Ever since the wireless channel evolved to accommodate data applications, we’ve seen a transition from voice-only communication to wireless multimedia and web type of applications. Given the limitations of natural frequency spectrum, it becomes obvious that current static frequency allocation schemes cannot accommodate these requirements of increasing number of higher data rate devices. As a result, innovative techniques that can offer new ways of exploiting the available spectrum are needed. Cognitive radio arises to be a tempting solution to spectral crowding problem by introducing the opportunistic usage of frequency bands that are not heavily occupied by licensed users.
Multiple measurement campaigns reveal that much of the licensed spectrum remains unused—both in time and in frequency: traffic in wireless networks tends to be bursty. Hence, efficient exploitation of the spectrum requires the ability to exploit instantaneous opportunities at a rather fine time scale.
One of the most important components of cognitive radio concept is the ability to measure, sense, learn, and be aware of the parameters related to the radio channel characteristics, availability of spectrum and power, interference and noise temperature, radio’s operating environment, user requirements and applications, available networks (infrastructures) and nodes, local policies and other operating restrictions. In cognitive radio terminology, primary users can be defined as the users who have higher priority or legacy rights on the usage of a specific part of the spectrum. On the other hand, secondary users, which have lower priority, exploit this spectrum in such a way that they do not cause interference to primary users. Therefore, secondary users need to have cognitive radio capabilities, such as sensing the spectrum reliably to check whether it is being used by a primary user and to change the radio parameters to exploit the unused part of the spectrum. Spectrum sensing by far is the most important task among others for the establishment of cognitive radio. Spectrum sensing includes awareness about the interference temperature and existence of primary users. As an alternative to spectrum sensing, geolocation and database or beacons can be used for determining the current status of the spectrum usage
Although spectrum sensing is traditionally understood as measuring the spectral content, or measuring the interference temperature over the spectrum; when the ultimate cognitive radio is considered, it is a more general term that involves obtaining the spectrum usage characteristics across multiple dimensions such as time, space, frequency, and code. It also involves determining what type of signals are occupying the spectrum (including the modulation, waveform, bandwidth, carrier frequency, etc.).
Spectrum sensing as a critical component of cognitive networking requires therefore that the secondary user (SU) sense the spectrum efficiently, quickly seize opportunities to transmit, and vacate the spectrum should a primary user (PU) reoccupy the spectrum. A critical component of opportunistic spectrum allocation is the design of the spectrum sensor for opportunity detection. It’s suggested that by detecting the presence of primary signals cognitive radio can be aware of spectrum opportunities. However the perfect detection of primary signals does not necessarily lead to perfect detection of spectrum opportunities.
Opportunistic spectrum sensing requires that cognitive radio continuously sense the spectrum it is using in order to detect the re-appearance of the primary user. Once the primary user is detected, the cognitive radio should withdraw from the spectrum instantly so as to minimize the interference it may possibly incur. This is a very difficult task as the various primary users will be employing different modulation schemes, data rates and transmission powers in the presence of variable propagation environments and interference generated by other secondary users. Another great challenge of implementing spectrum sensing is the hidden terminal problem. I have discussed this issue this Article.
Whereas the detection of primary signals is not equivalent to the detection of spectrum opportunities, constitutes a basic step in spectrum opportunity detection. Spectrum sensing is probabilistic in nature and because of this, spectrum sensors essentially perform a binary hypothesis test on whether or not there are primary signals in a particular channel. The channel is idle under the null hypothesis and busy under the alternate. Under the idle scenario, the received signal is essentially the ambient noise in the radio frequency (RF) environment, and under the busy scenario, the received signal would consist of the PU’s (Primary User) signal and the ambient noise. Some well known spectrum sensing techniques include the use of Energy Detection, Matched Filter, Cyclostationary Detection, Wavelet Detection. Below is a table providing the advantages and disadvantages of each method;
Remember that detection of Primary User Signals is not equivalent to detecting spectrum opportunities. But rather is step towards achieving it. So what exactly is spectrum opportunity? Consider the illustration below for this definition.
consider a pair of secondary users (A and B) seeking to communicate in the presence of primary users as shown in the figure above A channel is an opportunity to A and B if the transmission from A does not interfere with nearby primary receivers in the solid circle, and the reception at B is not affected by nearby primary transmitters in the dashed circle. The radius r1 of the solid circle at A depends on the transmission power of A and the maximum allowable interference power perceived by an active primary receiver, whereas the radius RI of the dashed circle depends on the transmission power of primary users and the interference tolerance of B. Spectrum opportunities therefore must be defined jointly at the transmitter and the receiver. It is a function of (1) the transmission powers of both primary and secondary nodes, (2) the geographical locations of these nodes, and (3) the interference constraint. From this definition, we arrive at the following properties of spectrum opportunity. Spectrum opportunity depends on both transmitting and receiving activities of primary users. Spectrum opportunity is, in general, asymmetric: A channel that is an opportunity when A is the transmitter and B the receiver may not be an opportunity when B is the transmitter and A the receiver.
