On the Physical Layer of Ultra-Wideband Systems
Licentiatavhandling, 2005
This licentiate thesis consists of two published conference papers, one
technical report, and an introduction. The focus is on communication at bit
rates of 100 Mbps and higher for single-user systems at short range up to 10
meters.Three physical layers are investigated that use impulse radio, orthogonal
frequency division multiplexing (OFDM), and carrier-based direct-sequence
spread-spectrum, respectively. All layers use coherent detection. In all papers,
the IEEE 802.15.3a channel model is used for the evaluation of the systems and
their performance.
In paper A, a comparison between direct-sequence impulse radio (DS-IR) and
time-hopping impulse radio (TH-IR) at 100 Mbps is presented. The performance of
suboptimal, fractionally spaced (FS), coherent Rake receivers with a
pulse-matched filter is numerically evaluated with two channel estimation
algorithms. TH-IR and DS-IR with antipodal modulation is shown to perform
basically the same. The FS-rake receiver performs much better than chip- and
symbol-spaced rake receivers.
In paper B, an amplitude autocovariance function of the Fourier transform of
channel impulse response is defined. A coherence bandwidth is obtained for every
channel impulse response with this autocovariance function. The standard
deviation of the coherence bandwidth is shown to be one third of the mean
coherence bandwidth. Numerical simulations show that the performance of a
multiband-OFDM system on the IEEE 802.15.3a channel model CM4 is close to the
truncated union bound of the performance of convolutional codes on uncorrelated
Rayleigh fading channels.
Paper C provides a set of physical layer specifications for a carrier-based
single-band direct-sequence spread-spectrum system so that the physical layer
requirements from IEEE 802.15.3a are fulfilled. Performance results are also
presented for a dual-band system that uses the same spectrum and sampling rate
as the single-band systems. A channel impulse response gain is defined. It is
shown that this gain, which is a random variable, can be approximated by the
multiplication of two other random variables that have a log-normal and a gamma
distribution, respectively.