Chip and Signature Interleaving in DS CDMA Systems

Siirretty Doriast

The effect of quantized ETF, grouping, and power allocation on non-orthogonal multiple accesses for wireless communication networks

Nonorthogonal multiple access (NOMA) is a significant technology in radio resource sharing and it has been recognized as a favorable method in fifth-generation (5G) wireless networks to meet the requirements of system capacity, service latency, and user connectivity. Many schemes for NOMA have been proposed in the last few years. such as transmitter linear spreading-based NOMA as a code domain, as well as a linear minimum mean square error (LMMSE), parallel interference cancellation (PIC), and serial interference cancellation (SIC) with power allocation and grouping as a power domain at the receiver side for uplink NOMA. This work aims to evaluate the performance of multiple types of linear spreading-based NOMA schemes. Simulations are achieved for the error-rate performance evaluation of these NOMA schemes, received signal after detection, and received signal and effect of every user on the other. Evaluating the performance of these technologies with comparison is also achieved through using grouping and power allocation. Simulations are achieved for the sum rate and spectral efficiency. For the future, 5G NOMA development, an equiangular tight frame (ETF) is suggested for improving performance and suggests grouping with 64qam-quantized Grassmannian for improving performance favorite about grouping with Generalized welch-bound equality (GWBE

External Support Vector Machine Clustering

The external-Support Vector Machine (SVM) clustering algorithm clusters data vectors with no a priori knowledge of each vector\u27s class. The algorithm works by first running a binary SVM against a data set, with each vector in the set randomly labeled, until the SVM converges. It then relabels data points that are mislabeled and a large distance from the SVM hyperplane. The SVM is then iteratively rerun followed by more label swapping until no more progress can be made. After this process, a high percentage of the previously unknown class labels of the data set will be known. With sub-cluster identification upon iterating the overall algorithm on the positive and negative clusters identified (until the clusters are no longer separable into sub-clusters), this method provides a way to cluster data sets without prior knowledge of the data\u27s clustering characteristics, or the number of clusters

External Support Vector Machine Clustering

The external-Support Vector Machine (SVM) clustering algorithm clusters data vectors with no a priori knowledge of each vector\u27s class. The algorithm works by first running a binary SVM against a data set, with each vector in the set randomly labeled, until the SVM converges. It then relabels data points that are mislabeled and a large distance from the SVM hyperplane. The SVM is then iteratively rerun followed by more label swapping until no more progress can be made. After this process, a high percentage of the previously unknown class labels of the data set will be known. With sub-cluster identification upon iterating the overall algorithm on the positive and negative clusters identified (until the clusters are no longer separable into sub-clusters), this method provides a way to cluster data sets without prior knowledge of the data\u27s clustering characteristics, or the number of clusters

Fast Decoder for Overloaded Uniquely Decodable Synchronous CDMA

We consider the problem of designing a fast decoder for antipodal uniquely decodable (errorless) code sets for overloaded synchronous code-division multiple access (CDMA) systems where the number of signals K_{max}^a is the largest known for the given code length L. The proposed decoder is designed in a such a way that the users can uniquely recover the information bits with a very simple decoder, which uses only a few comparisons. Compared to maximum-likelihood (ML) decoder, which has a high computational complexity for even moderate code length, the proposed decoder has a much lower computational complexity. Simulation results in terms of bit error rate (BER) demonstrate that the performance of the proposed decoder only has a 1-2 dB degradation at BER of 10^{-3} when compared to ML

Fly or Cry: Is Airport Noise Costly?

Airport noise is costly. Airport location is typically associated with lower property prices. Airport expansion often sparks protests by local residents. In this paper, I provide new evidence on the costs of airport-related noise (and other disamenities of airports) for individuals. In contrast to previous work, I analyze voting results on restricting airport operations. Using data from a referendum on the closure of one of Berlin’s inner-city airports, Tempelhof, I find that voting behavior is not primarily explained by exposure to airport disamenities. Rather, strong opposition to closure in the vicinity of Tempelhof indicates that adaptive preferences may be important.noise, preferences, traffic, airports

Noise (AWGN) Avoidance in CDMA Systems Using the Mechanism of Spread Spectrum

In today communication systems the most probable problems are that of channel capacity, jamming and interference or noise. The channel capacity can be maximized by multiplexing the channel. While the jamming problem and for noise reduction the most important technique that we can apply is spread spectrum. That by spreading the spectrum of the original message signal, the impact of noise upon the message signal can be reduced. For that purpose, two different techniques that is DSSS(Direct Sequence Spread Spectrum) and FHSS (Frequency Hoping Spread Spectrum) can be applied. Since the two approaches are core ideas upon which CDMA system is based, so in this paper we have analyzed both the techniques to observe that h up to what extent they are efficacious in removing AWGN in CDMA systems communication. IndexTerms:DSSS, FHSS, Code Division Multiple Access (CDMA), Additive White Gaussian Noise (AWGN), spread spectrum