Proceedings of the International Conference on Electrical and Computer Systems Ottawa, Ontario, Canada, 22-24 August 2012 Paper No. 124
Jamming and Fading Channels Mitigation Using Anti-Jamming Advanced Frequency Hopping Walid M. Saad, Ian Marsland Carleton University, Department of Systems and Computer Engineering 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6
[email protected];
[email protected]
Abstract - Performance degradation caused by channel dispersion can be mitigated using avoidance techniques such as frequency hopping spread spectrum. Adaptive frequency hopping techniques such as matched frequency hopping (MFH), clipped matched frequency hopping (CMFH) and advanced frequency hopping (AFH) have been introduced as efficient techniques in slowly fading dispersive channels. These techniques work by adaptively selecting a subset of frequencies over which hopping is performed, in an attempt to avoid severely attenuated frequencies. This paper contains a comparison of the performance of these techniques when smart jamming signals interfere with the transmission in addition to frequency selective fading. Modifications to these techniques are then proposed that provide greater resilience to jamming. In particular, the proposed anti-jamming advanced frequency hopping (AJAFH) technique is shown to be very effective in jamming environments, providing much higher throughput than the existing techniques. Keywords: frequency hopping spread spectrum (FHSS), matched frequency hopping (MFH), anti-
jamming (AJ), frequency selective fading
1. Introduction Frequency hopping is a spread spectrum technique that involves partitioning the allocated frequency band into a large number of sub-channels. With slow frequency hopping spread spectrum (FHSS), transmission is carried out in short bursts of a few bits on one sub-channel at a time, hopping from subchannel to sub-channel in a pseudo-random fashion after each burst. In this manner all sub-channels are used a roughly equal amount of time, but no sub-channel is used continuously for a long time. The pseudo-random hopping pattern used by the transmitter is known by the intended receiver so it can easily recover the transmitted signal, but other receivers, without this knowledge, are unable to detect the signal, thereby impeding undesirable signal interception. One problem with FHSS as described above is that, in a frequency-selective fading environment, at any given time some sub-channels may be severely attenuated (or, in a jamming environment, some sub-channels may be jammed). Better performance is possible if frequency hopping is performed over only a subset of the sub-channels. Sub-channels that have severe attenuation or are jammed are excluded from the subset. Many techniques have been proposed for selecting the subset of sub-channels, including matched frequency hopping (MFH) (El-Khamy, 1998), clipped matched frequency hopping (CMFH) (El-Khamy et al., 2005), and advanced frequency hopping (AFH) (El-Khamy, Saad, 2009). These techniques, known as tone selection algorithms, however, were designed in the absence of jamming (only frequency-selectivity is considered). In this paper we present a new tone selection algorithm designed to work in the presence of jamming and slow frequency selective fading. Section 2 of this paper provides a description of the system model under consideration, while Section 3 gives details on some existing tone selection algorithms. A performance comparison of these techniques, in terms of system throughput, is presented in Section 4, in both the absence and presence of jamming. Our new anti-jamming technique is presented in Section 5, along with throughput comparisons that demonstrate the benefits of this method.
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2. System Model In this system, the allocated frequency band is partitioned into K sub-channels. The transmission starts by sending training sequences over each of the K sub-channels to facilitate channel estimation. Assuming that the sub-channels are sufficiently narrow relative to the coherence bandwidth of the channel, each sub-channel experiences frequency flat fading, with complex channel gain Hk for the kth sub-channel, k ϵ {1, 2, ...., K}. Once the receiver has estimated the channel gains, it selects the N “best” sub-channels (N tones) according to one of the tone selection algorithms described in Section 3 of this paper. A list of the selected tones is fed back to the transmitter using a tone selection mask of K bits. The transmitter then begins transmitting data, hopping pseudo-randomly over the N selected tones. Periodically, as the channel changes over time, channel estimation is repeated and the list of selected tones is updated. The focus of this paper is on the tone selection algorithm, including comparison of our new technique with the previously proposed algorithms. To provide an illustrative example we consider the frequency selective channel model proposed by Rummler (Rummler, 1979), (Lundgren, Rummler, 1979). This two ray multipath channel model can be modified to account for the finite channel bandwidth (El-Khamy, Dobaie, 1991). The channel gains for the two-ray channel model can be expressed as
2k K 1
H c 1 s exp j 2 k
2K
f
null
D
(1)
where c is the scale factor, s is the shape factor, fnull is the normalized fading null frequency offset from the band centre, and D is the normalized delay spread.
3. Tone Selection Algorithms In this section five different tone selection algorithms are presented. Each algorithm selects N tones out of the K available sub-channels for use with frequency hopping. The first two algorithms do not exploit the channel estimation, and are included as low-complexity benchmark schemes. The third algorithm, MFH selects the tones based on the channel characteristics. The last two algorithms, clipped MFH and advanced FH, are variants of MFH. The first algorithm is random frequency hopping (RFH). In this simple algorithm the N tones are selected randomly from the K sub-channels. That is, for n ϵ {1, 2, ...., N}, the index of the nth selected tone, kn, is selected randomly from {1, 2, ...., K}, where the selection is done without replacement so no sub-channel can be selected more than once. The second algorithm is uniform frequency hopping (UFH) that the N tones are selected equally spaced (uniformly) from the K sub-channels. The index of the nth selected tone is K 1 k n n N 2
(2)
rounded to the nearest integer, for n ϵ {1, 2, ...., N}. In MFH the tones are selected based on the channel gains, Hk, so that good tones tend to be selected, while also keeping the tones reasonably well-spaced (El-Khamy, 1998). In particular, the normalized tone power metric,
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P k
Q
k
(3)
K
Ql
l 1
where Qk = |Hk|2, is calculated for each tone, along with the cumulative metric k
C P k l
(4)
l 1
which is a monotonically increasing function of k, spanning the range [0, 1]. The cumulative metrics are used with the N equally-spaced values over [0, 1],
y n
1 1 n N 2
n 1, 2 ,......,N
(5)
to determine the indices of the selected tones. The index of the nth tone is given by the value of kn such that Ckn 1 yk Ckn (El-Khamy, 1998). This procedure is illustrated in Fig. 1, where N = 10 tones are selected. It is clear that the algorithm tends to select tones with low attenuation, while avoiding selecting clusters of adjacent tones, as would be the case if one were to merely select the N tones with the lowest attenuations.
1 Channel PSD comulative metric selected tones
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Fig. 1. Illustration of selecting N = 10 tones out of K = 100 tones using MFH in a Rummler channel
MFH performance is improved by clipping the PSD of the channel with a certain value proportional to the maximum amplitude of this PSD (El-Khamy et al., 2005). Any value of the PSD of the channel less than a specific threshold, T, is set to zero according to
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| H |2 T Q k k 0
if | H |2 T k
(6)
if | H |2 T k
The CMFH technique will result in more concentrated hopping frequencies within the less-attenuated bands than in the MFH technique. The performance of MFH is improved by using the AFH technique (El-Khamy, Saad, 2009) that improves the selection of the hopping pattern by placing more emphasis on sub-channels with low attenuation. It is based on a modified PSD given by
Q k
|H |2 k
(7)
( 1 ) max|H |2 |H |2 k
k
where α is a small value. After calculating the modified PSD we will select the hopping pattern in the same way as the MFH technique. That will result in ignoring the slots with high attenuation as will be shown in Section 4.
4. Performance Comparison In this section we will use the Rummler channel with parameters c = , s = 0.75, D = 1.5 and fnull = 0.2 to illustrate the selected tones for each of the previously mentioned technique as shown in Fig. 2. Fig. 2a illustrates the positions of N tones selected from K=100 sub-channels, along with the PSD of a Rummler channel. We see that the selected tones, indicated by black vertical lines, are randomly distributed over the frequency band, and that some tones are for sub-channels with severe channel attenuation. For example, sub-channels 13, 56, 72, 73 and 81 have been selected even though the channel gains are low. This will degrade system performance, resulting in either a high bit error rate (BER) or the need for a low-rate error correcting code, diminishing the system throughput.
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Fig. 2. Graphical representation of different frequency hopping patterns in the presence of jamming 124-4
As shown in Fig 2b, we can see that UFH suffers from the same channel degradation as RFH. However, its performance is better in the presence of partial band jamming, in which the jammer concentrates all its available power to jam a fraction of the transmission bandwidth, and multi-tone jamming, in which the jammer distributes its power over a number of frequency bands to jam a larger percentage of the transmission bandwidth, because the hopping frequencies are equally separated over the total bandwidth. This separation forces the jammer to jam a large number of sub-channels. Figs. 2c, d, e illustrate the selected tones using MFH, CMFH, and AFH techniques respectively. To provide a comparison of the relative merits of the presented frequency hopping techniques, we use the average system throughput, given by
ave( )
1 N 2 log2 1 | H k n | N n 1
(8)
as a performance metric, where is the signal to noise ratio (SNR), N is the number of the selected tones, and |Hkn|2 is the channel gain of the nth selected tone. A comparison of the throughput, for the presented Rummler channel in the absence of jamming, is shown in Fig. 3a. The RFH and UFH techniques have the worst performance because they do not consider the channel characteristics in their tone selection. As a result many of their selected tones suffer from severe channel attenuation. The MFH and CMFH techniques have better performance because they select their tones concentrated within sub-channels that have high channel gains. The modified function in AFH makes the tone selection even more concentrated within sub-channels that have high channel gains. For this reason the AFH technique has the best performance when compared to the others. However, this comparison is based on the assumption that there is no jamming in the channel. To investigate the effects of jamming on system throughput, we assume a smart jammer that can simultaneously jam two clusters of sub-channels, each containing 5% of the transmission bandwidth. The jammer selects the clusters so that the largest numbers of selected hopping frequencies are jammed. Whenever the set of selected tones is changed, the jammer tries to detect this change and repositions the two jamming clusters to again attack the largest number of selected tones. The positions of the two jamming clusters are also shown in Fig. 2. 7
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AFH CMFH MFH UFH RFH
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Fig. 3. The performance of the different tone selection algorithms
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The average throughput of all the techniques is compared in the presence of jamming, as shown in Fig. 3b. We see that the performance of all techniques is degraded compared to their performance in the absence of jamming. However, the performance of AFH is particularly degraded, so much so that CMFH has the best performance in the presence of jamming compared to the other techniques. It is clear that concentrating the selected tones in sub-channels with low attenuations, which is advantages in the absence of jamming, becomes a liability in jamming environments because it is easier for the jammer to disrupt the transmission.
5. A Novel Anti-jamming Technique To reduce the detrimental effects of jamming, the communication system should employ antijamming techniques. In this section we propose a simple modification to AFH that mitigates the effects of jamming. When the receiver detects the presence of jamming, it should select a new set of tones, avoiding the jammed sub-channels. This can easily be accomplished by using the clipped matched PSD, Q' k Qk ( 1 J k )
(9)
in the tone selection algorithm, where Qk is given by (7) and no jammingin sub channelk; jammingin sub channelk.
0 J k 1
(10)
When the jammer starts to attack the frequency bands that have a large number of selected tones and the receiver detects this threat, Q′k will be applied to the modified PSD of the channel and then the N tones will be selected using the MFH technique. Whenever the jammer changes the jamming bands the system will change the selected tones using the new values for Q′k. Fig. 4 illustrates the system operation with the proposed anti-jamming AFH (AJAFH) technique. In the absence of jamming the receiver uses AFH to select the tones, as shown in Fig. 4a, and transmission begins over these tones. Eventually the jammer detects the presence of signals on these tones and begins jamming as many of the tones as it can. The receiver can quickly detect the presence of the jamming, and immediately applies the AJAFH technique to select new tones, avoiding the jammed sub-channels, as shown in Fig. 4b. We see that tones with low attenuation still tend to be selected, while jammed tones are avoided.
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Fig. 4. Illustration of AFH and AJAFH before and after jamming detection 124-6
The AJAFH technique is also suitable in multitone jamming environments, where the jammer blindly jams a large number of sub-channels. Fig. 5 shows that AJAFH is able to select good tones even in this situation.
1 PSD Modified PSD Selected tones
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Fig. 5. Illustration of AFH and AJAFH before and after jamming detection in the presence of multitone jamming
This technique of clipping the jammed sub-channels in the tone selection process can also be applied to the other tone selection algorithms. The new proposed techniques are: anti-jamming matched frequency hopping (AJMFH), anti-jamming clipped matched frequency hopping (AJCMFH), anti-jamming advanced frequency hopping (AJAFH), and anti-jamming uniform frequency hopping (AJUFH). Fig. 6 shows the selection of tones for each of these techniques after clipping the jammed sub-channels.
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Fig. 6. Graphical representation for the selection of different hopping patterns using AJMFH, AJCMFH, AJAFH, and AJUFH after clipping the jammed bands
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As shown in Fig. 7a, the AJAFH technique provides a significant advantage in terms of average throughput over the techniques that do not adapt to the presence of jamming. It can be seen that AJAFH gives the improvement in throughput of over 10% compared to AFH. Fig. 7b provides a comparison between AJUFH, AJMFH, AJCMFH and AJAFH in terms of the average throughput. It can be seen that AJAFH is the most effective of the techniques. 7
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b) Compared to AJMFH, AJCMFH and AJUFH
a) Compared to MFH, CMFH and AFH
Fig. 7. The performance of AJAFH system
6. Conclusion In this paper, a new algorithm is presented to mitigate the fading and jamming in slowly fading frequency-selective channels. The new algorithm consists of two steps. In the first step AFH is used before the receiver detects any jamming signals. The throughput results in Fig. 3a show that AFH is an effective technique for spread spectrum signaling in the absence of jamming in slowly fading dispersive channel. In the second step of the algorithm when the receiver detects the jamming signals, AFH is modified to the AJAFH technique which is used to select the new tones. This technique is able to select tones that have low attenuation while avoiding jammed sub-channels. Furthermore, the tones are somewhat spread out to provide resilience for the tone when the smart jammer is able to adjust its jamming clusters but before the receiver is able to adapt with new tones. The results show that the performance of CJAFH technique is very effective against jamming in frequency-selective channels.
References El-Khamy S. E., Dobaie A. M., (1991). Propagation-medium Matched Direct Sequence (PM-MDS) Spread-spectrum Signals “IEEE Trans. Antennas Propagat.,” Oct., pp. 1449–1456. El-Khamy S. E., (1998). Matched Frequency Hopping (MFH) Signals for Slowly Fading Dispersive Channels “IEEE Trans. Vehicular Technology,” Feb., pp. 365–369. El-Khamy S. E., Abdalla F., Al-Hourani A., (2005). An Improved Channel Aware Clipped Matched Frequency Hopping (CMFH) Signaling Technique in Slowly Fading Dispersive Channels “IEEE Trans. Commun.,” Apr., pp. 506–509. El-Khamy S. E., Saad W. M., (2009). New Technique for Enhancing the Signaling in Slowly Fading Dispersive Channels “IEEE Commun. Mag. Cognitive Radio,” Sept., vol. 2, pp. 1–4. Lundgren C. W., Rummler W. D., (1979). Digital Radio Outage to Selective Fading Observation vs. Prediction from Laboratory Simulation “Bell Sys. Tech. J.,” May-June, vol. 58, no. 5, pp. 1073– 1100. Rummler W. D., (1979). A New Selective Fading Model: Application to Propagation Data “Bell Syst. Tech. J.,” May-June, vol. 58, no. 5, pp. 1037–1071.
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