Ayman Elezabi

Cognitive interference-minimizing code assignment for underlay CDMA networks in asynchronous multipath fading channels

We propose a secondary CDMA network that operates as an underlay for a primary CDMA network where the code assignment for the secondary network is done cognitively. A code assignment criterion that minimizes interference from primary users and existing secondary users is formulated. The primary user codes as well as bit boundaries are unknown to the secondary network. The problem is initially formulated as a constrained optimization problem. Exhaustive search has complexity that is exponential in the spreading factor. The constraints are therefore relaxed to obtain a near-optimal solution with a complexity that is linear in the spreading factor and performance very close to the exhaustive search method. We consider the different cases where the primary users are bit- and chip-synchronous, chip-synchronous but bit-asynchronous, and chip-asynchronous over multi-path fading channels. We propose a method for blind epoch acquisition by processing the covariance matrix of the received signal. In all cases the performance improvement of the interference-minimizing code assignment over random code assignment is significant reaching over 3 dB for coded systems.

Improved Viterbi decoder metrics for two-stage detectors in DS-CDMA

Modified branch metrics are proposed for single-user Viterbi decoders in two-stage detectors for convolutionally-encoded code-division multiple-access (CDMA) systems with random spreading sequences. The modifications are based on modeling the residual multiple-access interference (RMAI) after subtractive interference cancellation as conditionally Gaussian with time-dependent variance, where the conditioning is on the time-varying user crosscorrelations. A novel estimate of the variance of the total RMAI is presented, and used in the proposed branch metrics. Significant performance gains are demonstrated over the Euclidean branch metric of the standard Viterbi decoder.

Blind symbol rate estimation using autocorrelation and zero crossing detection

In this paper we introduce a new and simple method to estimate the symbol rate for single carrier systems of unknown modulation. The introduced technique detects the symbol rate from a continuous range of symbol rates, i.e. it does not assume a finite set of candidate symbol rates. The method does not require any knowledge about system parameters and is therefore totally blind. The method belongs to the family of autocorrelation-based symbol rate estimators, yet, unlike many such schemes, its performance is insensitive to the value of the roll-off factor. We then propose a simple method for frequency offset compensation also based on the autocorrelation function. The proposed estimator is implemented as part of a complete DVB-C [1] receiver and is verified using simulations and results in robust performance even at low SNR and high frequency offsets.

System parameter selection for asymmetric underlay CDMA networks with interference-minimizing code asssignment

We propose a framework for designing an underlay secondary CDMA network. The objective is to select the secondary systems bit rate and spreading factor that improve the secondary network throughput given a required bit error rate and an allowable transmit power level acceptable to the primary network. The selection scheme is applied to both the case of random code assignment and an interference-minimizing code assignment (IMCA) scheme. Our simulations reveal that the parameter selection for the system with interference-minimizing code assignment scheme leads to higher system throughput over that achieved with random code assignment. We also show that the IMCA scheme, unlike random code assignment, suffers negligible interference from adjacent bands in asynchronous channels.

Improved single-user decoder metrics for two-stage detectors in DS-CDMA

Among the advantages of subtractive interference cancellation (IC), or multistage detectors for CDMA (code-division multiple-access) systems is that they facilitate feedback between the multiuser detection and decoding stages in a CDMA receiver. We propose modified branch metrics for the single-user Viterbi decoders used in conjunction with two-stage detectors for CDMA systems with long (random) spreading sequences. The modifications are based on modeling the residual multiple-access interference (RMAI) as conditionally Gaussian with time-dependent variance where the conditioning is on the time-varying user cross-correlations. A novel estimate of the variance of the total RMAI is presented, and put to use in the modified branch metrics. Significant performance gains are demonstrated over the Euclidean branch metric of the standard Viterbi decoder, and further improvements are discussed.

Novel modified energy detection spectrum sensing technique for FM wireless microphone signals

Spectrum Sensing is an important functionality of Cognitive Radio (CR). Accuracy and speed of estimation are the key indicators to select the appropriate spectrum sensing technique. In this paper, we focus on spectrum sensing of narrowband wireless microphone (WM) signals using the modified periodogram and Welch method for different window types. It is well-known that the power of the WM signal is highly concentrated in the frequency domain, particularly under silence. Due to this property, spectrum sensing can be performed by what we call modified energy detection (MED) which applies of two techniques. First, a proposed window is used to reduce the height of the side-lobes or spectral leakage, which is called modified periodogram method. This increases the difference between the signal PSD peak and the noise level resulting in better detection. Second, Welchs method is used, which takes the average of the modified periodograms using overlapped windows that decreases the noise variance compared to single periodogram estimation. The performance of the proposed spectrum sensing technique is demonstrated by computer simulations.

Improved Turbo Decoding and Interference Cancellation for DS-CDMA with Random Spreading

Parallel interference cancellation (PIC) receivers for turbo-encoded direct-sequence code-division multiple-access (DS-CDMA) systems with random spreading are considered. The residual multiple-access interference (RMAI) that remains in each users signal after PIC is modeled as Gaussian with time- dependent variance conditioned on the user cross-correlations. An enhanced estimate of the conditional variance of the RMAI is used in the log-likelihood ratio (LLR) computation for the Turbo decoders of each user. Significant performance gains reaching 2 dB are demonstrated on the frequency non-selective Rayleigh fading channel over the conventional LLR which assumes that the RMAI is Gaussian with a fixed variance.

Adaptive Puncturing for Coded OFDMA Systems

A scheme is proposed for adaptively changing the code rate of coded OFDMA systems via changing the puncturing rate within a single codeword (SCW). In the proposed structure, the data is encoded with the lowest available code rate then it is divided among different resource blocks (tiles) where it is punctured adaptively based on some measure of the channel quality for each tile. The proposed scheme is compared against using multiple codewords (MCWs) where the transmitter divides the data over tiles and encodes them separately. We investigate two different adaptive modulation and coding (AMC) selection methods. The first is a recursive scheme that operates directly on the SNR whereas the second operates on the effective SNR value that is obtained using Mutual Information Effective SNR Mapping (MIESM). We then compare our scheme to Per-Frame Adaptation (PFA) where we fix the modulation and coding scheme (MCS) over a given frame. We show via simulations that when using the recursive rate selection method the SCW scheme significantly outperforms the MCWs and the PFA. It is also shown that applying the MIESM rate selection method, the PFA improves significantly, yet the SCW scheme is the best performer. We also introduce a novel interleaving method prior to puncturing that improves the performance for certain restricted adaptation mechanisms.

Robust Acquisition of Hybrid Direct Sequence-Slow Frequency Hopping Spread-Spectrum under Multi-Tone and Gaussian Interference in Fading Channels

This paper proposes new techniques for acquisition of hybrid DS-SFH spread-spectrum systems in the presence of partial-band interference in fading channels. The proposed techniques include differential detection followed by maximizing the circular cross correlation with a known PN sequence. This is extremely robust against tone interference. An interference rejection method is used to improve the performance for interference with high power and small bandwidth occupancy by detecting anomalies in metric amplitudes caused by peaked interference and eliminating such metrics from the decision process. Finally, an adaptive method is used to select the best processing for either Gaussian or tone interference. The performance of the proposed acquisition techniques are compared to the conventional FH acquisition technique in AWGN and fading channels and superior performance is demonstrated for narrowband Gaussian and multi-tone interference.

Joint estimation-detection of cyber attacks in smart grids: Bayesian and non-Bayesian formulations

Smart grid operations face a significant threat from the presence of cyber attacks or bad data that may contaminate the system observations. Therefore, in this paper, we are interested in introducing a new strategy for detecting the presence of bad data in smart grids and we also try to simultaneously estimate it in order to be able to separate the bad data from the system observations. We aim to obtain the attack free observations which reflect the true state of the smart grid. This can be done by defining a joint detection-estimation strategy based on Bayesian and non-Bayesian settings where the costs in general will be functions of the observation. We start with Bayes approach and derive the detector (which, in general, may not be a LRT) and then we set the problem by defining some maximum constraint under the null hypothesis based on the derived detector and minimize certain cost under the alternative hypothesis. Our results reveal that the proposed model is applicable on some cases that other models reported in previous works failed to deal with.