André Pollok

Symbol-wise beamforming for MIMO-OFDM transceivers in the presence of co-channel interference and spatial correlation

In MIMO-OFDM communications over channels subject to co-channel interference, beamforming (BF) is conventionally applied independently to all subcarriers. Whilst this approach maximises mutual information, it is highly computationally complex. Symbol-wise BF considerably reduces the complexity by carrying out BF in the time domain. In this paper, we generalise symbol-wise BF to take co-channel interference into account. Maximising the mutual information is infeasible in this case and instead, we propose a novel iterative algorithm that maximises the SINR before OFDM demodulation. Computer simulations show that the performance loss relative to subcarrier-wise BF reduces with decreasing frequency selectivity or increasing spatial correlation.

Multiple-input multiple-output options for 60 GHz line-of-sight channels

The 60 GHz band is an attractive candidate for wireless indoor communications as it offers a large amount of license free spectrum. Non-rich scattering situations, which commonly arise at 60 GHz due to the particular propagation conditions, result in relatively high spatial correlation. Spatial multiplexing, a widely considered concept for multiple-input multiple-output (MIMO) communications, can offer large capacity gains if the spatial correlation is low. In this paper, we demonstrate that spatial multiplexing (SM) in conjunction with polarisation diversity is a viable option for 60 GHz line-of- sight (LoS) channels. The performance of the proposed scheme, which uses two antenna elements with orthogonal polarisation at each end of the transmission link, is assessed in terms of capacity. It is then compared to an optimal MIMO beamforming scheme that uses two parallel and identical antennas per link end. Furthermore, the impact of antenna misalignment is investigated.

Distributed stochastic routing optimization using expander graph theory

In this paper, we propose a novel algorithm for distributed and decentralized stochastic routing to optimize the convergence rate and the resilience of routing. More precisely, the novelty of our method is the provision of a stochastic routing technique which greatly improves the spectral gap of the routing matrix, as compared to existing methods. We define a novel measure of effective expansion capability of a node, which we use to maximize the spectral gap of the stochastic routing matrix. Simulation results demonstrate that our proposed routing method significantly improves the convergence rate and resilience of routing compared to other existing methods.

Carrier phase and amplitude estimation for phase shift keying using pilots and data

We consider least squares estimators of carrier phase and amplitude from a noisy communications signal that contains both pilot signals, known to the receiver, and data signals, unknown to the receiver. We focus on signaling constellations that have symbols evenly distributed on the complex unit circle, i.e., M-ary phase shift keying. We show, under reasonably mild conditions on the distribution of the noise, that the least squares estimator of carrier phase is strongly consistent and asymptotically normally distributed. However, the amplitude estimator is asymptotically biased and converges to a positive real number that is a function of the true carrier amplitude, the noise distribution and the size of the constellation. This appears to be the first time that the statistical properties of a non-data-aided estimator for carrier amplitude have been analyzed theoretically. The results of Monte Carlo simulations are provided and these agree with the theoretical results.

Noncoherent least squares estimators of carrier phase and amplitude

We consider least squares estimators of carrier phase and amplitude from a noisy communications signal. We focus on signaling constellations that have symbols evenly distributed on the complex unit circle, i.e., M-ary phase shift keying. We show, under reasonably mild conditions on the distribution of the noise, that the least squares estimator of carrier phase is strongly consistent and asymptotically normally distributed. However, the amplitude estimator is not consistent, but converges to a positive real number that is a function of the true carrier amplitude, the noise distribution and the size of the constellation. The results of Monte Carlo simulations are provided and these corroborate the theoretical results.

Fault-tolerant stochastic routing for wireless sensor networks with unreliable links

Timely and reliable delivery of critical information is vital for military applications and disaster relief applications. Such applications rely on communications networks, which in practice operate via unreliable links. Improving the packet delivery ratio while reducing the end-to-end delay is a major challenge for stochastic routing in networks with unreliable communication links. In this paper, we propose a novel decentralized stochastic routing algorithm to improve the packet delivery ratio and end-to-end delay for wireless sensor networks (WSNs) with unreliable links. We introduce an evaluation framework based on discrete time absorbing Markov chains to evaluate the packet delivery ratio and end-to-end delay. Simulation results show that our proposed routing algorithm performs significantly better in terms of packet delivery ratio and end-to-end delay when compared to existing decentralized methods.

Fast communication: On the Cramér-Rao bound for polynomial phase signals

Polynomial-phase signals have applications including radar, sonar, biology, and radio communication. Of practical importance is the estimation of the parameters of a polynomial phase signal from a sequence of noisy observations. Assuming that the noise is additive and Gaussian, the direct evaluation of the Cramer-Rao lower bound for this estimation problem involves evaluating the inverse of a matrix. Computing this inverse is numerically difficult for polynomial phase signals of large order. By making use of a family of orthogonal polynomials, we derive formulae for the Cramer-Rao bounds that are numerically stable and easy to compute.

Simultaneous Symbol Timing and Frame Synchronization for Phase Shift Keying

We develop an estimator of time offset (or time-of-arrival) of a transmitted communications signal that contains both pilot symbols, known to the receiver, and data symbols, unknown to the receiver. We focus on signalling constellations that have symbols lying on the complex unit circle, such as M-ary phase shift keying (M-PSK). We describe an algorithm for computing the estimator that requires O(L log L) operations in the worst case, where L is the number of transmitted symbols. Our estimator integrates information from the pilot symbols more effectively than popular estimators from the literature that usually split estimation into two subproblems called symbol timing and frame synchronisation. Our estimator combines these subproblems into a single operation, that of estimating time offset. We hypothesise that our estimator will be statistically more accurate. Monte-Carlo simulations support this hypothesis.

Modified Cramér-Rao Bounds for Continuous-Phase Modulated Signals

We consider the estimation of signal amplitude, time offset, and the parameters of a polynomial-phase signal from a continuous-phase modulated (CPM) signal that contains both unknown data symbols and known pilot symbols. Transformation of the polynomial-phase signal into an orthogonal basis allows us to derive the modified Cramér-Rao bounds (MCRB) for the problem of vector-parameter estimation in closed form. Numerical results demonstrate that the achievable estimation accuracy significantly depends on the burst structure and highlight the need for properly designed pilot sequences. Since our bounds are easy to evaluate, they can aid the design of pilot and burst configuration for CPM systems.

A DHT precoded OFDM system with full diversity and low PAPR

The use of discrete Hartley transform (DHT) pre-coding was recently shown to achieve peak to average power (PAPR) reduction for OFDM. In this paper, we show that DHT precoding also achieves full diversity. We consider the sparse matrix formed by the combination of DHT and the discrete Fourier transform (DFT) and propose a receiver configuration that minimizes complexity. Furthermore, we present a detailed account of the system complexity to show that it is slightly more than uncoded conventional OFDM. Also, since this system saves the complexity required for achieving diversity gain and reducing the peak to average power (PAPR), it reduces the system complexity when the PAPR reduction and diversity techniques are taken into account for conventional OFDM. We analytically show that this system achieves full diversity and then verify it using simulation results. Simulations results also show that the system has a substantial improvement in bit error performance over conventional OFDM.