How does compressive sensing improve the efficiency of mobile communications systems in terms of data transmission and storage?
Best insight from top research papers
Compressive sensing improves the efficiency of mobile communication systems in terms of data transmission and storage by reducing power consumption, data communication volume, and energy consumption. It achieves this by exploiting the sparse nature of data and minimizing the number of samples required for reconstruction. Compressive sensing algorithms adapt to the characteristics of the data and optimize the measurement matrix and sparse dictionary, resulting in better performance for signal acquisition and reconstruction in low sampling rate environments . Additionally, compressive sensing enables the processing of compressed signals directly in the compressed domain, reducing the complexity of reconstruction operations . This technique has promising applications in telecommunications, such as spectrum sensing for cognitive radios, where it can extract information from compressed signals using machine learning algorithms with lower complexity compared to traditional detectors .
Answers from top 5 papers
More filters
| Papers (5) | Insight |
|---|---|
8 Citations | Compressive sensing improves efficiency in terms of data transmission and storage by compressing signals using simple linear transformations, saving storage and energy. |
| The provided paper does not specifically mention how compressive sensing improves the efficiency of mobile communications systems in terms of data transmission and storage. | |
06 May 2022 | The provided paper does not specifically mention mobile communications systems or data transmission and storage. It focuses on improving the energy efficiency of wireless sensor networks through compressive sensing. |
01 Dec 2022 | The provided paper does not specifically mention how compressive sensing improves the efficiency of mobile communications systems in terms of data transmission and storage. |
5 Citations | The provided paper does not specifically mention how compressive sensing improves the efficiency of mobile communications systems in terms of data transmission and storage. |
Related Questions
How does sensor technology help enhance efficiency in storage?5 answersSensor technology helps enhance efficiency in storage by addressing various challenges and optimizing energy consumption. One approach is to avoid using void sensors, which are nodes that do not transmit packets and consume energy unnecessarily. Another method is to compress and secure sensor data, reducing communication costs and extending network lifetime. Additionally, inferring sensed data can reduce data volume, leading to reduced bandwidth and battery power consumption while maintaining accuracy. Furthermore, the combination of sensor hardware technology and network bandwidth advancements in the Internet of Things (IoT) enables the development of applications that facilitate efficient data exchange and storage. These approaches collectively contribute to enhancing efficiency in storage by optimizing energy consumption, reducing communication costs, and improving data processing and scheduling in sensor networks.
How does compressed sensing work?5 answersCompressed sensing is a technique that allows for the recovery of sparse signals from a small number of measurements. It works by exploiting the sparsity of the signal, which means that the signal can be represented by a small number of non-zero coefficients in a certain basis. By taking fewer measurements than the traditional Nyquist-Shannon sampling rate, compressed sensing can accurately reconstruct the original signal. This technique has been widely used in various fields such as signal processing, nuclear magnetic resonance imaging, and seismic exploration acquisition. The classical theory of compressed sensing considers random linear measurements or subsampled isometries and has found applications in accelerated magnetic resonance imaging and computed tomography. Compressed sensing is based on the idea of projecting the sparse signal into a low-dimensional space using linear transformation and then accurately recovering the original signal using a nonlinear decoding method. In the context of bio-signal recording, compressed sensing can improve analog-to-digital converter power efficiency by reducing the digitizing rate. Overall, compressed sensing is a promising method that allows for the recovery of sparse signals from under-sampled measurements, with applications in various fields.
What is the purpose to have a compressive strength testing?5 answersCompressive strength testing is conducted to evaluate the strength and durability of building materials, such as concrete and cement mortar. It is an important mechanical property that determines the ability of a material to withstand compressive forces without breaking or deforming. The purpose of compressive strength testing is to assess the performance and quality of the materials used in construction projects. It helps in determining the suitability of materials for specific applications, such as load-bearing structures, and ensures that they meet the required strength standards. Compressive strength testing also allows for the comparison of different materials and mixtures, enabling researchers and engineers to optimize the composition and design of building materials for improved performance and sustainability.
What is compressive strength?4 answersCompressive strength is the ability of a material to withstand loads without deformation or cracking. It is an important property for evaluating the strength of various materials, including concrete and dust aggregates. In the context of concrete, compressive strength is crucial for assessing the quality and durability of structures. Several studies have used machine learning models, such as artificial neural networks and support vector regression, to predict the compressive strength of concrete based on various input variables. These models have shown high accuracy in estimating compressive strength. In the context of dust aggregates, compressive strength plays a key role in understanding the internal structure of protoplanetary disks and celestial bodies like comets and asteroids. Numerical simulations have been used to investigate the compressive strength of dust aggregates, revealing that it becomes significantly harder as the volume filling factor exceeds 0.1. The dominant compression mechanisms vary depending on the volume filling factor, with sliding and twisting motions dominating at high filling factors and rolling motion dominating at low filling factors.
How can radio compression be used to improve the efficiency of wireless communications?5 answersRadio compression can be used to improve the efficiency of wireless communications by reducing redundant bits and increasing information rates. One approach is to use compression coding with forward error correction (FEC) coding, which reduces the proportion of redundant bits relative to information bits transmitted from a transmitter to a receiver. Another method is to compress data intended for a radio terminal in a wireless communication network. This involves receiving a request for data and an indication of compression schemes supported by the radio terminal, forwarding the request to a data provider, compressing the received data with a supported compression scheme, and sending the compressed data to the radio terminal. By applying these compression techniques, power, spectrum, and transmission efficiency can be increased in dual-connection or multi-connection scenarios, leading to improved spectrum efficiency and resource scheduling.
How can I improve my smartphone signal strength?10 answers