulator reaches an incorrect decision. That makes it

2160-400: Is valid only for positive values of x , but it can be used in conjunction with Q ( x ) = 1 − Q (− x ) to obtain Q ( x ) for negative values. This form is advantageous in that the range of integration is fixed and finite. Craig's formula was later extended by Behnad (2020) for the Q -function of the sum of two non-negative variables, as follows: The inverse Q -function can be related to

2232-868: Is very close to zero, and simplifies formulas in some contexts, such as in the Bayesian inference of variables with multivariate normal distribution . Alternatively, the reciprocal of the standard deviation τ ′ = 1 / σ {\textstyle \tau '=1/\sigma } might be defined as the precision , in which case the expression of the normal distribution becomes f ( x ) = τ ′ 2 π e − ( τ ′ ) 2 ( x − μ ) 2 / 2 . {\displaystyle f(x)={\frac {\tau '}{\sqrt {2\pi }}}e^{-(\tau ')^{2}(x-\mu )^{2}/2}.} According to Stigler, this formulation

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2304-1910: The e a x 2 {\textstyle e^{ax^{2}}} family of derivatives may be used to easily construct a rapidly converging Taylor series expansion using recursive entries about any point of known value of the distribution, Φ ( x 0 ) {\textstyle \Phi (x_{0})} : Φ ( x ) = ∑ n = 0 ∞ Φ ( n ) ( x 0 ) n ! ( x − x 0 ) n , {\displaystyle \Phi (x)=\sum _{n=0}^{\infty }{\frac {\Phi ^{(n)}(x_{0})}{n!}}(x-x_{0})^{n}\,,} where: Φ ( 0 ) ( x 0 ) = 1 2 π ∫ − ∞ x 0 e − t 2 / 2 d t Φ ( 1 ) ( x 0 ) = 1 2 π e − x 0 2 / 2 Φ ( n ) ( x 0 ) = − ( x 0 Φ ( n − 1 ) ( x 0 ) + ( n − 2 ) Φ ( n − 2 ) ( x 0 ) ) , n ≥ 2 . {\displaystyle {\begin{aligned}\Phi ^{(0)}(x_{0})&={\frac {1}{\sqrt {2\pi }}}\int _{-\infty }^{x_{0}}e^{-t^{2}/2}\,dt\\\Phi ^{(1)}(x_{0})&={\frac {1}{\sqrt {2\pi }}}e^{-x_{0}^{2}/2}\\\Phi ^{(n)}(x_{0})&=-\left(x_{0}\Phi ^{(n-1)}(x_{0})+(n-2)\Phi ^{(n-2)}(x_{0})\right),&n\geq 2\,.\end{aligned}}} An application for

2376-861: The Q {\textstyle Q} -function, all of which are simple transformations of Φ {\textstyle \Phi } , are also used occasionally. The graph of the standard normal cumulative distribution function Φ {\textstyle \Phi } has 2-fold rotational symmetry around the point (0,1/2); that is, Φ ( − x ) = 1 − Φ ( x ) {\textstyle \Phi (-x)=1-\Phi (x)} . Its antiderivative (indefinite integral) can be expressed as follows: ∫ Φ ( x ) d x = x Φ ( x ) + φ ( x ) + C . {\displaystyle \int \Phi (x)\,dx=x\Phi (x)+\varphi (x)+C.} The cumulative distribution function of

2448-632: The Cauchy , Student's t , and logistic distributions). (For other names, see Naming .) The univariate probability distribution is generalized for vectors in the multivariate normal distribution and for matrices in the matrix normal distribution . The simplest case of a normal distribution is known as the standard normal distribution or unit normal distribution . This is a special case when μ = 0 {\textstyle \mu =0} and σ 2 = 1 {\textstyle \sigma ^{2}=1} , and it

2520-400: The Q -function, all of which are simple transformations of the normal cumulative distribution function , are also used occasionally. Because of its relation to the cumulative distribution function of the normal distribution, the Q -function can also be expressed in terms of the error function , which is an important function in applied mathematics and physics. Formally, the Q -function

2592-448: The bit error rate (BER) – sometimes misperceived as twice the BER of BPSK. The mathematical analysis shows that QPSK can be used either to double the data rate compared with a BPSK system while maintaining the same bandwidth of the signal, or to maintain the data-rate of BPSK but halving the bandwidth needed. In this latter case, the BER of QPSK is exactly the same as

2664-422: The constellation points chosen are usually positioned with uniform angular spacing around a circle . This gives maximum phase-separation between adjacent points and thus the best immunity to corruption. They are positioned on a circle so that they can all be transmitted with the same energy. In this way, the moduli of the complex numbers they represent will be the same and thus so will the amplitudes needed for

2736-850: The double factorial . An asymptotic expansion of the cumulative distribution function for large x can also be derived using integration by parts. For more, see Error function#Asymptotic expansion . A quick approximation to the standard normal distribution's cumulative distribution function can be found by using a Taylor series approximation: Φ ( x ) ≈ 1 2 + 1 2 π ∑ k = 0 n ( − 1 ) k x ( 2 k + 1 ) 2 k k ! ( 2 k + 1 ) . {\displaystyle \Phi (x)\approx {\frac {1}{2}}+{\frac {1}{\sqrt {2\pi }}}\sum _{k=0}^{n}{\frac {(-1)^{k}x^{(2k+1)}}{2^{k}k!(2k+1)}}\,.} The recursive nature of

2808-406: The integral is still 1. If Z {\textstyle Z} is a standard normal deviate , then X = σ Z + μ {\textstyle X=\sigma Z+\mu } will have a normal distribution with expected value μ {\textstyle \mu } and standard deviation σ {\textstyle \sigma } . This

2880-431: The inverse error functions : The function Q − 1 ( y ) {\displaystyle Q^{-1}(y)} finds application in digital communications. It is usually expressed in dB and generally called Q-factor : where y is the bit-error rate (BER) of the digitally modulated signal under analysis. For instance, for quadrature phase-shift keying (QPSK) in additive white Gaussian noise,

2952-495: The BER of BPSK – and believing differently is a common confusion when considering or describing QPSK. The transmitted carrier can undergo numbers of phase changes. Given that radio communication channels are allocated by agencies such as the Federal Communications Commission giving a prescribed (maximum) bandwidth, the advantage of QPSK over BPSK becomes evident: QPSK transmits twice

Q-function - Misplaced Pages Continue

3024-744: The Q-factor defined above coincides with the value in dB of the signal to noise ratio that yields a bit error rate equal to y . The Q -function is well tabulated and can be computed directly in most of the mathematical software packages such as R and those available in Python , MATLAB and Mathematica . Some values of the Q -function are given below for reference. The Q -function can be generalized to higher dimensions: where X ∼ N ( 0 , Σ ) {\displaystyle \mathbf {X} \sim {\mathcal {N}}(\mathbf {0} ,\,\Sigma )} follows

3096-466: The Taylor series expansion above to minimize computations. Repeat the following process until the difference between the computed Φ ( x n ) {\textstyle \Phi (x_{n})} and the desired Φ {\textstyle \Phi } , which we will call Φ ( desired ) {\textstyle \Phi ({\text{desired}})} ,

3168-459: The Taylor series expansion above to minimize the number of computations. Newton's method is ideal to solve this problem because the first derivative of Φ ( x ) {\textstyle \Phi (x)} , which is an integral of the normal standard distribution, is the normal standard distribution, and is readily available to use in the Newton's method solution. To solve, select

3240-401: The above Taylor series expansion is to use Newton's method to reverse the computation. That is, if we have a value for the cumulative distribution function , Φ ( x ) {\textstyle \Phi (x)} , but do not know the x needed to obtain the Φ ( x ) {\textstyle \Phi (x)} , we can use Newton's method to find x, and use

3312-490: The cosine and sine waves. Two common examples are "binary phase-shift keying" ( BPSK ) which uses two phases, and "quadrature phase-shift keying" ( QPSK ) which uses four phases, although any number of phases may be used. Since the data to be conveyed are usually binary, the PSK scheme is usually designed with the number of constellation points being a power of two. BPSK (also sometimes called PRK, phase reversal keying, or 2PSK)

3384-440: The data rate in a given bandwidth compared to BPSK - at the same BER. The engineering penalty that is paid is that QPSK transmitters and receivers are more complicated than the ones for BPSK. However, with modern electronics technology, the penalty in cost is very moderate. As with BPSK, there are phase ambiguity problems at the receiving end, and differentially encoded QPSK is often used in practice. The implementation of QPSK

3456-431: The density above is most commonly known as the standard normal, a few authors have used that term to describe other versions of the normal distribution. Carl Friedrich Gauss , for example, once defined the standard normal as φ ( z ) = e − z 2 π , {\displaystyle \varphi (z)={\frac {e^{-z^{2}}}{\sqrt {\pi }}},} which has

3528-408: The description given for BPSK above. The binary data that is conveyed by this waveform is: 11000110 . Offset quadrature phase-shift keying ( OQPSK ) is a variant of phase-shift keying modulation using four different values of the phase to transmit. It is sometimes called staggered quadrature phase-shift keying ( SQPSK ). Taking four values of the phase (two bits ) at a time to construct

3600-439: The distribution then becomes f ( x ) = τ 2 π e − τ ( x − μ ) 2 / 2 . {\displaystyle f(x)={\sqrt {\frac {\tau }{2\pi }}}e^{-\tau (x-\mu )^{2}/2}.} This choice is claimed to have advantages in numerical computations when σ {\textstyle \sigma }

3672-417: The even (or odd) bits are used to modulate the in-phase component of the carrier, while the odd (or even) bits are used to modulate the quadrature-phase component of the carrier. BPSK is used on both carriers and they can be independently demodulated. As a result, the probability of bit-error for QPSK is the same as for BPSK: However, in order to achieve the same bit-error probability as BPSK, QPSK uses twice

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3744-426: The in-phase and quadrature axes respectively due to their 90° separation. Such a representation on perpendicular axes lends itself to straightforward implementation. The amplitude of each point along the in-phase axis is used to modulate a cosine (or sine) wave and the amplitude along the quadrature axis to modulate a sine (or cosine) wave. By convention, in-phase modulates cosine and quadrature modulates sine. In PSK,

3816-452: The magnitude of jumps is smaller in OQPSK when compared to QPSK. The license-free shaped -offset QPSK (SOQPSK) is interoperable with Feher-patented QPSK ( FQPSK ), in the sense that an integrate-and-dump offset QPSK detector produces the same output no matter which kind of transmitter is used. These modulations carefully shape the I and Q waveforms such that they change very smoothly, and

3888-493: The most robust of all the PSKs. It is, however, only able to modulate at 1   bit/symbol (as seen in the figure) and so is unsuitable for high data-rate applications. In the presence of an arbitrary phase-shift introduced by the communications channel , the demodulator (see, e.g. Costas loop ) is unable to tell which constellation point is which. As a result, the data is often differentially encoded prior to modulation. BPSK

3960-548: The multivariate normal distribution with covariance Σ {\displaystyle \Sigma } and the threshold is of the form x = γ Σ l ∗ {\displaystyle \mathbf {x} =\gamma \Sigma \mathbf {l} ^{*}} for some positive vector l ∗ > 0 {\displaystyle \mathbf {l} ^{*}>\mathbf {0} } and positive constant γ > 0 {\displaystyle \gamma >0} . As in

4032-406: The odd-numbered bits have been assigned to the in-phase component and the even-numbered bits to the quadrature component (taking the first bit as number 1). The total signal – the sum of the two components – is shown at the bottom. Jumps in phase can be seen as the PSK changes the phase on each component at the start of each bit-period. The topmost waveform alone matches

4104-687: The one dimensional case, there is no simple analytical formula for the Q -function. Nevertheless, the Q -function can be approximated arbitrarily well as γ {\displaystyle \gamma } becomes larger and larger. Normal distribution#Standard normal distribution I ( μ , σ ) = ( 1 / σ 2 0 0 2 / σ 2 ) {\displaystyle {\mathcal {I}}(\mu ,\sigma )={\begin{pmatrix}1/\sigma ^{2}&0\\0&2/\sigma ^{2}\end{pmatrix}}} In probability theory and statistics ,

4176-444: The original data. This requires the receiver to be able to compare the phase of the received signal to a reference signal – such a system is termed coherent (and referred to as CPSK). CPSK requires a complicated demodulator, because it must extract the reference wave from the received signal and keep track of it, to compare each sample to. Alternatively, the phase shift of each symbol sent can be measured with respect to

4248-402: The other symbols select points from the other constellation. This also reduces the phase-shifts from a maximum of 180°, but only to a maximum of 135° and so the amplitude fluctuations of π / 4 {\displaystyle \pi /4} -QPSK are between OQPSK and non-offset QPSK. One property this modulation scheme possesses is that if the modulated signal is represented in

4320-412: The parameter defining the width of the distribution, instead of the standard deviation σ {\textstyle \sigma } or the variance σ 2 {\textstyle \sigma ^{2}} . The precision is normally defined as the reciprocal of the variance, 1 / σ 2 {\textstyle 1/\sigma ^{2}} . The formula for

4392-403: The phase can change by 180° at once, while in OQPSK the changes are never greater than 90°. The modulated signal is shown below for a short segment of a random binary data-stream. Note the half symbol-period offset between the two component waves. The sudden phase-shifts occur about twice as often as for OQPSK (since the signals no longer change together), but they are less severe. In other words,

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4464-583: The phase of the previous symbol sent. Because the symbols are encoded in the difference in phase between successive samples, this is called differential phase-shift keying (DPSK) . DPSK can be significantly simpler to implement than ordinary PSK, as it is a 'non-coherent' scheme, i.e. there is no need for the demodulator to keep track of a reference wave. A trade-off is that it has more demodulation errors. There are three major classes of digital modulation techniques used for transmission of digitally represented data: All convey data by changing some aspect of

4536-436: The power (since two bits are transmitted simultaneously). The symbol error rate is given by: If the signal-to-noise ratio is high (as is necessary for practical QPSK systems) the probability of symbol error may be approximated: The modulated signal is shown below for a short segment of a random binary data-stream. The two carrier waves are a cosine wave and a sine wave, as indicated by the signal-space analysis above. Here,

4608-1207: The probability of a random variable, with normal distribution of mean 0 and variance 1/2 falling in the range [ − x , x ] {\textstyle [-x,x]} . That is: erf ⁡ ( x ) = 1 π ∫ − x x e − t 2 d t = 2 π ∫ 0 x e − t 2 d t . {\displaystyle \operatorname {erf} (x)={\frac {1}{\sqrt {\pi }}}\int _{-x}^{x}e^{-t^{2}}\,dt={\frac {2}{\sqrt {\pi }}}\int _{0}^{x}e^{-t^{2}}\,dt\,.} These integrals cannot be expressed in terms of elementary functions, and are often said to be special functions . However, many numerical approximations are known; see below for more. The two functions are closely related, namely Φ ( x ) = 1 2 [ 1 + erf ⁡ ( x 2 ) ] . {\displaystyle \Phi (x)={\frac {1}{2}}\left[1+\operatorname {erf} \left({\frac {x}{\sqrt {2}}}\right)\right]\,.} For

4680-401: The same time. In the constellation diagram shown on the right, it can be seen that this will limit the phase-shift to no more than 90° at a time. This yields much lower amplitude fluctuations than non-offset QPSK and is sometimes preferred in practice. The picture on the right shows the difference in the behavior of the phase between ordinary QPSK and OQPSK. It can be seen that in the first plot

4752-421: The signal and the second as the quadrature component of the signal. Hence, the signal constellation consists of the signal-space 4 points The factors of 1/2 indicate that the total power is split equally between the two carriers. Comparing these basis functions with that for BPSK shows clearly how QPSK can be viewed as two independent BPSK signals. Note that the signal-space points for BPSK do not need to split

4824-481: The signal stays constant-amplitude even during signal transitions. (Rather than traveling instantly from one symbol to another, or even linearly, it travels smoothly around the constant-amplitude circle from one symbol to the next.) SOQPSK modulation can be represented as the hybrid of QPSK and MSK : SOQPSK has the same signal constellation as QPSK, however the phase of SOQPSK is always stationary. The standard description of SOQPSK-TG involves ternary symbols . SOQPSK

4896-581: The standard normal cumulative distribution function, Q ( x ) = 1 − Φ ( x ) {\textstyle Q(x)=1-\Phi (x)} , is often called the Q-function , especially in engineering texts. It gives the probability that the value of a standard normal random variable X {\textstyle X} will exceed x {\textstyle x} : P ( X > x ) {\textstyle P(X>x)} . Other definitions of

4968-783: The standard normal distribution can be expanded by Integration by parts into a series: Φ ( x ) = 1 2 + 1 2 π ⋅ e − x 2 / 2 [ x + x 3 3 + x 5 3 ⋅ 5 + ⋯ + x 2 n + 1 ( 2 n + 1 ) ! ! + ⋯ ] . {\displaystyle \Phi (x)={\frac {1}{2}}+{\frac {1}{\sqrt {2\pi }}}\cdot e^{-x^{2}/2}\left[x+{\frac {x^{3}}{3}}+{\frac {x^{5}}{3\cdot 5}}+\cdots +{\frac {x^{2n+1}}{(2n+1)!!}}+\cdots \right]\,.} where ! ! {\textstyle !!} denotes

5040-600: The standard normal distribution, usually denoted with the capital Greek letter Φ {\textstyle \Phi } , is the integral Φ ( x ) = 1 2 π ∫ − ∞ x e − t 2 / 2 d t . {\displaystyle \Phi (x)={\frac {1}{\sqrt {2\pi }}}\int _{-\infty }^{x}e^{-t^{2}/2}\,dt\,.} The related error function erf ⁡ ( x ) {\textstyle \operatorname {erf} (x)} gives

5112-520: The standard normal distribution. This variate is also called the standardized form of X {\textstyle X} . The probability density of the standard Gaussian distribution (standard normal distribution, with zero mean and unit variance) is often denoted with the Greek letter ϕ {\textstyle \phi } ( phi ). The alternative form of the Greek letter phi, φ {\textstyle \varphi } ,

5184-413: The symbol (bit) energy over the two carriers in the scheme shown in the BPSK constellation diagram. QPSK systems can be implemented in a number of ways. An illustration of the major components of the transmitter and receiver structure are shown below. Although QPSK can be viewed as a quaternary modulation, it is easier to see it as two independently modulated quadrature carriers. With this interpretation,

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