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Data transmission

About: Data transmission is a research topic. Over the lifetime, 68767 publications have been published within this topic receiving 563195 citations.


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Journal ArticleDOI
TL;DR: An achievable region which combines Gel'fand-Pinkser coding with an achievable region construction for the interference channel is developed, which resembles dirty-paper coding, a technique used in the computation of the capacity of the Gaussian multiple-input multiple-output (MIMO) broadcast channel.
Abstract: Cognitive radio promises a low-cost, highly flexible alternative to the classic single-frequency band, single-protocol wireless device. By sensing and adapting to its environment, such a device is able to fill voids in the wireless spectrum and can dramatically increase spectral efficiency. In this paper, the cognitive radio channel is defined as a two-sender, two-receiver interference channel in which sender 2 obtains the encoded message sender 1 plans to transmit. We consider two cases: in the genie-aided cognitive radio channel, sender 2 is noncausally presented the data to be transmitted by sender 1 while in the causal cognitive radio channel, the data is obtained causally. The cognitive radio at sender 2 may then choose to transmit simultaneously over the same channel, as opposed to waiting for an idle channel as is traditional for a cognitive radio. Our main result is the development of an achievable region which combines Gel'fand-Pinkser coding with an achievable region construction for the interference channel. In the additive Gaussian noise case, this resembles dirty-paper coding, a technique used in the computation of the capacity of the Gaussian multiple-input multiple-output (MIMO) broadcast channel. Numerical evaluation of the region in the Gaussian noise case is performed, and compared to an inner bound, the interference channel, and an outer bound, a modified Gaussian MIMO broadcast channel. Results are also extended to the case in which the message is causally obtained.

1,157 citations

Journal ArticleDOI
TL;DR: The authors provide a comprehensive survey of different modulation recognition techniques in a systematic way, and simulated some major techniques under the same conditions, which allows a fair comparison among different methodologies.
Abstract: The automatic recognition of the modulation format of a detected signal, the intermediate step between signal detection and demodulation, is a major task of an intelligent receiver, with various civilian and military applications. Obviously, with no knowledge of the transmitted data and many unknown parameters at the receiver, such as the signal power, carrier frequency and phase offsets, timing information and so on, blind identification of the modulation is a difficult task. This becomes even more challenging in real-world scenarios with multipath fading, frequency-selective and time-varying channels. With this in mind, the authors provide a comprehensive survey of different modulation recognition techniques in a systematic way. A unified notation is used to bring in together, under the same umbrella, the vast amount of results and classifiers, developed for different modulations. The two general classes of automatic modulation identification algorithms are discussed in detail, which rely on the likelihood function and features of the received signal, respectively. The contributions of numerous articles are summarised in compact forms. This helps the reader to see the main characteristics of each technique. However, in many cases, the results reported in the literature have been obtained under different conditions. So, we have also simulated some major techniques under the same conditions, which allows a fair comparison among different methodologies. Furthermore, new problems that have appeared as a result of emerging wireless technologies are outlined. Finally, open problems and possible directions for future research are briefly discussed.

1,140 citations

Journal ArticleDOI
TL;DR: In this paper, the authors consider a point-to-point data transmission with an energy harvesting transmitter which has a limited battery capacity, communicating in a wireless fading channel, and they consider two objectives: maximizing the throughput by a deadline, and minimizing the transmission completion time of the communication session.
Abstract: Wireless systems comprised of rechargeable nodes have a significantly prolonged lifetime and are sustainable. A distinct characteristic of these systems is the fact that the nodes can harvest energy throughout the duration in which communication takes place. As such, transmission policies of the nodes need to adapt to these harvested energy arrivals. In this paper, we consider optimization of point-to-point data transmission with an energy harvesting transmitter which has a limited battery capacity, communicating in a wireless fading channel. We consider two objectives: maximizing the throughput by a deadline, and minimizing the transmission completion time of the communication session. We optimize these objectives by controlling the time sequence of transmit powers subject to energy storage capacity and causality constraints. We, first, study optimal offline policies. We introduce a directional water-filling algorithm which provides a simple and concise interpretation of the necessary optimality conditions. We show the optimality of an adaptive directional water-filling algorithm for the throughput maximization problem. We solve the transmission completion time minimization problem by utilizing its equivalence to its throughput maximization counterpart. Next, we consider online policies. We use stochastic dynamic programming to solve for the optimal online policy that maximizes the average number of bits delivered by a deadline under stochastic fading and energy arrival processes with causal channel state feedback. We also propose near-optimal policies with reduced complexity, and numerically study their performances along with the performances of the offline and online optimal policies under various different configurations.

1,130 citations

Journal ArticleDOI
TL;DR: A class of nonlinear estimation algorithms is described to estimate the unknown phase of a carrier which is fully modulated by m -ary PSK modulation, and the effect of quantization and finite read-only-memory implementation of the nonlinearity are determined by computer simulation.
Abstract: Burst transmission of digital data and voice has become commonplace, particularly in satellite communication systems employing time-division multiple-access (TI)MA) and packet demand-assignment multiple-access (DAMA) techniques. In TDMA systems particularly, phase estimation on each successive burst is a requirement, while bit timing and carrier frequency can be accurately tracked between bursts. A class of nonlinear estimation algorithms is described to estimate the unknown phase of a carrier which is fully modulated by m -ary PSK modulation. Performance of the method is determined in closed form and compared to the Cramer-Rao lower bound for the variance of the estimation error in the phase of an unmodulated carrier. Results are also obtained when the carrier frequency is imprecisely known. Finally, the effect of quantization and finite read-only-memory (ROM) implementation of the nonlinearity are determined by computer simulation.

1,116 citations

Journal ArticleDOI
TL;DR: This demonstrates that statistical or asynchronous time-division multiplexing (TDM) can efficiently absorb temporal variations of the bit rate of individual sources without the significant variations in reception quality exhibited by multimode videocoders for synchronous TDM or circuit-switched transmission.
Abstract: Models and results are presented that assess the performance of statistical multiplexing of independent video sources. Presented results indicate that the probability of buffering (or delaying) video data beyond an acceptable limit drops dramatically as the number of multiplexed sources increases beyond one. This demonstrates that statistical or asynchronous time-division multiplexing (TDM) can efficiently absorb temporal variations of the bit rate of individual sources without the significant variations in reception quality exhibited by multimode videocoders for synchronous TDM or circuit-switched transmission. Two source models are presented. The first model is an autoregressive continuous-state, discrete-time Markov process, which was used to generate source data in simulation experiments. The second model is a discrete-state, continuous-time Markov process that was used in deriving a fluid-flow queuing analysis. The presented study shows that both models generated consistent numerical results in terms of queuing performance. >

1,041 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
2023323
2022808
20211,465
20203,232
20194,193