The low power regime has attracted various researchers in the information theory and
communication communities to understand the performance limits of wireless systems. Indeed,
the energy consumption is becoming one of the major limiting factors in wireless
systems. As such, energy-efficient wireless systems are of major importance to the next
generation wireless systems designers. The capacity is a metric that measures the performance
limit of a wireless system. The study of the ergodic capacity of some fading channels
in the low power regime is the main subject of this thesis. In our study, we consider that the
receiver has always a full knowledge of the channel state information. However, we assume
that the transmitter has possibly imperfect knowledge of the channel state information, i.e.
he knows either perfectly the channel or only an estimated version of the channel. Both
radio frequency and free space optical communication channel models are considered.
The main contribution of this work is the explicit characterization of how the capacity
scales as function of the signal-to-noise ratio in the low power regime. This allows
us to characterize the gain due to the perfect knowledge compared to no knowledge of
the channel state information at the transmitter. In particular, we show that the gain increases
logarithmically for radio frequency communication. However, the gain increases
as log2(Pavg) or log4(Pavg) for free-space optical communication, where Pavg is the average
power constraint imposed to the input. Furthermore, we characterize the capacity of cascaded fading channels and we applied the result to Rayleigh-product fading channel and
to a free-space optical link over gamma-gamma atmospheric turbulence in the presence of
pointing errors. Finally, we study the capacity of Nakagami-m fading channel under quality
of service constraints, namely the effective capacity. We have shown that the effective
capacity converges to Shannon capacity in the very low power regime.
Date of Award | Jan 2013 |
---|
Original language | English (US) |
---|
Awarding Institution | - Computer, Electrical and Mathematical Sciences and Engineering
|
---|
Supervisor | Mohamed-Slim Alouini (Supervisor) |
---|
- Capacity
- Low Power
- Quality of Service
- Fading Channel