Alexandr M. Kuzminskiy

Re-configurable semi-blind cancellation of asynchronous interference with an antenna array

The antenna array asynchronous interference cancellation problem is addressed by means of semi-blind algorithms with projections to the finite alphabet. It has been observed that the conventional least squares (LS) solution estimated over the training interval may not be suitable for initialization of iterative semi-blind schemes in the case of asynchronous interference. Unlike the synchronous case, a modified LS initialization based on the autocorrelation matrix estimated over the whole burst of data outperforms the conventional LS initialization for the high interference level. We propose a re-configurable receiver which exploits on-line selection of the initialization. Its efficiency is demonstrated in TDMA and OFDM environments.

Adaptive second-order asynchronous CCI cancellation: maximum likelihood benchmark for regularized semi-blind technique

An asynchronous interference cancellation problem is addressed when training and working intervals are available, containing the desired signal and arbitrary overlapping interference. A likelihood ratio (LR) maximization approach is developed for estimation of the structured correlation matrices over both training and working intervals for the Gaussian data model and exploited to obtain a performance benchmark for ad-hoc estimators. A regularized non-iterative estimation of the antenna array coefficients is proposed, which employs the autocorrelation matrix estimation as a weighted sum of the autocorrelation matrices estimated over the training and working intervals. It is shown by means of simulation in TDMA and OFDM environments that the regularized semi-blind solution significantly outperforms the conventional estimators and demonstrates performance close to the LR based benchmark.

Decentralized dynamic spectrum allocation based on adaptive antenna array interference mitigation diversity: Algorithms and Markov chain analysis

Decentralized dynamic spectrum allocation (DSA) that exploit adaptive antenna array interference mitigation (IM) diversity at the receiver, is proposed for interference-limited environments with high level of frequency reuse. The system consists of base stations (BSs) that may belong to different providers, who can optimize uplink frequency allocation to their subscriber stations (SSs) to achieve the least impact of IM on the useful signal, assuming no control over band allocation of other BSs sharing the same bands. “Selfish” and “good neighbor” decentralized DSA strategies are considered. Convergence and convergence rate of the introduced techniques are investigated by means of the theory of absorbing Markov chains.

Downlink SDMA for legacy IEEE 802.11a/g mobile stations: acknowledgement recovery and channel estimation

We address the problem of downlink throughput improvement for IEEE 802.11a/g systems by using a modified access point (AP) equipped with multiple antennas. The main restriction is that standard terminals should not be modified in any way. An alternating time-offset space division multiple access (SDMA) solution is proposed to overcome restrictions imposed by the legacy terminals requirement. Simulations based on the IEEE 802.11 channel models demonstrate that a near doubling of downlink capacity can be achieved in a conference room environment.

Asynchronous interference cancellation with an antenna array

The antenna array asynchronous interference cancellation problem is addressed by means of semi-blind algorithms with projections to the finite alphabet. It is observed that the conventional least squares (LS) solution estimated over the training interval may not be suitable for initialization of the iterative semi-blind schemes in the case of asynchronous interference. The simulation results in an OFDM HIPERLAN/2 environment are presented, which demonstrate that, contradictory to the synchronous interference case, a modified LS initialization based on the autocorrelation matrix estimated over the whole burst of data outperforms the conventional LS initialization for high interference levels.

RF Fingerprint detection in a wireless multipath channel

An RF Fingerprint is a unique signature passively imbued on a signal as it passes through a radio transmitter. We present the first RF Fingerprint detection technique capable of excellent performance in the presence of multipath propagation and the absence of a constant frequency offset. Our algorithm differs from previous work by performing joint channel estimation and classification on a steady state signal. The technique may be applied to any radio system with a repeated symbol sequence — such as a preamble. Our laboratory demonstrator is capable of distinguishing between the preamble signal transmitted by Universal Mobile Telephone System (UMTS) user equipment. We report excellent results — in excess of 99 % for 20 different UMTS models in an indoor wireless environment.

Adaptive Antenna Array Interference Mitigation Diversity for Decentralized Dynamic Spectrum Allocation in License-Exempt Spectrum

Decentralized dynamic spectrum allocation (DSA) that exploit adaptive antenna array interference mitigation (IM) diversity at the receiver, is proposed for interference-limited environments with high level of frequency reuse. The system consists of base stations (BSs) that may belong to different providers in license-exempt spectrum, who can optimize uplink frequency allocation to their subscriber stations (SSs) to achieve the least impact of IM on the useful signal, assuming no control over band allocation of other BSs sharing the same bands. The IM-based DSA algorithms based on a good neighbor decentralized DSA strategies are proposed. The new strategy introduces controllable behavior of decentralized networks, which promises a practical perspective for IM-based DSA algorithms even without guarantee of the network convergence to stationary points.

Adaptive Asynchronous CCI Cancellation: Selection of the Regularization Parameter for Regularized Semi-Blind Technique

A asynchronous interference cancellation problem is addressed when training and working data intervals are available containing the desired signal and arbitrary overlapping interference. A regularized non-iterative semi-blind estimation of the antenna array coefficients is considered, which employs the autocorrelation matrix estimation as a weighted sum of the autocorrelation matrices estimated over the training and working data intervals. On-line selection of the regularization parameter is proposed. A simple switched selection algorithm is developed based on the constant modulus criterion. It is shown by means of simulations in TDMA and OFDM environments that the adaptive regularization parameter allows significant performance improvement compared to any fixed regularization parameter in a wide range of the asynchronous interference scenario parameters

Semi-blind symbol synchronization for antenna array signal processing in short burst multiuser SDMA systems

The problem of symbol synchronization for semi-blind antenna array signal processing in digital communications is considered. It is relevant to situations where the location of known training symbols within a slot of received data is not known. Training based and blind techniques have been employed to address this problem but they become ineffective when the length of the training sequence and/or the data received under quasi-stationary conditions is not sufficiently long. A more effective semi-blind solution is proposed in this paper. A synchronization algorithm is developed and compared with the known training-based algorithm by means of computer simulations. The testing and evaluation conditions correspond to those of short burst multiuser spatial division multiple access (SDMA) systems.

Non-stationary multiple-antenna interference cancellation for unsynchronized OFDM systems with distributed training

Adaptive interference cancellation is addressed in an orthogonal frequency division multiplexing (OFDM) system with a frame containing a number of temporally distributed pilot symbols, e.g., as in the IEEE 802.16-2004 standard. A nonstationary symbol-by-symbol switching technique based on banks of training-based and semi-blind estimators is analyzed by means of comparison with the conventional stationary pilot-based solution and with the nonasymptotic maximum likelihood benchmark especially developed for assessment of the proposed nonstationary interference cancellation algorithms.