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Smart Transportation
Published in Jianbin Gao, Qi Xia, Kwame Omono Asamoah, Bonsu Adjei-Arthur, Smart Cities, 2023
Jianbin Gao, Qi Xia, Kwame Omono Asamoah, Bonsu Adjei-Arthur
where v is the received signal and v¯ is the average received SNR. m is the Nakagami fading figure, and Γ(·) is the Euler gamma function, represented as Γ(a)=(α−1)!. The Nakagami fading model has been shown to accurately represent a variety of indoor and outdoor multipath mobile signals. The channel approaches an AWGN channel as m approaches infinity. The Nakagami model is utilized in this study to assess the fading channel's capacity and to determine which ranges have a high probability of message reception, on which to base the experiment. The expression is what distinguishes m. m≜Ω2EV2−Ω2
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Published in Philip A. Laplante, Comprehensive Dictionary of Electrical Engineering, 2018
Generally, the power spectral density is expressed in watts per hertz (W/Hz) and the noise power is expressed in watts. See also noise, noise spectrum. noise power ratio (NPR) intermodulation distortion product generated in nonlinear transfer components such as high power amplifiers (HPAs) amplifying multiple carriers. It is defined as a ratio of an averaged power of white noise having a narrow notch, which represents multiple carriers, to an averaged power falling into a narrow bandwidth of notch. noise rejection the ability of a feedback control system to attenuate (reduce) the amplitude of any unwanted signal generated by the measurement of its output variable. noise smoothing any process by which noise is suppressed, following a comparison of potential noise points with neighboring intensity values, as for mean filtering or median filtering. noise spectrum indicates the frequency components in a noise signal. For ideal thermal noise (AWGN), the spectrum is flat across all frequencies and is referred to as the noise power spectral density expressed in watts per hertz (W/Hz). See also noise, noise power.
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Published in Lal Chand Godara, Handbook of Antennas in Wireless Communications, 2018
Clearly, the channel exhibits both fast fading and frequency-selective fading. Recall from Eq. (4.45) and (4.46) that f0 sets an upper limit and fd sets a lower limit on the signaling rate. Thus, the condition described by Eq. (4.50) presents a difficult design problem, because, unless distortion mitigation is provided, the maximum allowable signaling rate is, strictly speaking, less than the minimum allowable signaling rate. Mitigation in this case is similar to the initial approach outlined in case one. Choose a modulation/demodulation technique that is most robust under fast-fading conditions.Use transmission redundancy to increase the transmitted symbol rate.Provide some form of frequency-selective fading mitigation in a manner similar to that outlined in case two.Once the distortion effects have been reduced, introduce some form of diversity (as well as error-correction coding and interleaving), to approach AWGN performance.
Low Complexity Adaptive Spectrum Sensing using Modified FRM Filter Bank
Published in International Journal of Electronics, 2022
where denotes the received signal of the PU channel. The channel gain, , is herein assumed to be constant without loss of generality. The transmitted signal at the PU channel, is taken as independent and identically distributed () with zero mean and variance . The Additive White Gaussian Noise (AWGN) noise, , is also assumed to be an random process with zero mean and variance . The SNR can be defined as the ratio of signal variance to the noise variance. Let be the total number of PUs. Then. the input to the system, which is the summation of the received signal in channels, can be represented as .
Parallel Resource Allocation and Subcarrier Assignment for Downlink OFDMA
Published in IETE Technical Review, 2019
Satyendra Singh Yadav, Paulo Alexandre Crisóstomo Lopes, Sarat Kumar Patra
A cellular network system, which is formed by U uniformly located users in a cell with a single BS as shown in Figure 1 is considered. Resource allocation and subcarrier assignment problems are examined in the downlink scenario with OFDMA technology. The channel consists of N independent parallel narrow-band subcarriers which are distributed over the entire bandwidth B. Hence the channel gain , for uth user on nth subcarrier, can be expressed as [16]: where K is constant for a given environment, is the distance of user u from the base station, α is path-loss exponent (). represents the shadowing effect which is log-normal variable with a standard deviation (). is the small scale fading parameter with Rayleigh distribution. In flat fading, subcarriers suffer due to additive white Gaussian noise (AWGN), which is a zero mean normal distributed random variable with standard deviation σ. The variance and the channel gain to noise ratio (CGNR) for user u on subcarrier n can be presented respectively as: where is the thermal noise power spectral density. Since a wireless system can have finite amount of total transmit power (), it is necessary to allocate the power among the subcarriers subjected to the total power constraint [33]. The CGNR is averaged over the number of users to find the power for each subcarrier The along with the total transmit power () can be used to calculate the power for each subcarrier using the water-filling algorithm. Once the power for each subcarrier is calculated, the received SNR for user u on subcarrier n can be expressed as: where is the power for subcarrier n, obtained from the water-filling algorithm. Here the power is assumed to be independent of the users and depends only on the subcarriers. The total power of a particular user will be the sum of the powers allocated to their assigned subcarriers.