Thomas Hunziker

Optimal power adaptation for OFDM systems with ideal bit-interleaving and hard-decision decoding

We derive power adaptation strategies optimizing the error rates of broadband bit-interleaved coded OFDM systems performing hard-decisions after the demodulation and ideal interleaving. The adaptive subchannel power allocation is based on either perfect or outdated channel state information in a time-division duplex transmission. We find that for an average bit error rate level of 10/sup -6/ a gain of up to 4 dB can be achieved by the proposed adaptation in Rayleigh fading channels.

Bit and power loading procedures for OFDM systems with bit-interleaved coded modulation

We present adaptive power and bit loading schemes for a bit-interleaved coded OFDM system with perfect channel state information and square quadrature amplitude modulation constellations. In order to minimize the bit error rates at the output of the Viterbi decoder subject to bit rate and power constraints, an analytical expression for the bit error rate of a hard-decision device has to minimized with respect to the number of bits and the power assigned to the subcarrier channel. The prohibitive complexity of the optimum solution can be circumvented by a simple suboptimum two-step procedure where the bit and power loading parts are decoupled. It is shown by Monte Carlo simulations that for broadband systems with Rayleigh fading the loading procedures provides a SNR gain of up to 6 dB for an average bit error rate level of 10/sup -6/.

Optimal power loading for multiple-input single-output ofdm systems with bit-level interleaving

We derive a power loading procedure optimizing the bit-error rates of multiple-input single-output (MISO) bit-interleaved coded modulation (BICM) orthogonal frequency-division multiplexing (OFDM) systems performing hard-decisions at the receiver and ideal interleaving. The adaptive subcarrier power allocation is based on either perfect or outdated channel state information at the transmitter. The scheme has the same complexity as the one for the single transmit antenna case. For a standard BICM-OFDM system in Rayleigh fading, Monte Carlo simulations show that the relative signal-to-noise ratio gain by the adaptation is up to 4 dB at an average bit-error rate level of 10-66. The relative gain in MISO systems decreases to 1.05 dB for increasing the number of transmit antennas. The achievable gain decreases for decreasing cross-correlation of the outdated and the actual channel state

Iterative detection for multicarrier transmission employing time-frequency concentrated pulses

We consider multicarrier transmission schemes in which the elementary signal pulses relate to the elements of a Weyl-Heisenberg system, i.e., resulting from a prototype function shifted in time and frequency. The overlapping of the information-bearing signal parts at the output of doubly dispersive channels and the resulting interference are confined by utilizing a prototype function whose energy is concentrated in both time and frequency. We derive a symbol detector which first calculates a sufficient statistic for the unknown data symbols from the linearly combined output signals of a filter bank, and second, performs an iterative maximization of the likelihood function. The presented receiver takes full advantage of the confined pulse overlapping to limit the computational effort. An analysis of the computational complexity and bit-error rate performance of the iterative detection scheme is provided for wide-sense stationary uncorrelated scattering channels.

Optimal Frame Splitting for Downlink MIMO Channels With Distributed Antenna Arrays

A frame-splitting (FS) scheme is proposed to exploit spatial diversity in the downlink wireless transmission from a base station (BS) to a mobile station (MS) that has multiple receive antennas. The BS has multiple geographically distributed arrays, each consisting of multiple transmit antennas. The scenario comprises a number of downlink multiple-input-multiple-output (MIMO) channels from different BS arrays to an MS with mutually independent Rayleigh-fading processes. A data frame from the BS for the MS is split into portions, which are consecutively transmitted from multiple BS arrays. For the FS transmission scheme, the distribution of information capacity is formulated on the basis of the FS fractional lengths of the portions. Analytical evaluation of the outage probability reveals the optimal setting of FS fractional lengths for the maximum diversity advantage based on knowledge of the long-term average signal-to-noise ratios (SNRs) of the downlink MIMO channels.

Feedback-aided selective subspace retransmission for outage-free spatial multiplexing

We study a novel spatial multiplexing scheme for a multiple-input/multiple-output (MIMO) architecture with vertical coding and a feedback channel. Rather than for sending back channel state information (CSI), the feedback channel is used to request the retransmission of signal parts in critical signal subspaces. This enables the receiver to perform linear reconstruction of the layered signals without the destructive noise enhancement in ill-conditioned channel matrices that is experienced with conventional linear processors. Moreover, a given target signal-to-noise ratio at the decoder input can be ensured. A comparison against standard MIMO architectures in terms of achievable throughput lets us conclude that the proposed multiplexing facilitates an advantageous closed-loop MIMO system which does not rely on accurate transmitter-side CSI.

Iterative symbol detection for bandwidth efficient nonorthogonal multicarrier transmission

We consider a general, bandwidth efficient multicarrier transmission scheme without guard periods. Intersymbol and interchannel interferences are limited by using nonorthogonal pulses with good time-frequency localization characteristics, i.e., concentration of the energy in both time and frequency domains. This lets us derive a receiver of moderate complexity, employing iterative methods for the symbol detection. The achievable performance with the transmission and detection scheme is assessed by means of computer simulations and compared against the theoretical error rate of a corresponding interference-free transmission.

Optimized paraunitary filter banks for time-frequency channel diagonalization

We adopt the concept of channel diagonalization to time-frequency signal expansions obtained by DFT filter banks. As a generalization of the frequency domain channel representation used by conventional orthogonal frequency-division multiplexing receivers, the time-frequency domain channel diagonalization can be applied to time-variant channels and aperiodic signals. An inherent error in the case of doubly dispersive channels can be limited by choosing adequate windows underlying the filter banks. We derive a formula for the mean-squared sample error in the case of wide-sense stationary uncorrelated scattering (WSSUS) channels, which serves as objective function in the window optimization. Furthermore, an enhanced scheme for the parameterization of tight Gabor frames enables us to constrain the window in order to define paraunitary filter banks. We show that the design of windows optimized for WSSUS channels with known statistical properties can be formulated as a convex optimization problem. The performance of the resulting windows is investigated under different channel conditions, for different oversampling factors, and compared against the performance of alternative windows. Finally, a generic matched filter receiver incorporating the proposed channel diagonalization is discussed which may be essential for future reconfigurable radio systems.

On the ergodic performance of a simple closed-loop spatial multiplexing architecture

We investigate a closed-loop spatial multiplexing architecture with linear array signal processing, which can be combined with off-the-shelf single-input single-output encoders/decoders. Rather than resorting to sophisticated interference cancellation schemes, excessive noise amplification due to ill-conditioned multiple-input multiple-output (MIMO) channels is evaded by retransmission of signal parts in critical subspaces, facilitated by a low-rate feedback channel. This lets the great capacities of MIMO channels be capitalized on with low system complexity, without requiring channel state information at the transmitter end. The closed-loop architecture involves a reverse propagation of the noise power, which we study using the theory of Markov chains. Conditions are defined under which stationarity is attained, considering both infinite and finite-rate feedback, and the constrained ergodic capacity of the system is expressed. It turns out that in the case of an (8 times 8) MIMO channel with uncorrelated Rayleigh fading, the constrained capacity comes as close as 4 dB to the unconstrained ergodic MIMO capacity.

Spectrum sensing in cognitive radios: Design of DFT filter banks achieving maximal time-frequency resolution

Filter banks facilitate an estimation of the power spectral density of broad-band non-stationary signals, an operation required in many cognitive radio systems. The samples at the filter bank output may serve as a basis for an estimation of the input signal energy within any time-frequency (TF) region of interest. In order to achieve a high resolution in both time and frequency, the prototype window underlying a Discrete Fourier Transform (DFT) filter bank needs to exhibit high TF concentration. Moreover, in order to provide uncorrelated samples in case of white input processes, the TF-translated versions of the prototype window that underlie the elementary filtering operations need to constitute an orthogonal set. In this paper we present a technique to design DFT filter banks that possess these two required properties in an optimal manner. The numerical optimization procedure takes advantage of a parametrization of paraunitary filter banks and relies on semidefinite programming. We analyze the residual leakage of our optimized filter banks and draw a comparison against Thomsons multitaper method.