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.
In response to the operator's commands, the cognitive engine is capable of configuring radio-system parameters. These parameters include "waveform, protocol, operating frequency, and networking". This functions as an autonomous unit in the communications environment, exchanging information about the environment with the networks it accesses and other cognitive radios (CRs). A CR "monitors its own performance continuously", in addition to "reading the radio's outputs"; it then uses this information to "determine the RF environment, channel conditions, link performance, etc.", and adjusts the "radio's settings to deliver the required quality of service subject to an appropriate combination of user requirements, operational limitations, and regulatory constraints".
Some "smart radio" proposals combine wireless mesh network—dynamically changing the path messages take between two given nodes using cooperative diversity; cognitive radio—dynamically changing the frequency band used by messages between two consecutive nodes on the path; and software-defined radio—dynamically changing the protocol used by message between two consecutive nodes.
The concept of cognitive radio was first proposed by Joseph Mitola III in a seminar at KTH Royal Institute of Technology in Stockholm in 1998 and published in an article by Mitola and Gerald Q. Maguire, Jr. in 1999. It was a novel approach in wireless communications, which Mitola later described as:
The point in which wireless personal digital assistants (PDAs) and the related networks are sufficiently computationally intelligent about radio resources and related computer-to-computer communications to detect user communications needs as a function of use context, and to provide radio resources and wireless services most appropriate to those needs.
Cognitive radio is considered as a goal towards which a software-defined radio platform should evolve: a fully reconfigurable wireless transceiver which automatically adapts its communication parameters to network and user demands.
Traditional regulatory structures have been built for an analog model and are not optimized for cognitive radio. Regulatory bodies in the world (including the Federal Communications Commission in the United States and Ofcom in the United Kingdom) as well as different independent measurement campaigns found that most radio frequency spectrum was inefficiently utilized. [2] Cellular network bands are overloaded in most parts of the world, but other frequency bands (such as military, amateur radio and paging frequencies) are insufficiently utilized. Independent studies performed in some countries confirmed that observation, and concluded that spectrum utilization depends on time and place. Moreover, fixed spectrum allocation prevents rarely used frequencies (those assigned to specific services) from being used, even when any unlicensed users would not cause noticeable interference to the assigned service. Regulatory bodies in the world have been considering whether to allow unlicensed users in licensed bands if they would not cause any interference to licensed users. These initiatives have focused cognitive-radio research on dynamic spectrum access.
The first cognitive radio wireless regional area network standard, IEEE 802.22, was developed by IEEE 802 LAN/MAN Standard Committee (LMSC) [3] and published in 2011. This standard uses geolocation and spectrum sensing for spectral awareness. Geolocation combines with a database of licensed transmitters in the area to identify available channels for use by the cognitive radio network. Spectrum sensing observes the spectrum and identifies occupied channels. IEEE 802.22 was designed to utilize the unused frequencies or fragments of time in a location. This white space is unused television channels in the geolocated areas. However, cognitive radio cannot occupy the same unused space all the time. As spectrum availability changes, the network adapts to prevent interference with licensed transmissions. [4]
Depending on transmission and reception parameters, there are two main types of cognitive radio:
Other types are dependent on parts of the spectrum available for cognitive radio:
Although cognitive radio was initially thought of as a software-defined radio extension (full cognitive radio), most research work focuses on spectrum-sensing cognitive radio (particularly in the TV bands). The chief problem in spectrum-sensing cognitive radio is designing high-quality spectrum-sensing devices and algorithms for exchanging spectrum-sensing data between nodes. It has been shown that a simple energy detector cannot guarantee the accurate detection of signal presence, [14] calling for more sophisticated spectrum sensing techniques and requiring information about spectrum sensing to be regularly exchanged between nodes. Increasing the number of cooperating sensing nodes decreases the probability of false detection. [15]
Filling free RF bands adaptively, using OFDMA, is a possible approach. Timo A. Weiss and Friedrich K. Jondral of the University of Karlsruhe proposed a spectrum pooling system, in which free bands (sensed by nodes) were immediately filled by OFDMA subbands. Applications of spectrum-sensing cognitive radio include emergency-network and WLAN higher throughput and transmission-distance extensions. The evolution of cognitive radio toward cognitive networks is underway; the concept of cognitive networks is to intelligently organize a network of cognitive radios.
The main functions of cognitive radios are: [16] [17]
The practical implementation of spectrum-management functions is a complex and multifaceted issue, since it must address a variety of technical and legal requirements. An example of the former is choosing an appropriate sensing threshold to detect other users, while the latter is exemplified by the need to meet the rules and regulations set out for radio spectrum access in international (ITU radio regulations) and national (telecommunications law) legislation.
An intelligent antenna (or smart antenna) is an antenna technology that uses spatial beam-formation and spatial coding to cancel interference; however, applications are emerging for extension to intelligent multiple or cooperative-antenna arrays for application to complex communication environments. Cognitive radio, by comparison, allows user terminals to sense whether a portion of the spectrum is being used in order to share spectrum with neighbor users. The following table compares the two:
Point | Cognitive radio (CR) | Intelligent antenna (IA) |
---|---|---|
Principal goal | Open spectrum sharing | Ambient spatial reuse |
Interference processing | Avoidance by spectrum sensing | Cancellation by spatial precoding/post-coding |
Key cost | Spectrum sensing and multi-band RF | Multiple- or cooperative-antenna arrays |
Challenging algorithm | Spectrum management tech | Intelligent spatial beamforming/coding tech |
Applied techniques | Cognitive software radio | Generalized dirty paper coding and Wyner-Ziv coding |
Basement approach | Orthogonal modulation | Cellular based smaller cell |
Competitive technology | Ultra-wideband for greater band utilization | Multi-sectoring (3, 6, 9, so on) for higher spatial reuse |
Summary | Cognitive spectrum-sharing technology | Intelligent spectrum reuse technology |
Note that both techniques can be combined as illustrated in many contemporary transmission scenarios. [28]
Cooperative MIMO (CO-MIMO) combines both techniques.
Cognitive Radio (CR) can sense its environment and, without the intervention of the user, can adapt to the user's communications needs while conforming to FCC rules in the United States. In theory, the amount of spectrum is infinite; practically, for propagation and other reasons it is finite because of the desirability of certain spectrum portions. Assigned spectrum is far from being fully utilized, and efficient spectrum use is a growing concern; CR offers a solution to this problem. A CR can intelligently detect whether any portion of the spectrum is in use, and can temporarily use it without interfering with the transmissions of other users. [29] According to Bruce Fette, "Some of the radio's other cognitive abilities include determining its location, sensing spectrum use by neighboring devices, changing frequency, adjusting output power or even altering transmission parameters and characteristics. All of these capabilities, and others yet to be realized, will provide wireless spectrum users with the ability to adapt to real-time spectrum conditions, offering regulators, licenses and the general public flexible, efficient and comprehensive use of the spectrum".
Examples of applications include:
At present, modeling & simulation is the only paradigm which allows the simulation of complex behavior in a given environment's cognitive radio networks. Network simulators like OPNET, NetSim, MATLAB and ns2 can be used to simulate a cognitive radio network. CogNS [36] is an open-source NS2-based simulation framework for cognitive radio networks. Areas of research using network simulators include:
Network Simulator 3 (ns-3) is also a viable option for simulating CR. [39] ns-3 can be also used to emulate and experiment CR networks with the aid from commodity hardware like Atheros WiFi devices. [39]
The success of the unlicensed band in accommodating a range of wireless devices and services has led the FCC to consider opening further bands for unlicensed use. In contrast, the licensed bands are underutilized due to static frequency allocation. Realizing that CR technology has the potential to exploit the inefficiently utilized licensed bands without causing interference to incumbent users, the FCC released a Notice of Proposed Rule Making which would allow unlicensed radios to operate in the TV-broadcast bands. The IEEE 802.22 working group, formed in November 2004, is tasked with defining the air-interface standard for wireless regional area networks (based on CR sensing) for the operation of unlicensed devices in the spectrum allocated to TV service. [40] To comply with later FCC regulations on unlicensed utilization of TV spectrum, the IEEE 802.22 has defined interfaces to the mandatory TV White Space Database in order to avoid interference to incumbent services. [41]
IEEE 802.11 is part of the IEEE 802 set of local area network (LAN) technical standards, and specifies the set of media access control (MAC) and physical layer (PHY) protocols for implementing wireless local area network (WLAN) computer communication. The standard and amendments provide the basis for wireless network products using the Wi-Fi brand and are the world's most widely used wireless computer networking standards. IEEE 802.11 is used in most home and office networks to allow laptops, printers, smartphones, and other devices to communicate with each other and access the Internet without connecting wires. IEEE 802.11 is also a basis for vehicle-based communication networks with IEEE 802.11p.
The ISM radio bands are portions of the radio spectrum reserved internationally for industrial, scientific, and medical (ISM) purposes, excluding applications in telecommunications. Examples of applications for the use of radio frequency (RF) energy in these bands include radio-frequency process heating, microwave ovens, and medical diathermy machines. The powerful emissions of these devices can create electromagnetic interference and disrupt radio communication using the same frequency, so these devices are limited to certain bands of frequencies. In general, communications equipment operating in ISM bands must tolerate any interference generated by ISM applications, and users have no regulatory protection from ISM device operation in these bands.
A wireless network is a computer network that uses wireless data connections between network nodes. Wireless networking allows homes, telecommunications networks and business installations to avoid the costly process of introducing cables into a building, or as a connection between various equipment locations. Admin telecommunications networks are generally implemented and administered using radio communication. This implementation takes place at the physical level (layer) of the OSI model network structure.
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.
Wireless local loop (WLL), is the use of a wireless communications link as the "last mile / first mile" connection for delivering plain old telephone service (POTS) or Internet access to telecommunications customers. Various types of WLL systems and technologies exist.
The S band is a designation by the Institute of Electrical and Electronics Engineers (IEEE) for a part of the microwave band of the electromagnetic spectrum covering frequencies from 2 to 4 gigahertz (GHz). Thus it crosses the conventional boundary between the UHF and SHF bands at 3.0 GHz. The S band is used by airport surveillance radar for air traffic control, weather radar, surface ship radar, and some communications satellites, especially those satellites used by NASA to communicate with the Space Shuttle and the International Space Station. The 10 cm radar short-band ranges roughly from 1.55 to 5.2 GHz. The S band also contains the 2.4–2.483 GHz ISM band, widely used for low power unlicensed microwave devices such as cordless phones, wireless headphones (Bluetooth), wireless networking (WiFi), garage door openers, keyless vehicle locks, baby monitors as well as for medical diathermy machines and microwave ovens. India's regional satellite navigation network (IRNSS) broadcasts on 2.483778 to 2.500278 GHz.
Extremely high frequency (EHF) is the International Telecommunication Union (ITU) designation for the band of radio frequencies in the electromagnetic spectrum from 30 to 300 gigahertz (GHz). It lies between the super high frequency band and the far infrared band, the lower part of which is the terahertz band. Radio waves in this band have wavelengths from ten to one millimetre, so it is also called the millimetre band and radiation in this band is called millimetre waves, sometimes abbreviated MMW or mmWave. Millimetre-length electromagnetic waves were first investigated by Bengali physicist Jagadish Chandra Bose, who generated waves of frequency up to 60 GHz during experiments in 1894–1896.
IEEE 802.22, is a standard for wireless regional area network (WRAN) using white spaces in the television (TV) frequency spectrum. The development of the IEEE 802.22 WRAN standard is aimed at using cognitive radio (CR) techniques to allow sharing of geographically unused spectrum allocated to the television broadcast service, on a non-interfering basis, to bring broadband access to hard-to-reach, low population density areas, typical of rural environments, and is therefore timely and has the potential for a wide applicability worldwide. It is the first worldwide effort to define a standardized air interface based on CR techniques for the opportunistic use of TV bands on a non-interfering basis.
Orthogonal frequency-division multiple access (OFDMA) is a multi-user version of the popular orthogonal frequency-division multiplexing (OFDM) digital modulation scheme. Multiple access is achieved in OFDMA by assigning subsets of subcarriers to individual users. This allows simultaneous low-data-rate transmission from several users.
IEEE 802.11p is an approved amendment to the IEEE 802.11 standard to add wireless access in vehicular environments (WAVE), a vehicular communication system. It defines enhancements to 802.11 required to support intelligent transportation systems (ITS) applications. This includes data exchange between high-speed vehicles and between the vehicles and the roadside infrastructure, so called vehicle-to-everything (V2X) communication, in the licensed ITS band of 5.9 GHz (5.85–5.925 GHz). IEEE 1609 is a higher layer standard based on the IEEE 802.11p. It is also the basis of a European standard for vehicular communication known as ETSI ITS-G5.
High-speed multimedia radio (HSMM) is the implementation of high-speed wireless TCP/IP data networks over amateur radio frequency allocations using commercial off-the-shelf (COTS) hardware such as 802.11 Wi-Fi access points. This is possible because the 802.11 unlicensed frequency bands partially overlap with amateur radio bands and ISM bands in many countries. Only licensed amateur radio operators may legally use amplifiers and high-gain antennas within amateur radio frequencies to increase the power and coverage of an 802.11 signal.
Spectrum management is the process of regulating the use of radio frequencies to promote efficient use and gain a net social benefit. The term radio spectrum typically refers to the full frequency range from 1 Hz to 3000 GHz that may be used for wireless communication. Increasing demand for services such as mobile telephones and many others has required changes in the philosophy of spectrum management. Demand for wireless broadband has soared due to technological innovation, such as 3G and 4G mobile services, and the rapid expansion of wireless internet services.
IEEE 802.11y-2008 is an amendment to the IEEE 802.11-2007 standard that enables data transfer equipment to operate using the 802.11a protocol on a co-primary basis in the 3650 to 3700 MHz band except when near a grandfathered satellite earth station. IEEE 802.11y is only being allowed as a licensed band. It was approved for publication by the IEEE on September 26, 2008.
Cognio, Inc. was an American company that developed and marketed radio frequency (RF) spectrum analysis products that find and solve channel interference problems on wireless networks and in wireless applications. Cognio’s Spectrum Expert product was designed for common frequency bands such as RFID and Wi-Fi. It was sold primarily to network engineers responsible for security for wireless networks or applications that run on wireless networks. Cognio was acquired by Cisco Systems in 2007.
In telecommunications, white spaces refer to radio frequencies allocated to a broadcasting service but not used locally. National and international bodies assign frequencies for specific uses and, in most cases, license the rights to broadcast over these frequencies. This frequency allocation process creates a bandplan which for technical reasons assigns white space between used radio bands or channels to avoid interference. In this case, while the frequencies are unused, they have been specifically assigned for a purpose, such as a guard band. Most commonly however, these white spaces exist naturally between used channels, since assigning nearby transmissions to immediately adjacent channels will cause destructive interference to both.
One of the key challenges of the cognitive radio based wireless networks, such as IEEE 802.22 wireless regional area networks (WRAN), is to address two apparently conflicting requirements: assuring Quality of Services (QoS) satisfaction for services provided by the cognitive radio networks, while providing reliable spectrum sensing for guaranteeing licensed user protection. To perform reliable sensing, in the basic operation mode on a single frequency band one has to allocate Quiet Times, in which no data transmission is permitted. Such periodic interruption of data transmission could impair the QoS of cognitive radio systems.
IEEE 802.11af, also referred to as White-Fi and Super Wi-Fi, is a wireless computer networking standard in the 802.11 family, that allows wireless local area network (WLAN) operation in TV white space spectrum in the VHF and UHF bands between 54 and 790 MHz. The standard was approved in February 2014. Cognitive radio technology is used to transmit on unused portions of TV channel band allocations, with the standard taking measures to limit interference for primary users, such as analog TV, digital TV, and wireless microphones.
Self-interference cancellation (SIC) is a signal processing technique that enables a radio transceiver to simultaneously transmit and receive on a single channel, a pair of partially-overlapping channels, or any pair of channels in the same frequency band. When used to allow simultaneous transmission and reception on the same frequency, sometimes referred to as “in-band full-duplex” or “simultaneous transmit and receive,” SIC effectively doubles spectral efficiency. SIC also enables devices and platforms containing two radios that use the same frequency band to operate both radios simultaneously.
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.
WiFi Sensing uses existing Wi-Fi signals to detect events or changes such as motion, gesture recognition, and biometric measurement. WiFi Sensing is a combination of Wi-Fi and RADAR sensing technology working in tandem to enable usage of the same Wi-Fi transceiver hardware and RF spectrum for both communication and sensing.