Adaptation from Transmission Security (transec) to Cognitive Radio Communication

Communication systems have to be made secure against unauthorized interception or against disruption or corruption in complicated electromagnetic environments. There are mainly three security categories used to delineate wireless communication systems generally, such as shown in Fig. 1, i.e., INFOSEC, COMSEC, and TRANSEC. We state about information security (INFOSEC) as that trying to against unauthorized access to or modification of information; we describe the communications security (COMSEC) as that keeping important communications secure. And we describe transmission security (TRANSEC) as that making it difficult for someone to intercept or interfere with communications without prior accurate waveforms, modulation schemes, and coding (Nicholson, 1987).


Introduction
Communication systems have to be made secure against unauthorized interception or against disruption or corruption in complicated electromagnetic environments. There are mainly three security categories used to delineate wireless communication systems generally, such as shown in Fig. 1, i.e., INFOSEC, COMSEC, and TRANSEC. We state about information security (INFOSEC) as that trying to against unauthorized access to or modification of information; we describe the communications security (COMSEC) as that keeping important communications secure. And we describe transmission security (TRANSEC) as that making it difficult for someone to intercept or interfere with communications without prior accurate waveforms, modulation schemes, and coding (Nicholson, 1987).

Fig. 1. Wireless communication security delineation
Therefore, in general, the basic strategies for acquiring and paralyzing the communication victim for the untended or intended users are to detect, intercept, exploit, and jam the communication signals. Relatively, the basic measures to counter these strategies for the victim are to design system with TRANSEC capabilities, i.e., low probability of detection, interception, and exploitation (LPD/I/E), and with receiving security capability, i.e., AJ or jam-resistant. LPD/I/E can be defined as measures with hidden signals which make it In Section 2, a systematic approach for evaluating the interactions of the link geometry and TRANSEC system parameters (AJ and LPD are assumed) for secure communication is proposed. In many typical cases, communication designs have to deal simultaneously with adversary threats of both active jamming and passive detection to protect against jamming and detection. And by increasing communication power to counter jammer and enhancing anti-jamming capability must be weighted carefully against the increased threats of deteriorating low probability of detection capability and being detected by an unintended interceptor receiver. A qualitative and quantitative approach with sinc-type antenna patterns being included for evaluating both AJ and LPD concurrently is reached. And it is intuitive to see that by spreading signal spectrum, complicating signal waveforms, and lowering power control uncertainty, respectively, will enhance system security and performance accordingly.
In Section 3, a cognitive radio unit (CRU) model with uniform scanning (U-scanning) and sequential scanning (S-scanning) techniques and cognitive perception ratio (CPR) metric for cognitive communications adapted from TRANSEC is investigated. In this model realtime spectrum sensing characteristics are coordinated together with system parameters in temporal and frequency domains, e.g., scanning rate and framing processing time, for evaluating the performance of the cognitive radio (CR) communications under an elliptical or a hyperbolic operation scenario. CR technology has been proved to be a tempting solution to promote spectrum efficiency and relieve spectrum scarcity problems. Nevertheless, the cognitive capability cannot only be realized by monitoring on some frequency bands of interest but also more innovative techniques are required to capture the spectrum holes with temporal, frequency or spatial variations in sophisticated Frequency hopping spread spectrum (FHSS) radio environments, and avoid interference to the existing primary users. Nowadays, the FHSS systems have been widely used in civil and military communications, but somewhat their benefits would be potentially neutralized by a follow-on jamming (FOJ) with wideband scanning and responsive jamming capabilities covering the hopping period. The FOJ concept is actually implicitly analogous to a CR communication with spectrum and location awareness, listen-then-act, and adaptation characteristics. High CPR value means high spectrum awareness but low coexistence. Many intriguing numerical results are also illustrated to examine their interrelationships.
In Section 4, a systematic approach with their corresponding metrics for evaluating independent and concurrent AJ and LPD performance qualitatively and quantitatively is drawn in this section. Moreover, specific scanning schemes and a quantified CPR metric are available for evaluations of the coexistence of radio resources. Section 5 is literatures listing.

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Advances in Cognitive Radio Systems 84

Secure communications system through concurrent TRANSEC evaluations
The central concept for a secure communications system is to protect against unintended or intended jammers and interceptors, force them to change system parameters or work outside of the prescribed acceptable regions, and maintain secure system performance simultaneously. In this section, a systematic approach for evaluating the interactions of the link geometry and TRANSEC system parameters for secure communication will be investigated.

Survey of related works
There are many inspiring methods and metrics which have already been explored and proposed by many forerunners for secure communication related performance concerns, which are addressed as follows. Turner described the reasons of LPD/LPI/LPE communications developments and anti-jamming verse LPD/LPI/LPE communications requirements, which offer capabilities not available with AJ communications. The ideal characteristics of a LPD/LPI/LPE communications waveform and methods for detecting LPD/LPI/LPE transmissions are listed to form the basis for discussing of their developments and capabilities (Turner, 1991). Glenn made a LPI analysis and showed the effect of scenario-dependent parameters and detectability-threshold factors in jamming and non-jamming environments, and concluded that the most significant improvement in LPI performance can be obtained by operating at Extremely High Frequency (EHF) and by maximizing the effective spread-spectrum processing gain and the communicator's antenna discrimination to the jamming signal, and by minimizing the number of symbols in the message (Glenn, 1983). Based on power gains and losses, Gutman and Prescott have given a LPI system quality factor (Q LPI ) to a grouping of quality factor terms consisting of the antennas (Q ANT ), type of modulation (Q MOD ), atmospheric propagation conditions (Q ATM ), and interference rejection capability (Q ADA ) in the presence of jammers and intercept receivers (Gutman & Prescott, 1989). Based on gain difference between the communication receiver and the radiometer, Dillards developed a detectability gain (DG) metric for defining "acceptable" LPD performance of a communication signal by a radiometer, which includes their path losses, antenna gains, etc., plus two "mismatch" losses incurred by the radiometers (Dillard & Dillard, 2001). Using classical radiometer analysis and communication theory, Weeks et. al. developed a methodology through detectability distance to quantify the LPD characteristics of some COTS wireless communication systems, i.e., GSM, IS-54, IS-95, and WCDMA, which is obtained by exploiting the step-like function behavior of the probability of detection curve for a given system. Tradeoffs between the observation time of the interceptor and the detectability distance with multiple users are also investigated (Weeks et al, 1998). Mills and Prescott presented a scenario-independent stand-off intercept model for situations in which the collocated network transmitters and the relatively distant interceptor are assumed. Under these assumptions, the detectability performance of the network using a frequency hopping multiple access scheme (FHMA) can be evaluated for the wideband and channelized radiometers and LPI quality factors can be used to compare the performance of them (Mills & Prescott, 1995). Furthermore, Mills and Prescott also established two multiple access LPI network detectability models, i.e., scenarioindependent standoff network and scenario-dependent dispersed network models, and developed their corresponding LPI performance metrics to provide new insight into these www.intechopen.com issues (Mills & Prescott, 2000). Benia explored the effect of message length, processing gain, and coding gain on LPI performance and suggested a method for analyzing the effects of channel absorption loss models on the LPI quality factor (Binia, 2004). Wu investigated the impacts of the filter-bank interceptor performance and the emitter with FH waveform and specific antenna pattern on so-called circular equivalent vulnerable radius (CEVR) sensitivity within a statistical context like confidence interval (Wu, 2005).On the other hand, many forerunners have already investigated optimal interceptors for best detection probability concerns as well, which are addressed as follows. Schoolcraft defined six conventional and LPD waveforms to resist against seven detection techniques and provided a general approach to test the effectiveness of postulated threats against candidate waveforms and the relative LPD strengths of competing candidate waveforms (Schoolcraft, 1991). Wu studied the optimal interceptor for a FH-DPSK waveform, derived the detection algorithm based on the maximum likelihood principle, and proposed a novel performance evaluation approach (Wu, 2006). In spite of focusing on geometrical or power aspects of jamming only before, Burder analyzed and derived a mathematical intercept model for computation of the jamming probability when a follower jammer with a wideband-scanning receiver jams a single FH system (Burda, 2004). Gross and Chen developed and predicted the relative detection range for two types of transmitted waveforms, i.e., a benchmark rectangular pulse and a Welti binary coded waveform, and some classic passive receivers, e.g., square-law, delay and multiply, wideband, and channelized receivers possessing typical bandwidth, noise-floor, and loss parameters (Gross & Chen, 2005). In spite of the active jamming measures taken, FOJ is implicitly analogous to a cognitive radio communication with spectrum and location awareness, listen-then-act, and adaptation characteristics. For transmission security concerns, concurrent anti-jamming and low probability detection were investigated to have a secure communication (Liao et al., 2007).

System analysis scenario
The operation scenario with both AJ and LPD for a Ka-band GEO satellite communication system will be taken as system analysis model in this subsection. The relative geometry locations of the victim satellite communication system and the adversary multiple jammers and interceptors are shown in Fig. 3, where the victim communication terminal is put at the origin, and the latter two are collocated on the same fixed or varying positions, i.e., (x 1 , y 1 , 0), (x 2 , y 2 , 0), (x, y, 0), and (x N , y N , 0) etc. The paired jammer and interceptor on the same position (x, y, 0) are varying in an approaching or receding way for evaluating AJ and LPD performance. R c is the range between our communication system themselves (e.g., R c is assumed to be 36000kM for a geosynchronous elliptic orbit (GEO) satellite). R j /R i is the jammer/interceptor range from their collocated earth position to the victim communicator on the position of (0, 0, R). As shown in this figure, one very important factor for the effectiveness of jamming or interception is the relative angle φ off the main beam pattern of the victim communicator (on the position of (0, 0, R)) in the direction of earth jammer/interceptor. Generally, our friendly communication system (communicators at the origin and on the position (0, 0, R)) will direct main beam patterns at each other to get maximum gain patterns, and the intentional jammers or unintended interceptors will only be able to cover from the sidelobe direction, especially when the operating frequency is higher. Fig. 3 shows a basic scenario with an intercepted and jammed satellite and multiple jammers and interceptors on the ground. Whenever the jamming and interception range is very far away from the victims, e.g., a GEO satellite, the interceptor and jammer will also get the advantage of the main beam gain of the victim communicator on the position (0, 0, R) relatively easier, if no antenna shaping or nulling pattern designs are taken.

Fig. 3. The operation scenario with both AJ and LPD for a Ka-band GEO satellite communication system
Jammer/interceptor will get the advantages of the victim antenna pattern (mainlobe) to enhance their jamming or interception effects if the relative angles of the jammer/interceptor and the victim communicator on the position (0, 0, R) are tilted with the line of sight of the victim communicators themselves. The well-known parabolic antenna power gain G o (D) and pattern G(φ) are given as follows (Jain, 1990) where D is antenna diameter, λ is wavelength, η is antenna efficiency, and J 1 is first order Bessel function. If the satellite communicator on the position of (0, 0, R) is assumed to be the victim with a 3m sinc-type antenna, a narrower 30GHz and a wider 20GHz antenna patterns will be for uplink and downlink communication for the terminals on the ground, respectively. It is therefore good for anti-jamming design (30GHz) but not for LPD (20GHz) due to its wider transmission pattern.

Evaluation method
Not only are the power control schemes of a communication system very crucial to provide adaptive adjustments of transmission power and signal-to-noise ratios required, but are also the communication signal very dangerous to be more easily detected by the unintended or intended interceptors, especially, whenever the power sources are transmitted unscrupulously. In general, the receiving and transmission security achieved by a communication link depends very strongly on its system related parameters and location relative to an adversary's jamming transmitter and intercept receiver, which can be categorized as system-dependent and geometry-dependent factors, respectively, for independent or concurrent AJ and LPD security concerns. The jamming to signal ratio (J/S) and the intercept signal to noise ratio ((S/N) i ) can be categorized, respectively, as systemdependent factors, i.e., f(•) and g(•) and geometry-dependent factors, i.e., R js (•) and R si (•), respectively. In coordination with the system operation scenario as shown in Fig. 3, the signal bit energy to jamming density (E b /J o ), where J o is very large compared to noise power density N o , can be categorized as system-dependent factor h(•) and geometry-dependent factors R ej (•), respectively. Furthermore, E b /J o can be proportionally or inversely related to these four system related parameters, i.e., processing gain (G P ), effective jamming power for the adversary jammer (ΔM j ), effective intercepting sensitivity for the adversary interceptor (ΔM i ), and effective power control for the victim communication system (ΔM t ). For example, whenever any of the latter three parameters is increased, E b /J o is lowered, i.e., error probability is increased. In contrast, whenever any of these three parameters is decreased, error probability is decreased.

Concurrent AJ and LPD communications (E b /J o )
In this subsection, in order to consider the AJ and LPD applications concurrently, we assume that the jamming power spectral density J o is very large compared to noise power density N o . Binary frequency shift keying (BFSK) is a kind of digital modulation method with two frequencies representing 0 and 1. Frequency hopping multiple access (FHMA) is a kind of spread spectrum schemes with many orthogonal or pseudo-orthogonal frequency patterns for multiple users application. The error probability for BFSK and FHMA combination, P fh , is given by (Sklar, 2001) where E b (=S/R b ) and J o are, respectively, the bit energy and jamming power density given as follows for the n th paired jammer/interceptor By substituting equation (3) and (4) into equation (2) and taking an inverse natural logarithm of it, the required E b /J o for the n th paired jammer/interceptor is given as follows where (S/N) io means the optimum intercepting signal-to-noise ratio of an interceptor receiver; N oi represents the output thermal noise power density of interceptor receiver, which is equal to kT 0 N fi,n , where k, T 0 and N fi,n are Boltzmann's constant (1.38×10 -23 W/Hz/˚K), absolute temperature (290˚K assumed), and interceptor receiver noise figures, respectively. Equation (5) can also be categorized as system-dependent parameter h(•) and geometry-dependent parameters R ej (•) as shown in equation (6). The E b /J o can be further manipulated and given as follows where G p is the spreading spectrum processing gain given by W ss /W bb and (S/N) t is be given as follows From equation (7), J/S is inversely related to (S/N) i with the other parameters fixed, which can be further manipulated and simplified as given by where ΔM j , ΔM i , and ΔM t are defined as J/S, (S/N) i /(S/N) io , and (S/N) t /(S/N) to , respectively. They mean the ratios of effective jamming power for the adversary jammer, effective intercepting sensitivity for the adversary interceptor, and effective power control for the victim communicator. E b /J o is inversely related to these three parameters if G p is fixed. For example, whenever any of these three parameters is increased, E b /J o is lowered, i.e., error probability is increased. On the contrary, whenever any of these three parameters is decreased, error probability is decreased. From equation (9), it is intuitive for the victim communicator side to enhance system performance (lowering error probability) by spreading signal spectrum (G p is increased), increasing signal power (ΔM j is decreased), complicating signal waveforms (ΔM i is decreased), and (or) lowering power control uncertainty (ΔM t is decreased), respectively. For the adversary side, in order to deteriorate the performance of this secure victim communication system, ΔM j , ΔM i , and ΔM t should be increased to lower E b /J o accordingly. In fact, the proposed concurrent AJ and LPD research can contribute to the CR communications for practical implementation by replacing all the collocated jammers/interceptors as shown in Fig. 3 with "cooperative" communicators, in which some geometry-and system-dependent factors can be sensed and aware of for spectrum resources adjustments or accesses, e.g., ΔM j , ΔM i , ΔM t , relative positioning locations, and their corresponding parameters like power, bandwidth, spectrum hole, and etc.

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Adaptation from Transmission Security (TRANSEC) to Cognitive Radio Communication 89

E b /J o numerical analysis
In this section, one typical Ka-band (f up /f dn =30/20GHz) GEO satellite communication (SATCOM) example (R c is assumed to be 36000kM) is illustrated through the proposed design approach for a secure communication system with concurrent requirements of both AJ and LPD capabilities. As shown in Fig. 3, the 7-m size jammer and interceptor antennas with maximum sinc type antenna pattern gains of G js and G is , respectively, are assumed in simulations. The antenna sizes for the communicators at the origin and on the position (0, 0, R) are both 3-m, and they are pointed each other with maximum gains. The sidelobe patterns leaked from the victim communicator on the position (0, 0, R) (i.e., GEO satellite) to the collocated interceptor and jammer on the ground are tilted φ angle dependent on relative positions among them, i.e., G si (φ) and G sj (φ). Based on equation (8) and (9)  combinations are shown: 1 VJI(red solid-), 1 VJI + 1 FJI @R t =450km(blue dot·····), 1 VJI + 1 FJI @R t =300km(blue dash----), 1 VJI + 1 FJI @R t =200km(blue dash dot-·-·-), 1 VJI + 5 FJI @R t =200km(thick blue dot·····), and 1 VJI + 1 FJI @R t =100km(thick blue dash----). The concurrent AJ and LPD performance under these single or multiple jammers/interceptors operation scenario can be examined if a minimum 10 -4 FH error probability (P fh ) is asked to maintain (E b /J o =12.3dB). It is clear that whenever one single paired jammer/interceptor is beyond the range (R t ≈139kM), the communication performance criterion will be met (P fh <10 -exist even more "smoothed" effects for E b /J o curves when in comparison with J/S and (S/N) i curves as aforementioned, which maybe are due to randomized sidelobe patterns effects. Fig. 5 shows the respective intuitive E b /J o contour plot with one varying jammer/ interceptor and one collocated fixed jammer/interceptor (1FJI) at R t =200km. The prescribed E b /J o =12.3dB circle (radius is about 139km) within which P fh >10 -4 is also shown for concurrent AJ and LPD performance evaluations criterion. Therefore, a specific strategy could be taken to expel the approached varying jammer/interceptor beyond this zone. A much more smoothed E b /J o contour outside the prescribed criterion circle is observed, which means a less secure communication performance even only one more fixed jammer/interceptor at distant range is considered. According to equation (9), four main system-dependent factors can be as metrics for tradeoffs.

Spectrum sensing capability through specific scanning schemes
In previous section, we have proposed the approach of TRANSEC design by considering both AJ and LPE capabilities concurrently for multiple jammers and interceptors. In this section, we will further investigate a kind of special jamming with both real-time scanning and transmission characteristics, i.e., concurrent detection and jamming capabilities, which is designed inherently to counter a FH communication system. This should be a good bench target to evaluate the performance of the FH spread spectrum system with both transmission and reception characteristics being considered simultaneously. Moreover, effective jamming probability metrics for specified scanning schemes taken by FOJ, are investigated, which will be good figures of merit for evaluating FH and CR communication system performance.

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Adaptation from Transmission Security (TRANSEC) to Cognitive Radio Communication 91

Survey of related works
For the past years, traditional spectrum management approaches have been challenged by their actually inefficient use or low utilization of spectrums even with multiple allocations over many of the frequency bands (NTIA). Thus, within the current regulatory frameworks of communication, spectrum is a scarce resource ,Spectrum policy task force report, 2002). Cognitive radio is the latest emphasized technology that enables the spectrums to be used in a dynamic manner to relieve these problems. The term "cognitive radio (CR)" was first introduced in 1999 by Mitola and Maguire and is recognized as an enhancement of software defined radio (SDR), which could enhance the flexibility of personal wireless services through a new language called the radio knowledge representation language (RKRL), and the cognition cycle to parse these stimuli from outside world and to extract the available contextual cues necessary for the performance of its assigned tasks (Mitola III & Maguire Jr., 1999;Mitola III, 2000). Haykin therefore defines the cognitive radio as an intelligent wireless communication system that is aware of its surrounding environment, and uses the methodology of understanding-by-building to learn from the environment and adapt its internal states to statistical variations in the incoming RF stimuli by making corresponding changes in certain operating parameters in real-time (Haykin, 2005). In addition, some engineering views and advances for helping the implementation of cognitive radio properties into practical communications are described (Jondral & Karlsruhe, 2007;Mody et al., 2007). With these groundbreaking investigations and developments, international standardization organizations and industry alliances have already established standards and protocols for cognitive radio as well (Cordeiro et al., 2005;Ning et al., 2006;Cordeiro et al., 2006). The frequency hopping spread spectrum (FHSS) systems are widely used in civil and military communications, but somewhat the benefits of FHSS systems could be potentially neutralized by a follow-on jamming (FOJ) with an effective jamming ratio covering the hopping period (Torrieri, 1986;Felstead, 1998;Burda, 2004).
In spite of the active jamming measures taken, FOJ is implicitly analogous to a cognitive radio communication with spectrum and location awareness, listen-then-act, and adaptation characteristics. Therefore, the cognitive process cannot be simply realized by monitoring the power or signal-to-noise ratio in some frequency bands of interest in a FH radio environment. For transmission security concerns, concurrent anti-jamming and low probability detection were investigated to have a secure communication (Liao et al., 2007). Furthermore, real-time spectrum sweeping characteristics are coordinated together with system parameters in temporal and frequency domains, e.g., scanning rate and framing processing time, for evaluating the performance of CR communications under an elliptical or a hyperbolic operation scenario, which can be applied for radio spectrum sensing and location awareness in cognitive radio communications. The proposed schemes and metrics can pave one practical way for system evaluations of cognitive radio communications (Liao et al., 2009). Although the performance evaluation of cognitive radio (CR) networks is an important problem, it has received limited attention from the CR community. It is imperative for cognitive radio network designers to have a firm understanding of the interrelationships among goals, performance metrics, utility functions, link/network performance, and operating environments. Various performance metrics at the node, network, and application levels are reviewed. A radio environment map-based scenariodriven testing (REM-SDT) for thorough performance evaluation of cognitive radios and an IEEE 802.22 WRAN cognitive engine testbed are also presented to provide further insights into this important problem area, respectively (Zhao et al., 2009). A coexistence window inside which the primary user and secondary user share the radio channel in time division manner is proposed. Connectivity probability and link utility efficiency are defined to measure the performance of secondary user. Considering the practical noise channel, how the metrics change is studied and the data rate of the secondary user in this case is obtained (Liu et al., 2010). An optimal power allocation scheme for a physical layer network coding relay based secondary user (SU) communication in cognitive radio networks is proposed.  Fig. 7 shows the basic FOJ function block diagram with many allocated process time to acquire incoming "victim" signals and implement jamming, where jT z time is the total analytical time needed to acquire the instant hoping frequency, τ r is the total activation time needed to synthesize and amplify a repeater signal tone or noise to jam the "victim" signal, which may compose of the process times of frequency synthesizer, power amplifier, and filter banks. In general, the processed times for these three parameters are in the order of us, ns, and ns, respectively. Furthermore, the propagation delay or difference time (τ d ) dependent on relative positions should be included for effective jamming probability analysis. For example, if the range difference (ΔR) is 30km, the τ d propagation difference time will be around 100 µs, far longer than the response time τ r . Therefore, this parameter can be assumed to be zero while compared to other larger parameters under this circumstance. Fig. 8 shows the effective jamming dwell time breakdown for FOJ, where T r represents the jamming total delay time of process delay and propagation time (=τ r +τ d ), T l represents the latency time (=jT z + T r ), and T j represents the effective jamming dwell time (=T h -T l ).

Adaptation from Transmission Security (TRANSEC) to Cognitive Radio Communication
T j must be smaller than T h under any circumstance. The effective jamming probability (h) is defined to be the ratio of T j and T h . Fig. 7. Effective dwell time (T J ) and latency time breakdown for CRU operation Scanning windows available during hopping dwell interval is defined to be m, which is represented as where T z represents the analysis framing time per scanning window W s of the jammer and └x┘ symbol means the maximum integer equal to or smaller than x. It follows that the follower jammer is able to analyze at most m scan windows during the single dwell interval, T h . Scanning window number available in the FH system bandwidth is defined to be n and represented as where W represents the hopping bandwidth of a FH system, W s represents scanning window of the jammer, and ┌x┐ symbol means the minimum integer equal to or larger than x. Let k be the number of scan windows which the FOJ analyzes in the dwell interval. It is evident that www.intechopen.com

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which means the smaller one of m or n is selected as the analyzed number of scanned windows. Let us suppose that one FH system operates in the bandwidth W only and that the follower jammer knows the parameters of the FH system and knows the moments of channel changes as well. Therefore, exactly at these moments (t=0), the jammer will initiate searching of the actual channel. When FH terminal transmits in j th scan window, then this transmission is found at moment t 0 = jT z . Let t 1 be the moment when the scanning receiver finds the actual transmission channel of the FH system. Let t 2 be the moment when the follower jammer initiates jamming of the found channel. Let t 3 be the moment when the initiated signal of the FOJ reaches the receiver site of the found channel, i.e., the FH receiver is jammed at the moment t 3 .

Scanning schemes
In the following sections, two schemes named uniform scanning and sequential scanning will be explored and taken as scanning measures to scan and trace the incoming hopping signals fast enough to implant effective noise or tone jamming thereafter. In addition, the case of delay response (T r ≠0) will be examined as well for these two scanning schemes.

Uniform scanning (U-scanning) scheme
A uniform scanning (U-scanning) technique will be explored and taken as the scanning measures to scan and trace the incoming hopping signals fast enough to implant transmission signals thereafter. If the CRU analyzes all scan windows randomly with uniform probability p u (T J )=1/n, and p u (T J )=(n-k)/n is the probability that the FH system operates in the scanning window which is not analyzed. Therefore, the probability distribution of the jammed period of the dwell interval can be given by It is assumed that T r is assumed not to be zero, i.e., τ r is zero, but τ d is not zero and T r =τ d =l×T h , where l is the propagation time ratio between T r =τ d and T h . The average jammed period of the dwell interval is therefore derived and given by From the above derived equation, the criterion of hopping rate (R hu ) and analysis framing time product (T z ) for effective dwell can be available and given by which is the basic condition whenever T r ≠ 0 for effective CRU. The effective dwell ratio and scanning rate (R su ) for uniform scanning technique can be expressed and given by equation (18)

Geometric model for FH jamming
In this section, two analytical geometric models, i.e., elliptic and hyperbolic, will be examined furthermore dependent on their relative positions among the FOJ, FH transmitter, and FH receiver. Fig. 9 shows an elliptic FH jamming model. If the relative positions among the FOJ, FH transmitter, and FH receiver are shown in Fig. 9 with fixed range R tr =a between the FH transmitter and receiver and varying FOJ position, then the following expressions will be available by using the fact that latency time (T l ) should be smaller than the hopping period (T h ) for an effective jamming.

Elliptical FH jamming model
where τ r can be assumed to be zero for instant response for the jammer, R jr is the range between transmitter and FOJ, and R jr is the range between FOJ and receiver. where D is assumed to be given by Fig. 10 shows the typical hopping rate (R h ) contours for an elliptic FH jamming model with varying FOJ locations and assumed scanning time around 1ms ( jT z =10×100µs) and fixed R tr =a =100km. Whenever a specified fixed hopping rate is required (e.g. R h =500Hz), an even higher hopping rate is necessary for the FH communication system if FOJ is penetrated through this boundary and inside the specified ellipse. On the contrary, if FOJ is located outside the ellipse boundary, then the specified hopping rate is fast enough to counter the FOJ jamming for the FH communication system. Fig. 9. Typical elliptic contour of FH jamming model

Hyperbolic FH jamming model
If the relative positions among the FOJ, FH transmitter, and FH receiver are shown in Fig.  11 with fixed range R tj =a between the FH transmitter and FOJ and varying FH receiver position, then the following expressions will be available by using the fact that latency time (T l ) should be smaller than the hopping period (T h ) for an effective jamming.
where τ r can be assumed to be zero for instant response for the jammer, R jr is the range between FOJ and receiver, and R tr is the range between transmitter and receiver. After a simple manipulation, a standard ellipse equation will be given by www.intechopen.com

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where D is assumed to be given by Fig. 10. Hyperbolic FH jamming model Fig. 12 shows the typical contours for a hyperbolic FH jamming model with varying FH receiver locations and assumed scanning time around 1ms (jT z =10×100µs) and fixed R tj =a=100km. Whenever a specified fixed hopping rate is required (e.g. R h =650Hz) under this circumstance, an even higher hopping rate is necessary for the FH communication system if the varying FH receiver is penetrated through this boundary to be closer to the fixed FOJ position on the right side. On the contrary, if the varying FH receiver is located on the left side of the hyperbolic boundary, then the specified hopping rate is fast enough to counter the FOJ jamming for the FH communication system.  Fig. 13 shows the comparison results of effective jamming probability (h) vs. hopping rate (R h ) for both uniform (U-) scanning and sequential (S-) scanning schemes. Under the same framing time (T z ) conditions it is observed obviously that S-scanning scheme is better than U-scanning scheme for fixed hopping rate, e.g., the effective jamming probability value will be around 0.8 and 0.5 if R h =500Hz and T z = 100us for S-and U-scanning scheme, respectively. In another point of view, S-scanning scheme will have better hopping rate sensing capability (650Hz) than U-scanning scheme (500Hz) if effective jamming probability is fixed at 0.5.  Fig. 7 shows the basic FOJ function block diagram with many allocated process time to acquire incoming "victim" signals and implement jamming. This function block diagram is basically analogous to a cognitive radio unit (CRU) for sensing spectrum signals while applied in a cognitive communications adapted from TRANSEC. In addition, CRU models with U-scanning and S-scanning schemes and cognitive perception ratio (CPR) metric for quantified cognitive communications could be available as well. In this model real-time spectrum sensing characteristics can be coordinated together with system parameters in temporal and frequency domains, e.g., scanning rate and framing processing time, for evaluating the performance of CR communications under an elliptical or a hyperbolic operation scenario. Fig. 14 and Fig. 15 show the hyperbolic and elliptic CPR contours, respectively, with both U-and S-scanning being put together for comparisons, and with T z =100us and R h = 500Hz.

Fig. 14. Elliptic CPR contours with U & S scanning & R h = 500Hz
It is observed from Fig. 14 that the CPR-contour values of 0.25 to 0.45 (blue solid) and values of 0.3 to 0.8 (red dashed) for U-scanning and S-scanning, respectively, are shown from the left hyperbolic trajectories to the right trajectories. And it is observed from Fig. 15 that the CPR-contour values of 0.05 to 0.45 (blue solid) and values of 0.1 to 0.8 (red dashed) for Uscanning and S-scanning, respectively, are shown from the outside elliptic trajectories to the inner trajectories. As stated in last section, the performance of S-scanning scheme is better than U-scanning scheme in many aspects. And it will be the same, if the location awareness conditions are established through direction finding and emitter location capability, and are collaborated with each other among CRUs.

Conclusion
In this paper, we have first proposed a systematic approach with their corresponding metrics for evaluating independent and concurrent AJ and LPD performance qualitatively and quantitatively. A representative GEO satellite communication scenario for independent and concurrent AJ and LPD performance evaluations is explored thoroughly. Based on these metrics, it is direct to see that by spreading signal spectrum, complicating signal waveforms, or lowering power control uncertainty, respectively, will enhance system performance accordingly. A CRU model with U-scanning or S-scanning techniques and a quantified CPR metric for cognitive communications adapted from TRANSEC is investigated as well. In this model real-time spectrum sensing characteristics are coordinated together with system parameters in temporal and frequency domains, e.g., scanning rate and framing processing time, for evaluating the performance of CR communications under an elliptical or a hyperbolic operation scenario, which can be applied for radio spectrum sensing and location awareness in cognitive radio communications. The proposed schemes and metrics can pave one practical way for the system evaluations of cognitive radio communications.