To allow users to access networks and services ubiquitously, more and more user equipments (UEs) are equipped with multiple radio transceivers. However, due to the proximity of transmit and receive frequencies of in-device wireless technologies, the transmitter (TX) of one in-device wireless technology can interfere with the reception of another wireless technology within the same device, and the spurious emissions of the aggressor TX may result in unacceptable interference at the victim receiver which is co-located in-device. Hence, it is crucial to detect the in-device interference and adapt the strategies to avoid harm. In this paper, we consider the scenario of LTE coexisting with WiFi. Different from traditional spectrum sensing in cognitive radio which detects signal in the background of Gaussian noise, the WiFi leakage detection problem in this paper aims to detect WiFi leakage in the background of LTE signal and Gaussian noise. This makes the problem challenging. By identifying unique features of the WiFi leakage, we investigate this problem thoroughly and propose two detection algorithms, including entropy ratio based and cyclostationary based algorithms. Simulation results under different scenarios are presented to illustrate the effectiveness and efficiency of the proposed detection techniques.

In this paper, we propose a new method for blind modulation detection based on detailed second order cyclostationary features for underwater acoustic communication. Due to the severe and fast varying Doppler shift and phase noise in the underwater acoustic communication channel, much shorter signal length can be used to detection the modulation scheme, leading to less accuracy in the modulation detection performance. Here we propose a brand new method to perform modulation detection: by analyzing the zoomed-in spectral coherence function (SOF) of short time signal, we observe distinctive detailed features for different modulations. Taking advantage of such detailed features in short time SOF, we design a novel blind modulation detection algorithm for underwater acoustic communication system. To the best of our knowledge, our paper is the first to employ such detailed, in some sense hidden, features of cyclostationary analysis to conduct modulation detection. Coupled with our previous work on blind carrier frequency estimation and symbol rate estimation algorithms, the proposed modulation detection algorithm enjoys very high detection accuracy, high speed, and low complexity. Real experimental data collected at sea are used to validate the effectiveness of the proposed algorithm. It is also important to note that the proposed method does not assume any a priori knowledge of the target signal.

Target detection is a surveillance problem of practical importance that is well suited to wireless sensor networks. In this paper, we study the target search via track-before-detect process for moving targets in large area utilizing a network of distributed sensor nodes. Specifically, we extend the track-before-detect process to heterogeneous sensors with imperfect communication links between the sensor and fusion center. We consider two different models: (1) heterogeneous sensors with different probability of detection and perfect communication links; and (2) heterogeneous sensors with imperfect communication links. To analyze the performance of searching process for the system, we derive the expressions for the probabilities of both successful search and false search. We also investigate the strategy to optimize the system by obtaining the minimal false search when meeting the requirement of the successful search performance.

Orthogonal Frequency Division Multiplexing (OFDM) has been considered as a strong candidate for next generation high speed aerial vehicle communication systems. However, OFDM systems suffers severe performance degradation due to inter-carrier interference (ICI) in high mobility channel, if no ICI cancellation is performed. Traditionally, training symbols have been employed in one packet to help the OFDM receiver to estimate the multi-path channel and the carrier frequency offset (CFO) between the transmitter local oscillator and the receiver local oscillator. However, in aerial vehicle communication, the relative transmitter-receiver speed changes so rapidly that it is unreasonable to assume a constant speed (and CFO) during the entire packet transmission. Hence, to accurately estimate the CFO, training symbols need to be transmitted for every OFDM symbol. Obviously, this significantly reduces OFDM throughput while adding complexity due to repeated CFO estimation. In this paper, we extend our previous work to propose a joint channel/CFO estimation and ICI cancellation algorithm. Specifically, in our previous work, we have proposed a total ICI cancellation algorithm using parallel processing for OFDM system which offers the excellent ICI cancellation and BER performance. However, in this work, perfect channel information was assumed. In this paper, we combine the channel estimation with the ICI cancellation together. The proposed general total ICI cancellation algorithm has the ability to jointly estimate the carrier frequency offset and channel information, and improve the performance significantly. Meanwhile, a serial processing is proposed to reduce the computation complexity. Simulation results in different scenarios confirm the performance of the proposed scheme in multipath fading channels for high speed aerial vehicle communication.

Orthogonal Frequency Division Multiplexing (OFDM) has been considered as a strong candidate for next generation wireless communication systems. Compared to traditional OFDM, Single Carrier OFDM (SC-OFDM) has demonstrated excellent bit error rate (BER) performance, as well as low peak to average power ratio (PAPR). Similar to other multi-carrier transmission technologies, SC-OFDM suffers significant performance degradation resulting from intercarrier interference (ICI) in high mobility environments. Existing techniques for OFDM can be directly adopted in SC-OFDM to improve performance, however, this improved performance comes at costs such as decreased throughput. In this paper, we analyze the effect of ICI on an SC-OFDM system and propose a novel modulation scheme. The proposed Magnitude-Keyed Modulation (MKM) modulation provides SC-OFDM system immunity to ICI and with an easy implementation it significantly outperforms OFDM, SC-OFDM and MC-CDMA systems with Phase Shift Keying (PSK) modulation and Quadrature Amplitude Modulation (QAM) in severe ICI environment. Analysis also illustrates the proposed SC-OFDM system with MKM modulation maintains low PAPR compared to traditional OFDM and SC-OFDM systems with PSK and QAM modulations. Simulation results for different modulation schemes in various ICI environments confirm the effectiveness of the proposed system.

Cyclostationary analysis such as spectral correlation function (SCF) and spectral coherence function (SOF) has been accepted as an important tool in signal detection and radio frequency (RF) parameter estimation in cognitive radios. However, cyclostationary analysis requires extremely high resolution to fully observe the cyclic frequency features, leading to very high computational complexity and difficulty in real time implementation, especially on software defined radios where computational capability is limited. In this paper, we implement and demonstrate a real time SCF/SOF RF signal analyzer by adopting previously proposed two-stage dynamic resolution SCF/SOF estimation method using software defined radios. Specifically, high resolution SCF/SOF calculation is only performed near the expected cyclic feature locations obtained through a low complexity coarse estimation employing spectral analysis. This cyclostationary analysis based RF signal analyzer is capable of sensing the existence of primary users and estimating the carrier frequency and symbol rate accurately. Using Universal Software Radio Peripheral (USRP) software defined radio platform and GNU radio software, we implement and demonstrate such a cyclostationary analysis based RF signal analyzer in real time and validate the performance in realistic wireless communication channels.

In recently developed cognitive radio network (CRN), the spectrum sharing leads to many uncertainties associated with the aggregate interference in the network. It is highly desired to build an interference model for such cognitive radio networks to express such uncertainties to quantify the effect of the interference on the primary network. However, existing interference models have not account for lognormal shadowing due to the difficulty to estimate the entire lognormal sum distribution. In this paper, we propose to utilize the Scaled Student's t distribution to approximate the shadowing effect and improve existing interference models in CRN. Closed form probability density function (PDF), cumulative distribution function (CDF) and characteristic function (CF) of the interference including shadowing effects are derived. Simulation results of CDF, complementary CDF (CCDF), CF and bit error rate (BER) performance in various scenarios confirm the effectiveness of the proposed approximation method.

In cognitive radio (CR) and dynamic spectrum access (DSA) network research, most of current work on spectrum sensing focuses on the detection of existence of the spectrum holes for secondary user (SU) to harness. However, in a more sophisticated CR, the SU needs to detect more than just the existence of primary users (PUs) and spectrum holes: e.g., the transmission power and location of the primary users. In our previous work, we combined the spectrum sensing and PU power/localization detection together, and developed a joint PU detection and power/localization detection algorithm via compressed sensing (CS). By employing compressed sensing, the measurement ratio for the spectrum sensors is significantly reduced. However, if the measurement ratio is too low, the compressed sensing algorithm will not provide accurate estimates. Since the sparsity in the frequency domain is dynamically changing, it is unfeasible to set a predetermined measurement ratio. In this paper, we extend our previous work to employ the Bayesian Compressed Sensing (BCS) to improve the reconstruction results and dynamically determine the measurement ratio. Specifically, the BCS algorithm provides an "error bar" along with the reconstruction of the target vector. This "error bar" can then be used to determine if the current measurement ratio is sufficient. When the spectrum environment changes, the "error bar" will change accordingly, giving us direction to increase or decrease the measurement ratio. Simulation results including the measurement ratio, the miss detection probability (MDP), false alarm probability (FAP) and reconstruction probability (RP) confirm the effectiveness and robustness of the proposed method.

A spectrally modulated spectrally encoded (SMSE) based overlay cognitive radio has been implemented and demonstrated in [1] via GNU software define radio (SDR). However, like most of the current cognitive radio implementations and demonstrations, this work does not consider the mobility between cognitive radio nodes. In a high mobility environment, the frequency offset introduced by Doppler shift leads to loss of the orthogonality among subcarriers. As a direct result, severe inter-carrier interference (ICI) and performance degradation is observed. In our previous work, we have proposed a new ICI cancellation method (namely Total ICI Cancellation) for OFDM [2] and MC-CDMA [3] mobile communication systems, which eliminates the ICI without lowering the transmission rate nor reducing the bandwidth efficiency. In this paper, we apply the total ICI cancellation algorithm onto the SMSE base overlay cognitive radio to demonstrate a high performance cognitive radio in high mobility environment. Specifically, we demonstrate an SMSE based overlay cognitive radio that is capable of detecting primary users in real time and adaptively adjusting its transmission parameters to avoid interference to (and from) primary users. When the primary user transmission changes, the cognitive radio dynamically adjusts its transmission accordingly. Additionally, this cognitive radio maintains seamless real time video transmission between the cognitive radio pair even when large frequency offset is introduced by mobility between CR transmitter and receiver.

For orthogonal frequency division multiplexing (OFDM) communication systems, the orthogonality among subcarriers is lost in mobile radio channels due to the frequency offsets caused by mobility. As a direct result, intercarrier interference (ICI) is observed on each and every subcarrier, leading to significant performance degradation. Many ICI cancellation methods such as windowing and frequency domain coding have been proposed in the literature to cancel ICI and improve the BER performance of OFDM in mobile channel. However, the performance improvement achieved by all the existing ICI cancellation methods is far from enough: the BER performance after ICI cancellation is still much worse than the BER performance of original OFDM without ICI. Moreover, popular ICI cancellation methods like ICI self-cancellation reduce ICI at the price of lowering the transmission rate and reducing the bandwidth efficiency. Other frequency-domain coding methods do not reduce the data rate, but produce less reduction in ICI as well. In this paper, we propose a novel ICI cancellation scheme which can eliminate the ICI entirely and offer a OFDM mobile system with the same BER performance of a OFDM system without ICI. More importantly, the proposed ICI cancellation scheme, namely Total ICI cancellation, does not lower the transmission rate or reduce the bandwidth efficiency. Specifically, the total ICI cancellation scheme takes advantage of the orthogonality of the ICI matrix and offers perfect ICI cancellation and significant BER improvement at linearly growing cost. Simulation results in AWGN channel and multi-path fading channel confirm the superb performance of the proposed total ICI cancellation scheme in the presence of frequency offset or time variations in the channel, outperforming all the existing ICI cancellation methods.

Multi-carrier code division multiple access (MC-CDMA)has been considered as a strong candidate for next generation wireless communication system due to its excellent performance in multi-path fading channel and simple receiver structure. However, like all the multi-carrier transmission technologies such as OFDM, the inter-carrier interference (ICI) produced by the frequency offset between the transmitter and receiver local oscillators or by Doppler shift due to high mobility causes significant BER (bit error rate) performance degradation in MC-CDMA system. Many ICI cancellation methods such as windowing and frequency domain coding have been proposed in the literature to cancel ICI and improve the BER performance for multi-carrier transmission technologies. However, existing ICI cancellation methods do not cancel ICI entirely and the BER performance after ICI cancellation is still much worse than the BER performance of original system without ICI. Moreover, popular ICI cancellation methods like ICI self-cancellation reduce ICI at the price of lowering the transmission rate and reducing the bandwidth efficiency. Other frequency-domain coding methods do not reduce the data rate, but produce less reduction in ICI as well. In this paper, we propose a novel ICI cancellation scheme that can eliminate the ICI entirely and offer a MC-CDMA mobile system with the same BER performance of a MC-CDMA system without ICI. More importantly, the proposed ICI cancellation scheme (namely Total ICI Cancellation) does not lower the transmission rate or reduce the bandwidth efficiency. Specifically, by exploiting frequency offset quantization, the proposed scheme takes advantage of the orthogonality of the ICI matrix and offers perfect ICI cancellation and significant BER improvement at linearly growing cost. Simulation results in AWGN channel and multi-path fading channel confirm the excellent performance of the proposed Total ICI Cancellation scheme in the presence of frequency offset or time variations in the channel, outperforming existing ICI cancellation methods.

For orthogonal frequency division multiplexing (OFDM) communication systems, the orthogonality among subcarriers is lost in mobile applications due to frequency offset resulting from either transmitter-receiver local oscillator differences or Doppler shift caused by mobility. As a direct result, inter-carrier interference (ICI) is observed on each and every subcarrier, leading to significant performance degradation. There are a lot of OFDM carrier frequency offset (CFO) estimation schemes classified as data aided estimation and blind estimation. Due to the system power and high bandwidth efficiencies, blind estimators have received a lot of attention recently. Many blind CFO schemes were proposed for OFDM systems, some of which are based on power spectrum smoothing, kurtosis-type cost functions and minimum output variance. In this paper, we propose a novel blind CFO estimator based on Minimum Reconstruction Error (MRE). In contrast to other blind CFO estimators, the proposed technique can be used for any constellation schemes, does not require a large number of blocks to reach acceptable estimation error and provides reliable estimation performance with very low mean square error (MSE). Simulation results in AWGN and multi-path fading channels confirm that performance of the proposed highly accurate blind CFO estimator is superior when frequency offset or time variation occurs in the channel - the proposed technique outperforms most existing blind CFO estimation methods.

Interest in Cognitive Radio (CR) remains strong as the communications community strives to solve the spectrum congestion problem. In conventional CR implementations, interference to primary users is minimized using either overlay waveforms that exploit unused (white) spectrum holes or underlay waveforms that spread their power spectrum density over an ultra-wide bandwidth. In Part I, we proposed a novel hybrid overlay/underlay waveform that realizes benefits of both waveforms and demonstrated its performance in an AWGN channel. This was done by extending the original Spectrally Modulated Spectrally Encoded (SMSE) framework to enable soft decision CR implementations that exploit both unused (white) and underused (gray) spectral areas. In Part II, we analyze and evaluate performance of the proposed hybrid overlay/underlay waveform in frequency selective fading channels. A simulated performance analysis of overlay, underlay and hybrid overlay/ underlay waveforms in frequency selective fading channels is presented and benefits discussed.

Abstract In this paper, we present a software‐defined radio (SDR) based cognitive radio (CR) implementation and demonstration over the frequency modulation (FM) band. Using GNU Radio as the software platform and USRP (Universal Software Radio Peripheral) SDR boards as the hardware solution, we implement and demonstrate a CR that autonomously senses the entire FM band, detects all the active FM stations (occupied bands) as well as the spectrum holes (non‐occupied bands), exploits the available spectrum holes to transmit secondary users' data without interference with the existing FM transmission. Moreover, we demonstrate that when a primary user's transmission returns to its allocated spectrum band after a period of absence, the CR automatically adapts its transmission and hands off to a different spectrum hole that is available to avoid interference with the returning primary user. Moreover, we have proposed, implemented, and demonstrated a frequency hopping scheme over multiple spectrum holes to support multiple secondary users while attaining the minimum interference among the users. Copyright © 2009 John Wiley & Sons, Ltd.

SC-OFDM (single carrier orthogonal frequency division multiplexing) has demonstrated excellent performance in multipath fading channels with very low peak to average power ratio (PAPR). Similar to other multi-carrier transmission technologies such as MC-CDMA and OFDM, SC-OFDM also suffers significant performance degradation to inter-carrier interference (ICI) when there is a frequency offset between the transmitter and receiver or in a high mobility environment. In this paper, we analyze the effect of ICI on SC-OFDM system and propose a novel modulation scheme called Magnitude Shift Keying (MSK) for SC-OFDM system. The MSK modulation provides SC-OFDM system immunity to ICI and significantly outperforms SC-OFDM system and OFDM system with Phase Shift Keying (PSK) modulations in severe ICI environment. Simulation results over AWGN channel and multi-path fading channels with different ICI confirm the effectiveness of the proposed system.

This paper proposes a novel multi-carrier CDMA scheme, namely FD-CI/MC-CDMA (frequency division carrier interferometry multi-carrier code division multiple access), to combine the benefits of previously developed FD-MC-CDMA with CI/MC-CDMA together to provide higher BER performance in multipath fading channels. FD-MC-CDMA is capable of exploiting the available frequency diversity benefits in multipath fading channels while reducing MAI. Specifically, instead of transmitting all users' information bits over all carriers, FD-MC-CDMA employs a subset of non-contiguous carriers to support a subset of users (while maintaining the same overall system capacity and throughput as in MC-CDMA). However, since the length of Hadamard-Walsh codes only exists for certain integers, FD-MC-CDMA lacks the flexibility to accurately divide all subcarriers into subsets according to the channel condition. On the other hand, CI/MC-CDMA offers good BER performance while providing any length of orthogonal spreading codes. By combining these two systems together, the proposed FD-CI/MC-CDMA system significantly outperforms FD-MC-CDMA (as well as MC-CDMA) in multipath fading channel at similar complexity.

In this paper, we present a software defined radio (SDR) based cognitive radio implementation and demonstration. Using GNU Radio and USRP SDR boards, we implement and demonstrate a cognitive radio that detects spectrum holes in the FM band and exploits the available spectrum holes to transmit digital and analog data without interfering the existing FM transmission. Moreover, we demonstrate that when a primary user's transmission starts over the original spectrum holes, the cognitive radio automatically adapts its transmission to avoid interference to the newly coming primary user. Additionally, we have implemented and demonstrated a frequency hopping over multiple spectrum holes to support multiple secondary users with minimum interference to each other.

MC-CDMA (multiple carrier code division multiple access) has been considered a strong candidate for cognitive radio and dynamic spectrum access network, due to its high spectral efficiency, easy implementation and the capability of operating over non-contiguous frequency bands. However, like other multi-carrier transmission technologies such as OFDM (orthogonal frequency division multiplexing), the orthogonality among subcarriers in MC-CDMA system is lost in a mobile environment, leading to inter-carrier interference (ICI) and performance degradation. In this paper, we apply the ICI self-cancellation scheme previously proposed for OFDM system to orthogonal MC-CDMA system with Hadamard-Walsh codes to diminish ICI and improve BER performance. We show that the ICI self-cancellation scheme for MC-CDMA is equivalent to employing a subset of the Hadamard code matrix. As a direct result, the proposed ICI self cancellation method does not increase the complexity at both transmitter and receiver. To compensate for the network capacity (in terms of the number of users) loss in the proposed ICI self-cancellation method, a second set of orthogonal Hadamard-Walsh codes on the quadrature subcarriers are introduced. The proposed system offers significant BER performance gain than original MC-CDMA with the presence of ICI and same network capacity when BPSK modulation is employed. Simulation results over multi-path fading channel confirm the effectiveness of the proposed scheme, without increasing any complexity.

Sums of lognormal random variables occur in many important problems in wireless communications. However, the lognormal sum distribution is known to have no close-form and is difficult to compute numerically. Several approximation methods have already been proposed to approximate the lognormal sum distribution. However, these approximation methods all have their drawbacks: some widely used approximation methods are not very accurate at the lower region, some other approximation methods require the CDF curve from Monte Carlo simulation first. In this paper, we propose a novel approximation method, namely the Log Skew Normal (LSN) approximation, to model and approximate the sum of M lognormal distributed random variables. The proposed LSN approximation method has very high accuracy in most of the region, especially in the lower region. Furthermore, this approximation method does not require the CDF curve from Monte Carlo simulation first. The closed-form probability density function (PDF) of the resulting LSN random variable is presented and its parameters are derived from those of the M individual lognormal random variables by using an moment matching technique. Simulation results on the cumulative distribution function (CDF) of sum of M lognormal random variables in different conditions are used as reference curves to compare various approximation techniques. LSN approximation is found to provide better accuracy over a wide CDF range over other approximation methods.

Recent studies suggest that spectrum congestion is primarily due to inefficient spectrum usage rather than spectrum availability. Dynamic spectrum access (DSA) and cognitive radio (CR) are two techniques being considered to improve spectrum efficiency and utilization. The advent of CR has created a paradigm shift in wireless communications and instigated a change in FCC policy towards spectrum regulations. Within the hierarchical DSA model, spectrum overlay and underlay techniques are employed to enable primary and secondary users to coexist while improving overall spectrum efficiency. As employed here, spectrum overlay exploits unused (white) spectral regions while spectrum underlay exploits underused (gray) spectral regions. In general, underlay approaches use more spectrum than overlay approaches and operate below the noise floor of primary users. Spectrally modulated, spectrally encoded (SMSE) signals, to include orthogonal frequency domain multiplexing (OFDM) and multi-carrier code division multiple access (MC-CDMA), are candidate CR waveforms. The SMSE structure supports and is well suited for CR-based software defined radio (SDR) applications. This paper provides a general soft decision SMSE (SDSMSE) framework that extends the original SMSE framework to achieve synergistic CR benefits of overlay and underlay techniques. This extended framework provides considerable flexibility to design overlay, underlay and hybrid overlay/underlay waveforms that are scenario dependent. Overlay/underlay framework flexibility is demonstrated herein for a family of SMSE signals, including OFDM and MC-CDMA. Analytic derivation of CR error probability for overlay and underlay applications is presented. Simulated performance analysis of overlay, underlay and hybrid overlay/underlay waveforms is also presented and benefits discussed, to include improved spectrum efficiency and channel capacity maximization. Performance analysis of overlay/underlay CR waveform in fading channels will be discussed in Part II of the paper.