Abstract :
We develop an energy-efficient resourceallocation scheme with proportional fairness for downlink
multiuser orthogonal frequency-division multiplexing
(OFDM) systems with distributed antennas. Our aim is to
maximize energy efficiency (EE) under the constraints of
the overall transmit power of each remote access unit
(RAU), proportional fairness data rates, and bit error rates
(BERs). Because of the non convex nature of the
optimization problem, obtaining the optimal solution is
extremely computationally complex. Therefore, we
develop a low-complexity suboptimal algorithm, which
separates subcarrier allocation and power allocation. For
the low-complexity algorithm, we first allocate subcarriers
by assuming equal power distribution. Then, by exploiting
the properties of fractional programming, we transform the
non convex optimization problem in fractional form into an
equivalent optimization problem in subtractive form, which
includes a tractable solution. Next, an optimal energyefficient power-allocation algorithm is developed to
maximize EE while maintaining proportional fairness.
Through computer simulation, we demonstrate the
effectiveness of the proposed low-complexity algorithm
and illustrate the fundamental tradeoff between energy and
spectral-efficient transmission designs.
Keyword :
Distributed Antenna System (DAS), Energy Efficiency (EE), Fractional Programming, Proportional Fairness, Resource Allocation, Spectral Efficiency (SE).