Dimitrie C. Popescu

Enhancing VANET Performance by Joint Adaptation of Transmission Power and Contention Window Size

In this paper, we present a new scheme for dynamic adaptation of transmission power and contention window (CW) size to enhance performance of information dissemination in Vehicular Ad-hoc Networks (VANETs). The proposed scheme incorporates the Enhanced Distributed Channel Access (EDCA) mechanism of 802.11e and uses a joint approach to adapt transmission power at the physical (PHY) layer and quality-of-service (QoS) parameters at the medium access control (MAC) layer. In our scheme, transmission power is adapted based on the estimated local vehicle density to change the transmission range dynamically, while the CW size is adapted according to the instantaneous collision rate to enable service differentiation. In the interest of promoting timely propagation of information, VANET advisories are prioritized according to their urgency and the EDCA mechanism is employed for their dissemination. The performance of the proposed joint adaptation scheme was evaluated using the ns-2 simulator with added EDCA support. Extensive simulations have demonstrated that our scheme features significantly better throughput and lower average end-to-end delay compared with a similar scheme with static parameters.

On the likelihood-based approach to modulation classification

In this paper, likelihood-based algorithms are explored for linear digital modulation classification. Hybrid likelihood ratio test (HLRT)- and quasi HLRT (QHLRT)- based algorithms are examined, with signal amplitude, phase, and noise power as unknown parameters. The algorithm complexity is first investigated, and findings show that the HLRT suffers from very high complexity, whereas the QHLRT provides a reasonable solution. An upper bound on the performance of QHLRT-based algorithms, which employ unbiased and normally distributed non-data aided estimates of the unknown parameters, is proposed. This is referred to as the QHLRT-Upper Bound (QHLRT-UB). Classification of binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals is presented as a case study. The Cramer-Rao Lower Bounds (CRBs) of non-data aided joint estimates of signal amplitude and phase, and noise power are derived for BPSK and QPSK signals, and further employed to obtain the QHLRT-UB. An upper bound on classification performance of any likelihood-based algorithms is also introduced. Method-of-moments (MoM) estimates of the unknown parameters are investigated and used to develop the QHLRT-based algorithm. Classification performance of this algorithm is compared with the upper bounds, as well as with the quasi Log-Likelihood Ratio (qLLR) and fourth-order cumulant based algorithms.

Second-Order Cyclostationarity of Mobile WiMAX and LTE OFDM Signals and Application to Spectrum Awareness in Cognitive Radio Systems

Spectrum sensing and awareness are challenging requirements in cognitive radio (CR). To adequately adapt to the changing radio environment, it is necessary for the CR to detect the presence and classify the on-the-air signals. The wireless industry has shown great interest in orthogonal frequency division multiplexing (OFDM) technology. Hence, classification of OFDM signals has been intensively researched recently. Generic signals have been mainly considered, and there is a need to investigate OFDM standard signals, and their specific discriminating features for classification. In this paper, realistic and comprehensive mathematical models of the OFDM-based mobile Worldwide Interoperability for Microwave Access (WiMAX) and third-Generation Partnership Project Long Term Evolution (3GPP LTE) signals are developed, and their second-order cyclostationarity is studied. Closed-from expressions for the cyclic autocorrelation function (CAF) and cycle frequencies (CFs) of both signal types are derived, based on which an algorithm is proposed for their classification. The proposed algorithm does not require carrier, waveform, and symbol timing recovery, and is immune to phase, frequency, and timing offsets. The classification performance of the algorithm is investigated versus signal-to-noise ratio (SNR), for diverse observation intervals and channel conditions. In addition, the computational complexity is explored versus the signal type. Simulation results show the efficiency of the algorithm is terms of classification performance, and the complexity study proves the real time applicability of the algorithm.

A game-theoretic approach to joint rate and power control for uplink CDMA communications

Next generation wireless systems will be required to support heterogeneous services with different transmission rates that include real time multimedia transmissions, as well as non-real time data transmissions. In order to provide such flexible transmission rates, efficient use of system resources in next generation systems will require control of both data transmission rate and power for mobile terminals. In this paper we formulate the problem of joint transmission rate and power control for the uplink of a single cell CDMA system as a non-cooperative game. We assume that the utility function depends on both transmission rates and powers and show the existence of Nash equilibrium in the non-cooperative joint transmission rate and power control game (NRPG). We include numerical results obtained from simulations that compare the proposed algorithm with a similar one which is also based on game theory and it also updates the transmission rates and powers simultaneously in a single step.

Dynamic Adaptation of Joint Transmission Power and Contention Window in VANET

In this paper, we propose an algorithm for joint adaptation of transmission power and contention window to improve the performance of vehicular network in a cross layer approach. The high mobility of vehicles in vehicular communica- tion results in the change in topology of the Vehicular Ad-hoc Network (VANET) dynamically, and the communication link between two vehicles might remain active only for short duration of time. In order for VANET to make a connection for long time and to mitigate adverse effects due to high and fixed transmission power, the proposed algorithm adapts transmission power dynamically based on estimated local traffic density. In addition to that, the prioritization of messages according to their urgency is performed for timely propagation of high priority messages to the destination region. In this paper, we incorporate the contention based MAC protocol 802.11e enhanced distributed channel access (EDCA) mechanism to implement a priority- based vehicle-to-vehicle (V2V) communication. Simulation results show that the proposed algorithm is successful in getting better throughput with lower average end-to-end delay than the algorithm with static/default parameters.

Simultaneous Water Filling in Mutually Interfering Systems

In this paper we investigate properties of simultaneous water filling for a wireless system with two mutually interfering transmitters and receivers with non-cooperative coding strategies. This is slightly different from the traditional interference channel problem which assumes that transmitters cooperate in their respective coding strategies, and that interference cancellation can be performed at the receivers. In this noncooperative setup, greedy capacity optimization by individual transmitters through various algorithms leads to simultaneous water filling fixed points where the spectrum of the transmit covariance matrix of one user water fills over the spectrum of its corresponding interference-plus-noise covariance matrix, and in our paper we study the properties of these fixed points. We show that at a simultaneous water filling point the eigenvectors of transmit covariance matrices at each receiver are aligned, and identify three regimes which correspond to simultaneous water filling that depend on the interference gains: a) complete spectral overlap, b) partial spectral overlap, and c) spectral segregation. These imply that the transmit covariance matrices will be white in regions of both overlap and segregation, but not necessarily white overall. We also consider performance as a function of interference gain and show that complete spectral overlap is a strongly suboptimal solution over a wide range of gains. Overall, our results suggest that for strong mutual interference, an effort should be made to do joint decoding over receivers since such collaboration can provide large capacity increases. For moderate interference, distributed and/or centralized conflict resolution algorithms would be most effective since more complex collaborative methods do not afford much improvement and strictly greedy methods such as water filling perform poorly, while for weak interference a laissez faire approach seems reasonable

Adaptive Interference Avoidance for Dynamic Wireless Systems: A Game Theoretic Approach

In this paper, we present an adaptive algorithm for interference avoidance, which can be applied in a distributed manner by active users in a CDMA wireless system to obtain optimal codewords and powers for specified target signal-to-interference plus noise ratio (SINR). The algorithm is derived using a game-theoretic approach in which separable cost functions with respect to codeword and power are defined, and joint codeword and power adaptation is formulated as a separable game with two corresponding subgames: the noncooperative codeword adaptation game, and the noncooperative power control game. Codeword and power adaptation use incremental updates in the direction of the best strategy, which are desirable in practical implementations since they allow the receiver to follow transmitter changes with corresponding incremental changes of the receiver filter and continue detection of transmitted symbols with high accuracy. The algorithm can also track variable target SINRs or variable number of active users in the system, and is therefore useful for dynamic wireless systems with varying quality of service (QoS) requirements. We illustrate the proposed algorithm with numerical examples obtained from simulations that show convergence and tracking properties of the algorithm for different scenarios

Kalman filtering of colored noise for speech enhancement

A method for applying Kalman filtering to speech signals corrupted by colored noise is presented. Both speech and colored noise are modeled as autoregressive (AR) processes using speech and silence regions determined by an automatic end-point detector. Due to the non-stationary nature of the speech signal, non-stationary Kalman filter is used. Experiments indicate that non-stationary Kalman filtering outperforms the stationary case, the average SNR improvement increasing from 0.53 dB to 2.3 dB. Even better results are obtained if noise is considered also non-stationary, in addition to being colored, achieving an average of 7.14 dB SNR improvement.

Narrowband Interference Avoidance in OFDM-Based UWB Communication Systems

In this letter we present a new method for mitigating narrowband interference in orthogonal frequency-division multiplexing-based ultra-wideband communication systems. The proposed narrowband interference avoidance (NBIA) method performs spectral shaping of the transmitted signal using binary signature sequences with minimum total squared correlation (TSC) to avoid the narrowband interfering signal. We illustrate the proposed method with plots that show the spectrum of the transmitted signal with and without NBIA, and also present numerical results obtained from simulations showing improvement in the bit error rate (BER) performance of the system when NBIA is employed.

Cyclostationarity-Based Detection of LTE OFDM Signals for Cognitive Radio Systems

In this paper, a distinctive cyclostationarity-based feature of the Long Term Evolution (LTE) Orthogonal Frequency Division Multiplexing (OFDM) signals used in the Frequency Division Duplex (FDD) downlink transmission is proved, and further employed for their detection. This relates to the existence of the reference signals (RSs) used for channel estimation and cell search/ acquisition purposes. The analytical closed form expressions for the RS-induced cyclic autocorrelation function (CAF) and cyclic frequencies (CFs) are derived. Based on these findings, a signal detection algorithm is then developed. Simulation results show that the proposed algorithm achieves a good detection performance for low signal-to-noise ratios (SNRs), short sensing times, and under diverse channel conditions.