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In telecommunications, an interference is that which modifies a signal in a disruptive manner, as it travels along a communication channel between its source and receiver. The term is often used to refer to the addition of unwanted signals to a useful signal. Common examples include:
Noise is a form of interference but not all interference is noise.
Radio resource management aims at reducing and controlling the co-channel and adjacent-channel interference.
A solution to interference problems in wireless communication networks is interference alignment, which was crystallized by Syed Ali Jafar at the University of California, Irvine. [1] A specialized application was previously studied by Yitzhak Birk and Tomer Kol for an index coding problem in 1998. For interference management in wireless communication, interference alignment was originally introduced by Mohammad Ali Maddah-Ali, Abolfazl S. Motahari, and Amir Keyvan Khandani, at the University of Waterloo, for communication over wireless X channels. [2] Interference alignment was eventually established as a general principle by Jafar and Viveck R. Cadambe in 2008, when they introduced "a mechanism to align an arbitrarily large number of interferers, leading to the surprising conclusion that wireless networks are not essentially interference limited." This led to the adoption of interference alignment in the design of wireless networks. [3]
Jafar explained:
My research group crystallized the concept of interference alignment and showed that through interference alignment, it is possible for everyone to access half of the total bandwidth free from interference. Initially this result was shown under a number of idealized assumptions that are typical in theoretical studies. We have since continued to work on peeling off these idealizations one at a time, to bring the theory closer to practice. Along the way we have made numerous discoveries through the lens of interference alignment, which reveal new and powerful signaling schemes. [4]
According to New York University senior researcher Paul Horn:
Syed Jafar revolutionized our understanding of the capacity limits of wireless networks. He demonstrated the astounding result that each user in a wireless network can access half of the spectrum without interference from other users, regardless of how many users are sharing the spectrum. This is a truly remarkable result that has a tremendous impact on both information theory and the design of wireless networks. [1]
Code-division multiple access (CDMA) is a channel access method used by various radio communication technologies. CDMA is an example of multiple access, where several transmitters can send information simultaneously over a single communication channel. This allows several users to share a band of frequencies. To permit this without undue interference between the users, CDMA employs spread spectrum technology and a special coding scheme.
In telecommunications, orthogonal frequency-division multiplexing (OFDM) is a type of digital transmission used in digital modulation for encoding digital (binary) data on multiple carrier frequencies. OFDM has developed into a popular scheme for wideband digital communication, used in applications such as digital television and audio broadcasting, DSL internet access, wireless networks, power line networks, and 4G/5G mobile communications.
In telecommunications, direct-sequence spread spectrum (DSSS) is a spread-spectrum modulation technique primarily used to reduce overall signal interference. The direct-sequence modulation makes the transmitted signal wider in bandwidth than the information bandwidth. After the despreading or removal of the direct-sequence modulation in the receiver, the information bandwidth is restored, while the unintentional and intentional interference is substantially reduced.
In telecommunications and computer networks, a channel access method or multiple access method allows more than two terminals connected to the same transmission medium to transmit over it and to share its capacity. Examples of shared physical media are wireless networks, bus networks, ring networks and point-to-point links operating in half-duplex mode.
A communication channel refers either to a physical transmission medium such as a wire, or to a logical connection over a multiplexed medium such as a radio channel in telecommunications and computer networking. A channel is used for information transfer of, for example, a digital bit stream, from one or several senders to one or several receivers. A channel has a certain capacity for transmitting information, often measured by its bandwidth in Hz or its data rate in bits per second.
This is an index of articles relating to electronics and electricity or natural electricity and things that run on electricity and things that use or conduct electricity.
A cognitive radio (CR) is a radio that can be programmed and configured dynamically to use the best wireless channels in its vicinity to avoid user interference and congestion. Such a radio automatically detects available channels in wireless spectrum, then accordingly changes its transmission or reception parameters to allow more concurrent wireless communications in a given spectrum band at one location. This process is a form of dynamic spectrum management.
Spectral efficiency, spectrum efficiency or bandwidth efficiency refers to the information rate that can be transmitted over a given bandwidth in a specific communication system. It is a measure of how efficiently a limited frequency spectrum is utilized by the physical layer protocol, and sometimes by the medium access control.
Dynamic spectrum management (DSM), also referred to as dynamic spectrum access (DSA), is a set of techniques based on theoretical concepts in network information theory and game theory that is being researched and developed to improve the performance of a communication network as a whole. The concept of DSM also draws principles from the fields of cross-layer optimization, artificial intelligence, machine learning etc. It has been recently made possible by the availability of software radio due to development of fast enough processors both at servers and at terminals. These are techniques for cooperative optimization. This can also be compared or related to optimization of one link in the network on the account of losing performance on many links negatively affected by this single optimization.
In digital communications shaping codes are a method of encoding that changes the distribution of signals to improve efficiency.
Radio resource management (RRM) is the system level management of co-channel interference, radio resources, and other radio transmission characteristics in wireless communication systems, for example cellular networks, wireless local area networks, wireless sensor systems, and radio broadcasting networks. RRM involves strategies and algorithms for controlling parameters such as transmit power, user allocation, beamforming, data rates, handover criteria, modulation scheme, error coding scheme, etc. The objective is to utilize the limited radio-frequency spectrum resources and radio network infrastructure as efficiently as possible.
In telecommunications, dirty paper coding (DPC) or Costa precoding is a technique for efficient transmission of digital data through a channel subjected to some interference known to the transmitter. The technique consists of precoding the data in order to cancel the interference. Dirty-paper coding achieves the channel capacity, without a power penalty and without requiring the receiver to know the interfering signal.
Edholm's law, proposed by and named after Phil Edholm, refers to the observation that the three categories of telecommunication, namely wireless (mobile), nomadic and wired networks (fixed), are in lockstep and gradually converging. Edholm's law also holds that data rates for these telecommunications categories increase on similar exponential curves, with the slower rates trailing the faster ones by a predictable time lag. Edholm's law predicts that the bandwidth and data rates double every 18 months, which has proven to be true since the 1970s. The trend is evident in the cases of Internet, cellular (mobile), wireless LAN and wireless personal area networks.
In radio, multiple-input and multiple-output, or MIMO, is a method for multiplying the capacity of a radio link using multiple transmission and receiving antennas to exploit multipath propagation. MIMO has become an essential element of wireless communication standards including IEEE 802.11n, IEEE 802.11ac, HSPA+ (3G), WiMAX, and Long Term Evolution (LTE). More recently, MIMO has been applied to power-line communication for three-wire installations as part of the ITU G.hn standard and of the HomePlug AV2 specification.
Radio is the technology of signaling and communicating using radio waves. Radio waves are electromagnetic waves of frequency between 3 hertz (Hz) and 300 gigahertz (GHz). They are generated by an electronic device called a transmitter connected to an antenna which radiates the waves, and received by another antenna connected to a radio receiver. Radio is widely used in modern technology, in radio communication, radar, radio navigation, remote control, remote sensing, and other applications.
Telecommunication is the transmission of information by various types of technologies over wire, radio, optical, or other electromagnetic systems. It has its origin in the desire of humans for communication over a distance greater than that feasible with the human voice, but with a similar scale of expediency; thus, slow systems are excluded from the field.
In mathematics and telecommunications, stochastic geometry models of wireless networks refer to mathematical models based on stochastic geometry that are designed to represent aspects of wireless networks. The related research consists of analyzing these models with the aim of better understanding wireless communication networks in order to predict and control various network performance metrics. The models require using techniques from stochastic geometry and related fields including point processes, spatial statistics, geometric probability, percolation theory, as well as methods from more general mathematical disciplines such as geometry, probability theory, stochastic processes, queueing theory, information theory, and Fourier analysis.
Syed Ali Jafar is an Indian-American electrical engineer and computer scientist. He works at the University of California, Irvine, and has previously worked at Lucent Bell Labs, Qualcomm and Hughes Software Systems. His research interests include multi-user information theory, wireless communications and network coding. He was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2014 "for contributions to analyzing the capacity of wireless communication networks" and won the Blavatnik Award for Young Scientists in 2015 "for his discoveries in interference alignment in wireless networks, changing the field’s thinking about how these networks should be designed."
Electromagnetic radio frequency (RF) convergence is a signal-processing paradigm that is utilized when several RF systems have to share a finite amount of resources among each other. RF convergence indicates the ideal operating point for the entire network of RF systems sharing resources such that the systems can efficiently share resources in a manner that's mutually beneficial. With communications spectral congestion recently becoming an increasingly important issue for the telecommunications sector, researchers have begun studying methods of achieving RF convergence for cooperative spectrum sharing between remote sensing systems and communications systems. Consequentially, RF convergence is commonly referred to as the operating point of a remote sensing and communications network at which spectral resources are jointly shared by all nodes of the network in a mutually beneficial manner. Remote sensing and communications have conflicting requirements and functionality. Furthermore, spectrum sharing approaches between remote sensing and communications have traditionally been to separate or isolate both systems. This results in stove pipe designs that lack back compatibility. Future of hybrid RF systems demand co-existence and cooperation between sensibilities with flexible system design and implementation. Hence, achieving RF convergence can be an incredibly complex and difficult problem to solve. Even for a simple network consisting of one remote sensing and communications system each, there are several independent factors in the time, space, and frequency domains that have to be taken into consideration in order to determine the optimal method to share spectral resources. For a given spectrum-space-time resource manifold, a practical network will incorporate numerous remote sensing modalities and communications systems, making the problem of achieving RF convergence intangible.
Salman A. Avestimehr is a Dean's professor at the Electrical & Computer Engineering and Computer Science Departments of University of Southern California, where he is the inaugural director of the USC-Amazon Center for Secure and Trusted Machine Learning and the director of the Information Theory and Machine Learning (vITAL) research lab. He is also the CEO and Co-Founder of FedML. Avestimehr's contributions in research and publications are in the areas of information theory, machine learning, large-scale distributed computing, and secure/private computing and learning. In particular, he is best known for deterministic approximation approaches to network information theory and coded computing. He was a general co-chair of the 2020 International Symposium on Information Theory (ISIT), and is a Fellow of IEEE. He is also co-authors of four books titled “An Approximation Approach to Network Information Theory”, “Multihop Wireless Networks: A Unified Approach to Relaying and Interference Management”, “Coded Computing”, and “Problem Solving Strategies for Elementary-School Math.”