Equalization attacks against OFDM: analysis and countermeasures

Abstract

This paper introduces, investigates, and proposes power‐efficient equalization jamming attacks against the orthogonal frequency division multiplexing (OFDM) and possible countermeasures. Signals known a priori, called pilot tones, are employed in the conventional OFDM‐based systems to estimate the channel response and perform equalization. Attacks against these pilot tones can hamper equalization and degrade target's performance. This paper begins with noise‐based pilot tone jamming and moves onto pilot nulling attack. The paper embraces two mitigation strategies of randomizing the pilot tones. The paper presents mathematical model of effective noise per symbol and simulation results for OFDM systems with conventional and randomized pilot‐tones under such attacks. The paper concludes that the noise‐based pilot tone attacks are power efficient than conventional attacks, and the pilot nulling is capable of doing the most damage, but in the expense of additional channel state information. The paper also claims that the mitigation strategies offer a remedy, but works relatively poorly when no jammer is present. Copyright © 2015 John Wiley & Sons, Ltd.

Interference‐resilient spectrum sharing with collision detection and data recovery for cognitive radio networks

“…24,25 For estimating the PU signal subspace under collision scenario, a pilot permutation scheme within the data symbols subject to minimizing the channel estimation error has been proposed as well in this work. Many research studies [26][27][28][29][30][31] in literature have considered permuting the training data and pilot patterns for accurate channel and frequency offset estimation and as a countermeasure against security attacks. 31,32 However, none of these works can be directly compared with the data recovery task under consideration.…”

“…Many research studies [26][27][28][29][30][31] in literature have considered permuting the training data and pilot patterns for accurate channel and frequency offset estimation and as a countermeasure against security attacks. 31,32 However, none of these works can be directly compared with the data recovery task under consideration. The spectrum sensing technique proposed here is based on correlation-based preamble detection [33][34][35] ; however, a more reliable and modified version of spectrum sensing technique for application in OFDMbased CR under collision scenarios has been proposed, in contrast to the work of Pattanayak et al 35 proposed for detection of FM/microphone signals within the same band.…”

Modeling of Water Quality Parameters using Data-Driven Models, A Case Study Abo-Ziriq Marsh in South of Iraq

“…The idea of equalization is shown in Fig. 7 (Sanjana and Suma, 2014;Shahriar et al, 2016). It can be seen from Fig.…”

Identification method for OFDM signal based on fractal box dimension and pseudo-inverse spectrum

“…(1) Replacing the received signal into equations (6) and 14, we can get d( ) and d (2 ), then according to equation (5 If γ > J D , we could conclude that the received signal exists OFDM signal. Otherwise, the received signal is considered as Gaussian noise.…”

“…Multicarrier techniques, especially orthogonal frequency division multiplex (OFDM) system is a special cognitive radio system, which has been widely used in military and civilian applications [1]. One crucial aspect of spectrum monitoring and electronic countermeasures reconnaissance is the identification for OFDM signal [2]. In order to recognize the transmitted OFDM signal parameters, the identification of OFDM signal must be achieved first.…”