Erik Axell

Optimal Power Allocation for Parallel Two-State Gaussian Mixture Impulse Noise Channels

We consider power allocation on a set of independent parallel channels affected by additive impulse noise, which is modeled by a two-state Gaussian mixture interference model. We derive the optimal power allocation that maximizes the total capacity subject to a total power constraint. Moreover, we show that the well known water filling solution, which is optimal for Gaussian noise, is not the optimal power allocation for impulse interference. We also consider channel selection, i.e., to allocate all of the available power to a single channel, and show that the capacity is not necessarily maximized by the channel with the highest SNR in general.

Military HF communications considering unintentional platform-generated electromagnetic interference

High Frequency (HF) communications are of vital importance for modern military operations. It has the potential to move voice and data communications around the world by bouncing signals off the ionosphere, and at a fraction of the cost of heavily burdened satellite communication frequencies. However, HF-channels are touchy, unpredictable and prone to noise, fading, jamming and interference. Therefore, a number of prediction tools for channel selection have been developed. However, existing tools do not consider the local actual electromagnetic interference at receivers located on navy and army platforms. In this paper we propose a method to include this local electromagnetic interference in the frequency selection and we show how this method can improve the communication performance significantly. We also show that the consideration of local interference in combination with new wideband HF applications creates new challenges for power allocation and we show that the common water-filling solution is not always optimal with respect to data capacity in the system.

GNSS spoofing detection using multiple mobile COTS receivers

In this paper we deal with spoofing detection in GNSS receivers. We derive the optimal genie detector when the true positions are perfectly known, and the observation errors are Gaussian, as a benchmark for other detectors. The system model considers three dimensional positions, and includes correlated errors. In addition, we propose several detectors that do not need any position knowledge, that outperform recently proposed detectors in many interesting cases.

Online classification of Class A impulse interference

Electromagnetic interference can cause severe performance degradation on wireless communication systems. In modern military platforms there are many closely located electronic systems, which could potentially cause interference. The performance degradation is largely affected by the characteristics of the interference. With knowledge of the actual interference environment, radio receivers can be adapted to interference characteristics, and thereby providing greatly improved performance. In this work we propose a method for online classification of the interference while receiving an unknown communication signal. Thus, there is no need to interrupt the communication for sensing the environment. The proposed method is evaluated with Monte Carlo simulations, and shown to perform well. Simulations show that the proposed online classification method perform close to the offline optimal classifier at low and high SNR, and just slightly worse at medium SNR (close to 0 dB). The proposed classification method can be used in many applications, such as adaptive demodulation and error correction, dynamic frequency selection and power allocation, and detection and identification of different kinds of interference sources or jamming equipment.

Power Control in Interference Channels With Class A Impulse Noise

In this letter, we consider optimal power allocation, with respect to sum capacity, for an interference channel affected by additive independent Class A impulse noise. The probability distribution of the sum of a Gaussian and a Class A distributed variable is derived, and the result is exploited to derive the sum capacity of an interference channel with independent Class A distributed impulse noise. Moreover, we show that the optimal power allocation strategy for the Class A interference channel can differ significantly from the solution to the commonly used additive white Gaussian noise interference channel.

Mitigation of multiple impulse noise sources through selective attenuation

On modern military platforms, there are many electronic systems that can cause interference to other. In order to mitigate the performance degradation this cosite interference might cause, attenuation of the received power from the interference sources is needed. In this work, we propose simple methods to select appropriate attenuation values for multiple impulse noise sources. The methods are based on approximations of the total bit error probability (BEP), in order to determine the impact from each individual source on the total system performance. Different methods for approximating the resulting BEP, and thereafter selecting the appropriate attenuations, are proposed based on different levels of knowledge of the individual interference signals. Either the BEP as a function of receive SIR or the impulsiveness correction factors (ICFs) and average powers are assumed to be known for each individual interference signal. The proposed methods are evaluated numerically and perform well in different scenarios.

Mitigation of co-channel interference by transmit power control

Interference in the vicinity of a receiving radio system can cause serious degradation of the radio communication performance. This may even result in disruptions and lost calls. For a co-location scenario of several communication systems, the combination of output powers will affect the total Signal-to-Noise Ratio (SNR) for receivers involved. In this paper, we show the dependence between output power, antenna coupling, out-of-band characteristics and communication distance. We present results of how these parameters can be combined to guarantee that necessary interference requirements in terms of SNR are met. Furthermore, it is shown that under certain conditions, the maximum achievable SNR only depends on the physical geometry of the co-location scenario.