Otilia Popescu

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

Sum capacity and TSC bounds in collaborative multibase wireless systems

We consider a wireless system with base stations which collaborate, and derive bounds on sum capacity and total squared correlation for uniform channels between users and bases. The correspondence also investigates structural properties which must be satisfied by user transmit covariance matrices at the optimal sum capacity/total squared correlation (TSC) point, and shows that for multibase systems, maximizing sum capacity and minimizing TSC are, in general, not equivalent problems.

Water filling may not good neighbors make

Consider a wireless system with multiple and independent user-base pairings over some region. Each user tries to greedily optimize its performance, and eventually a simultaneous water-filling fixed point is reached. Here we seek to analytically understand properties of different water-filling fixed points. In so doing we show that water-filling alone does not generally result in optimum resource sharing and in some cases is a poor solution. We close by suggesting dynamic strategies for performance enhancement.

Interference avoidance for multiaccess vector channels

Using a general signal space approach we show that sequential application of the eigen-algorithm for interference avoidance by all users in a CDMA system is equivalent to iterative water filling and always yields codeword ensembles that maximize the sum capacity of multiaccess vector channels.

Signal space partitioning versus simultaneous water filling for mutually interfering systems

We consider a communication system with multiple independent user-base pairings in a white Gaussian noise environment, and for which a simultaneous water filling condition is satisfied by users at their respective bases. We focus on the weak mutual interference case for which the simultaneous water filling solution is unique and corresponds to complete user overlap in signal space. We show that when users at other bases are treated as Gaussian noise, simple separation of users in signal space usually offers better performance than simultaneous water filling, and present a distributed algorithm which separates users in signal space.

Interference Avoidance and Multiaccess Vector Channels

In this paper we present application of interference avoidance in the context of a general multiple access vector channel model. We show that this monotonically increases sum capacity, and discuss algorithms for code division multiple access (CDMA) codeword optimization based on this procedure. A greedy interference avoidance algorithm for multiaccess vector channels is presented in the paper, for which we discuss convergence to a class of codeword ensembles that satisfy a simultaneous water filling solution and maximize sum capacity. Numerical results obtained from simulations that corroborate our analytical results are also presented.

Maximizing the determinant for a special class of block-partitioned matrices

An analytical solution is found for the maximum determinant of a block-partitioned class of matrices with constant trace for each block. As an immediate application of this result, the maximum determinant of a sum of Kronecker products is derived.

Interference Mitigation in Aeronautical Telemetry Systems using Kalman Filter

In this correspondence we present a new method for mitigating multipath and adjacent channel interference in aeronautical telemetry systems. The proposed method uses a linear equalizer that is derived using Kalman filtering theory, which has been used successfully for channel equalization for high-speed communication systems. We illustrate the proposed method with numerical examples obtained from simulations that show the improvement in bit error rate performance (BER) for two modulation schemes using (ARTM) tier-1 waveforms currently used in aeronautical telemetry systems.

Greedy SINR maximization in collaborative multibase wireless systems

We present a codeword adaptation algorithm for collaborative multibase wireless systems. The system is modeled with multiple inputs and multiple outputs (MIMO) in which information is transmitted using multicode CDMA, and codewords are adapted based on greedy maximization of the signal-to-interference-plus-noise ratio. The procedure monotonically increases the sum capacity and, when repeated iteratively for all codewords in the system, converges to a fixed point. Fixed-point properties and a connection with sum capacity maximization, along with a discussion of simulations that corroborate the basic analytic results, are included in the paper.

Interference avoidance versus iterative water filling in multiaccess vector channels

We present an analysis of the relationship between the application of greedy interference avoidance and that of iterative water filling for vector multiaccess channels. The two methods converge to fixed points with similar properties corresponding to maximum sum capacity. However, the former is used for optimizing CDMA codewords, whereas the latter is used for optimizing transmit covariance matrices. We present numerical results from simulations and make a parallel between the two procedures, discussing differences and similarities.