AN OVERVIEW OF COGNITIVE RADIO NETWORKS 1

Radio spectrum needed for applications, such as mobile telephony, digital video broadcasting (DVB), wireless local area networks (WiFi), wireless sensor networks (ZigBee), and Internet of things, is enormous and continues to grow (1,2,3). This exponential growth is set to continue (4). For example, by 2019, the monthly mobile data traffic will exceed 24.3 exabytes, mobile devices per capita will be 1.5 and the average speed of a wireless connection will increase to 4 Mbps, over 59% of mobile connections will be from smartphones, and mobile-to-mobile connections will be the majority (4). Therefore, the demand for wireless connectivity, coverage, capacity, and services will continually expand. However, a critical bottleneck is the radio spectrum, a finite resource that cannot be readily expanded. For example, although theoretically ranging from 3 Hz to 3000 GHz, the entire spectrum is not usable; thus, the prime spectrum for current wireless standards may be roughly 1–5 GHz. This is because the spectrumbelow 1GHzhas already been reserved for applications such as radar, military communications, and terrestrial radio/television, while the spectrum above 5 GHz suffers from increased attenuation and atmospheric absorption. Therefore, the limited spectrum presents a roadblock for the rapid growth of wireless networks and users. Now given this real, physical spectrum constraint, an obvious question is how efficient is the current use of spectrum? Quantitatively, spectral efficiency is measured in bits per second per Hertz (bps/Hz), which is the data rate that can be sent over a unit bandwidth. While this efficiency has steadily increased due to technical improvements, such as the use of higher order modulation and adaptive techniques (5,6), the rate of growth has decreased recently (7). Due to this saturation, improving spectral efficiency by other means is essential for the growth of wireless networks. How do we improve the spectral efficiency of wireless networks as a whole? Before answering this question, we must look at the inefficiencies of current spectrum usage. First of all, spectrum is assigned in a fixed manner by national regulatory bodies, and their main principle is to avoid radio interference, which is achieved by dividing spectrum into bands (e.g., frequency division) that are allocated to one or more services. These radio services include mobile, satellite, amateur radio, navigation, and others (e.g., Table 1). A license gives an exclusive right to operate (transmit and receive wireless signals) in a specific frequency band, in a specific location or geographic area. But much of the licensed spectrum remains unused in practice at different times and/or locations. Those temporary spectrum slots (aka spectrumholes or white spaces) (8,9) can be as high as 15–85 % of the licensed spectrum (10). Clearly, to improve the overall spectral efficiency, unlicensed users can be allowed to access such spectrum holes. Thus, this fact suggests the need for opportunistic spectrum access without causing undue interference to licensed users (11,12). Such capability is the defining characteristic of cognitive radio (CR) nodes, which require algorithms and protocols for rapid spectrum sensing, coordination, and cooperation. In other words, CR nodes can recognize unused parts of spectrum and adapt their communications to utilize them while minimizing the interference on licensed users. Consequently, CR improves the overall spectrum usage, by moving away from static assignments into more dynamic forms of spectrum access. Thus, to enable access to idle or underutilized spectrum, CR networks have already been standardized in IEEE 802.22 WRAN (Wireless Regional Area Network) and its amendments, IEEE 802.11af for wireless LANs, IEEE 1900.x series, and has also been a motivating factor for licensed shared access (LSA) for LTE mobile operators (13). Furthermore, test beds have been built to verify the feasibility of CR within LTE systems (14). In the context of CR, licensed spectrum users are called primary users (PUs) and unlicensed users are called secondary users (SUs) or CR nodes (both terms will be used interchangeably henceforth.) Thus, SUs must opportunistically access spectrum holes, while keeping the interference on the PU receivers at either zero or below a prescribed level. The coexistence of a group of secondary CR networks and a primary network is shown in Figure 1. CR networks can be divided into the following three paradigms (Figure 2) (15,16,17,18,19,20):