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Cognitive radio (CR) requirements for 5G, IoT, Space and Military

The information and communication technology industry is today faced with a global challenge: develop new services with improved quality of service (QoS) and at the same time reduce its environmental impact. In addition, the development towards 5G and Beyond (B5G) technologies, the exponential growth in the number of connected objects via the Internet of Things (IoT), Wireless Sensor Network (WSN) devices, and recent wireless applications is widening the gap between wireless supply and demands. The fear of an imminent spectrum crisis is pushing the wireless communication community to enhance the utilization of the limited frequency resources to satisfy the increasing demand for wireless communication services.


Most of the current wireless communication systems are based on the concept of fixed (or static) frequency allocation. They are designed to operate on pre-selected frequency bands. This static allocation results in a low spectrum utilization especially at low traffic periods. According to some estimates,  the usage of some allocated frequency bands is lower than 15%. This means that there are many “holes” in the radio spectrum that could be exploited. An opportunistic radio system should be able to exploit these spectrum holes by detecting them and using them in an opportunistic manner.


In order to address the problem of spectrum usage efficiency, the cognitive radio (CR) concept was proposed.  Cognitive Radio (CR)  is defined as an adaptive, intelligent radio and network technology that automatically detects available channels in a wireless spectrum and changes transmission or reception parameters enabling more communications to run concurrently and without interfering with the licensed users.  This alteration of parameters is based on the active monitoring of several factors in the external and internal radio environment, such as radio frequency spectrum, user behavior, and network state. These capabilities help optimize the use of the available radio frequency (RF) spectrum.


The three key capabilities that differentiate cognitive radio from traditional radio are:

Cognitive capability: A cognitive radio system (CRS) is a radio system that is aware of its operational and geographical environment, established policies, and its internal state.

Reconfigurable capability: It is able to dynamically and autonomously adapt its operational parameters and protocols according to its obtained knowledge in order to achieve predefined objectives ;

learning capability: It is able  to learn from its previous experience 


The software-defined radio (SDR) approach is used to implement the reconfigurations. A software-defined radio (SDR) system is a radio communication system that can tune to any frequency band and receive any modulation across a large frequency spectrum by means of programmable hardware which is controlled by software. Also, the CRS can learn from its decisions to improve its future decisions. The results of learning contribute to both obtaining knowledge and decision making.


The benefits of CR systems would be to:
relieve spectrum scarcity by broadcasting on unused spectrum and avoiding interference with primary licensee
avoid radio jamming and interference based on the selected Spectrum Sensing (SS) approach,
support switch to power saving protocol,
improve communication quality by using higher bandwidth services, and
improve Quality of Service (QoS), since the availability, suitability and reliability will be enhanced


CR technology

CR has been introduced as a potential candidate to perform complete Dynamic Spectrum Allocation (DSA) by exploiting the free frequency bands that are also called “spectrum holes” or “white spaces”. Being capable to identify these spectral opportunities, CR classifies the users into two categories: licensed, i.e., the Primary Users (PUs), and unlicensed, i.e., the Secondary Users (SUs). While PUs can access the spectrum whenever they want, SUs are restricted by the activities of PUs.


In other words, SUs should respect the PUs’ Quality of Service and harmful interference coming from SUs to PUs transmission is prohibited. Therefore, three paradigms of CR can be distinguished according to the possibility of co-existence of SU and PU transmissions in the same channel, the permitted transmit power of SU and the cooperation between SU and PU.

Three main paradigms of CR can be distinguished:
1. Underlay Access: the SU may transmit simultaneously with the PU over the same channel. However, the transmitted power should not exceed a certain threshold in order to keep the interference on PU below a tolerable value. The main drawback of the underlay paradigm is the low transmitted power, which adversely impacts the throughput.
2. Overlay Access: the SU may transmit simultaneously with the PU on the same channel up to its maximum power, but at the cost of playing a role of relay between two or more PUs. In this case, the SU sends its data while relaying the PUs. This kind of access requires a high level of cooperation between PUs and SUs, which may expose the PUs privacy.
3. Interweave Access: SU is allowed to transmit using its maximum power only when PU is absent. This paradigm is also known as the classical CR. Interweave paradigm allows SUs to transmit with their maximum power, but at the cost of monitoring the activity of PU.

Spectrum Sensing in Cognitive Radio: Components and Methodologies

The CR works through a cognition cycle with four functional phases which are sensing, decision, sharing, and mobility. The cognition cycle begins with Spectrum sensing (SS) phase through which the available spectrum resources are detected over the selected spectrum band using different SS approaches. Spectrum sensing may be cooperative or non-cooperative. In the cooperative method, cognitive radio devices share spectrum information, while in the non-cooperative method, each CR device acts on its own. Based on the detection results, the decision is made to concurrently share the band, or to cease transmission in that band. Once a CR decides to exploit the band, a proper Medium Access Control (MAC) protocol is employed and power allocation should be considered to satisfy the PU protection. Finally, switching from band to another is performed through the mobility phase.
Block diagram of cognitive radio | Download Scientific Diagram
Main part of the CR is its Cognitive Engine (CE), also known as the ‘brain’ of it. It is that part of the CR which has its own intelligence and can take its own decision based on different parameters and situations. Another important part of the design is that Radio Environment Map (REM) which is the central database of the CR. It keeps different types of information in its records. In the receiver and transmitter different sensor nodes are placed to sense the surrounding environment. These sensor nodes sense and store the information into the REM. From the current data and past stored information CR can reconfigure itself. Data in the REM database also updated in different times based on the information available through the sensors.
CR can be implemented completely on the reconfigurable hardware. Implementation consists of two different parts:
Hardware implementation and Software implementation. Among the configurable hardwares available in the market for
commercial use ASIC and FPGA are widely used.
Though it can be implemented on ASIC successfully but the limitation of such implementation is that such architecture
is not flexible because ASIC is a onetime programmable chip. FPGA provides a better solution to this problem. It is flexible enough and can be programmed multiple times. Functionality of the modules as well as of the architecture can be changed even after implementation on the FPGA platform. Using different instructions the same FPGA can be tuned to different applications. Moreover, some FPGA supports partial reconfiguration. Therefore, CR can be implemented on FPGA at running time and its functionality can be changed at a later stage depending on the requirements. Parameters which control the functionality of the components can also be changed at a later stage. It adds flexibility to the implementation technique.
An excellent method for implementation of cognitive radio nodes was proposed by J. Lotze et. all. According to the conceptual framework proposed by them, a practical implementation can be divided into following three
different parts:
I) A virtual architecture: Framework for implementation is designed without considering the underlying implementation details. The architecture thus designed can be mapped directly to the FPGA board. It consists of two different parts: the Processor Subsystem (PS) and the Customizable Processing Subsystem (CPS). Duty of the PS is to execute the software instructions whereas the duty of the CPS is to implement them on the FPGA board. The objective of the CPS is to implement it as a partially reconfigurable area. This area can be reprogrammed without hampering the normal activity of the other parts. CPS is used for radio configuration.
II) An adaptive runtime system: Supports the econfiguration process and manages all the processes during run time reconfiguration. An XML file will maintain the flow of data, components and other parts required and other details
information. System execution is managed by this run time system. According to J. Lotze et. all the architecture for
implementation is divided into two different parts: processing and control plane. The processing plane performs all the
computations required. The control plane is the part which is used to manage the system.
III) High level design tools: Tools that helps such designers of the cognitive radio network who don’t have knowledge about FPGA implementation. It helps system-level design and selection of hardware components where the design will be implemented. Two parts of the design is to design the processing chain and the cognitive process. Processing chains are typically described as flow graph.
Another aspect of this design is to select which components will be selected for mapping. For this purpose a control
specification may be used. In this design, a Composer tool uses the control specification. It will generate the FPGA
bitstreams which will be used by the runtime system for reconfiguration.
CR benefits from the emergence and development of learning techniques applied to wireless communication. As a powerful tool, machine learning techniques are exploited in the domain of CR to improve SS performance. SS may be formulated as a binary classification problem related to the presence of PU. Unlike classical SS, the learning techniques may overcome the need to know statistical parameters of the channel or the PU signal. Moreover, these techniques are proposed to predict the PU activity, which can enhance the spectral efficiency of the secondary network and protect the primary transmission from secondary interference.

CR Applications

CR is proposed to be used in various wireless communication technologies, since it proves itself as one of the efficient techniques to ensure fair and flexible frequency allocation

CR for the fifth Generation (5G) is expected to play an important role to answer the need of the increasing number of data hungry devices. Knowing that 5G will extend the spectrum band to the millimeter-wave range, CR can be used to improve the spectrum utilization while providing better protection to co-existing users. Moreover, CR can be used to address interference issues from space, frequency and time domain. This is important knowing that 5G is expected to exploit spatial reuse of the spectrum as one of the main features of 5G systems. Yet, introducing CR in 5G imposes several challenges that need addressing.

The usage of CR is extended to the domains of IoT and WSN. This was motivated by the huge number of new IoT/WSN devices that require additional frequency resources.

In order to enable pervasive network connectivity, Integrated Satellite-Terrestrial Communication Networks (ISTCN)
has emerged as an important research area. ISTCN aims to provide high-speed and pervasive network services by
integrating broadband terrestrial mobile networks with satellite communication networks.

As terrestrial mobile network began to use higher frequency spectrum which overlaps with that of satellite communications (e.g. 4GHz to 8GHz for C band and 26GHz to 40GHz for Ka band), there are vast opportunities as well as difficult challenges. On one hand, satellite terminals can potentially access terrestrial network in an integrated manner; on the other hand, there will be more congestion and interference in this spectrum, hence more efficient spectrum management techniques are required.
CR, based on software radio, allows the system to adaptively adjust transmit parameters by sensing the current communication environment, so as to achieve efficient spectrum resource utilization. It can share the spectrum resources
among the heterogeneous communication systems through spectrum sensing and dynamic reconfiguration capability. As
a secondary user (SU), the CR system can opportunistically utilize the idle spectrum of primary user (PU) or share the
spectrum with the PU at a lower power. Satelliteterrestrial CR spectrum sharing makes the satellite system and
terrestrial system utilize the same spectrum resources, which can alleviate satellite spectrum tension effectively.


Military Applications

Military wireless networks need to be immune to deliberate interference and to remain operational even in the case of systematic destruction of telecommunication infrastructure. Since one of the main challenges at the tactical level is the high maneuverability of troops, specific technical answers are required. A promising solution to the problem is MANET (mobile ad-hoc network). The main advantage of MANET is their ability to self-organize in the environment where users frequently and unpredictably change their location. Moreover, in MANET, all radios play the role of user terminals and relay nodes.


The problem of efficient frequency management in common operations has been noticed by NATO Science and Technology Organization. As a consequence, the information systems technology (IST) panel has established an exploratory team and then a research task group (RTG) whose tasks include, inter alia, checking potential benefits resulting from the implementation of the radio environment map (REM) concept.


The aim of the IST-146 RTG-069 group is to work out a concept of REM enabling their users to obtain the spectrum operational picture and to minimize the level of interferences between wireless systems of coalition forces. One of the main goals of the research group is to define the architecture of the system and to specify interfaces to other systems in the area of frequency management.


In general, REM is considered to be a database which stores comprehensive and up-to-date information on the radio spectrum. It is assumed that this information is composed of geographical features, available services, spectral regulations, positions and activities of radios, and policies adopted by the user and/or service providers, as well as knowledge from the past




REM architecture comprises the following modules: REM Manager, REM storage and data collection, REM Acquisition, sensors, and GUI. REM Manager processes the data and controls the REM database in terms of measurement configuration, e.g., monitoring subranges, measurement mode (continuous or on request), and active sensors. REM storage and collection module is an interface between the database, REM acquisition modules, and REM Manager. REM acquisition modules are interfaces to various systems of sensors.


Sensors are generally named MCDs (measurement capable devices). MCDs are controlled through REM Acquisition modules and they monitor spectrum. In civilian applications, the function of MCDs can be performed by various devices with measurement capability, such as simple mobile phones, smart phones, and notebooks.


When military systems are considered, spectrum measurements can be taken by dedicated receivers, cognitive radios, electronic warfare (EW) systems, or intelligence, surveillance, reconnaissance (ISR) systems. It is worth noting that sensors are strictly connected to specific military platforms, e.g., trucks. As a consequence, the position of the sensor results from the operational needs for the platform and thus cannot be changed freely, e.g., to get better distribution of sensors. For this reason the possibility of deployment of sensors in tactical environment may be seriously reduced.



Cognitive Radio Market

The cognitive Radio Market size was valued at USD 5.66 Billion in 2020 and is projected to reach USD 19.13 Billion by 2028, growing at a CAGR of 16.4% from 2021 to 2028.


Owing to the increasing demand for the 5th generation wireless technology, excellent optimization of the radio frequency spectrum, and advancement in the technologies such as configuring cognitive radios with artificial intelligence (AI) and others lead to drive the growth of the market.


Cognitive Radio is the smart radio which is configured to use the wireless spectrum in the surroundings to avoid the user’s interference and allows communication concurrently with better-operating parameters. The important function of the cognitive radios is to search for the vacant spectrum, detecting an unutilized spectrum and sharing it without causing interference to another user. Cognitive radio uses several technologies such as Software Design Radio (SDR), adaptive radio (AD) to enhance efficiency.


In addition, the widely rising adoption of cognitive radio in space communication aid to boost the market. However, some of the factors such as security issues effects related to interoperability may affect the performance of radios while incorporating with wireless communication system Huge power consumption and poor tolerance capability might also restrict the growth of the market


Market Segments

On the basis of types, the market is segmented into Government and Defense, Telecommunication, Transportation

Government and Defense

Government and Defense is an application of cognitive radio that uses spectrum sensing, analysis, and allocation for defense purposes such as military communication. The increasing adoption of cognitive radio technology in government and defense applications such as military, aerospace, and security will drive this market. Cognitive radio technology will be used for military purposes such as command and control systems, battlefield situational awareness systems, weapons platforms & equipment, etc.



Telecommunication is an application of cognitive radio that uses spectrum sensing, analysis, and allocation for communication purposes such as mobile phones. The increasing demand for smart devices has created opportunities in the telecommunication sector which will drive this market. The development of new technologies by cellular
network operators to provide higher data rates with reduced latency on their networks is expected to increase the adoption of cognitive radio technology in telecommunication applications across various countries.



Transportation is an application of cognitive radio that uses spectrum sensing, analysis, and allocation for transportation purposes such as AM/FM radios in vehicles. The increasing need to improve the safety and security of people by improving communication with real-time information is expected to drive this market. For instance, in July
2016, Inmarsat launched a satellite for high-speed broadband connectivity to connected cars.

On basis of application, the market is segmented into Spectrum Sensing, Spectrum Analysis, Spectrum Allocation, Location Tracking, and Cognitive Routing.

Spectrum Sensing: Spectrum sensing is an important cognitive radio technology that can detect whether some part of the spectrum is free for use or not. Cognitive radios are equipped with advanced algorithms to analyze vast chunks of data in real-time which helps them identify usable frequency bands and avoid interference from other devices using the same frequencies, resulting in improved spectral efficiency & utilization. It also reduces network congestion by avoiding interference between neighboring cells on a wireless.


Spectrum analysis: Cognitive Radio is a type of wireless device which acts as both the transmitter and receiver. It uses software to replace hardware in conventional radios that are used for broadcasting, receiving, or switching between different radio systems. Cognitive Radio is able to sense the available spectrum around itself and then accordingly tune its transmission parameters like frequency etc., Thereby efficiently utilizing all available frequencies and preventing other devices from using it. This technology provides an efficient way of sharing unused Spectrum among different users/devices where each user can use this shared resource whenever required without interfering with others’
usage simultaneously.

Spectrum Allocation: Cognitive radio can be utilized to differentiate between primary and secondary users by spectrum allocation. Primary users have the sole privilege of using a certain band of frequency; secondary users are not permitted to take that section of the RF spectrum without permission from an authorized person or authority. When primary users utilize their assigned portion of the spectrum, they must adhere to specific regulations in order for secondary users to have equal access to these bands at all times possible with minimal interference.



On basis of region, the market is segmented into North America, Europe, Asia-Pacific, and the Rest of the World. In 2017 North America is the largest market for Cognitive. Radio owing to increased demand from the government and defense sector coupled with a high adoption rate in the telecommunication industry. Furthermore, factors such as the early deployment of new technology by players along with increase funding from federal agencies are driving growth rates positively.

Europe is the second-largest market for cognitive radio which is expected to grow at a rapid pace due to increasing demand from the government and defense sector. AsiaPacific region also have huge potential owing to the rapidly growing telecommunication industry. Asia-Pacific and the Rest of the World region are expected to grow at a high CAGR owing to demand from the Transportation industry and the increasing number of players entering this market


The U.S. Market is Estimated at $1.6 Billion in 2021, While China is Forecast to Reach $2 Billion by 2026
The Cognitive Radio market in the U.S. is estimated at US$1.6 Billion in the year 2021. China, the world`s second largest economy, is forecast to reach a projected market size of US$2 Billion by the year 2026 trailing a CAGR of 15.6% over the analysis period. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 14.1% and 14% respectively over the analysis period. Within EuropeGermany is forecast to grow at approximately 11.9% CAGR.


Services Segment to Reach US$5.5 Billion by the year 2026
In the global Services segment, USACanadaJapanChina and Europe will drive the 18.7% CAGR estimated for this segment. These regional markets accounting for a combined market size of US$1.4 Billion in the year 2020 will reach a projected size of US$4.5 Billion by the close of the analysis period. China will remain among the fastest growing in this cluster of regional markets. Led by countries such as AustraliaIndia, and South Korea, the market in Asia-Pacific is forecast to reach US$1.2 Billion by the year 2026


Some of the major players such as Raytheon Company, Rhode & Schwarz GmbH& Co KG, Thales Group, BAE Systems, Spectrum Signal Processing, Ettus Research, EpiSys Science, xG Technology, Shared Spectrum Company, and Nutaq.



References and Resources also include:






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