1,849 research outputs found
Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity under Fading Channels in Cognitive Radio Networks
This paper studies optimal bandwidth and power allocation in a cognitive
radio network where multiple secondary users (SUs) share the licensed spectrum
of a primary user (PU) under fading channels using the frequency division
multiple access scheme. The sum ergodic capacity of all the SUs is taken as the
performance metric of the network. Besides all combinations of the peak/average
transmit power constraints at the SUs and the peak/average interference power
constraint imposed by the PU, total bandwidth constraint of the licensed
spectrum is also taken into account. Optimal bandwidth allocation is derived in
closed-form for any given power allocation. The structures of optimal power
allocations are also derived under all possible combinations of the
aforementioned power constraints. These structures indicate the possible
numbers of users that transmit at nonzero power but below their corresponding
peak powers, and show that other users do not transmit or transmit at their
corresponding peak power. Based on these structures, efficient algorithms are
developed for finding the optimal power allocations.Comment: 28 pages, 6 figures, submitted to the IEEE Trans. Signal Processing
in June 201
On the Combined Effect of Directional Antennas and Imperfect Spectrum Sensing upon Ergodic Capacity of Cognitive Radio Systems
We consider a cognitive radio system, consisting of a primary transmitter
(PUtx), a primary receiver (PUrx), a secondary transmitter (SUtx), and a
secondary receiver (SUrx). The secondary users (SUs) are equipped with
steerable directional antennas. We assume the SUs and primary users (PUs)
coexist and the SUtx knows the geometry of network. We find the ergodic
capacity of the channel between SUtx and SUrx , and study how spectrum sensing
errors affect the capacity. In our system, the SUtx first senses the spectrum
and then transmits data at two power levels, according to the result of
sensing. The optimal SUtx transmit power levels and the optimal directions of
SUtx transmit antenna and SUrx receive antenna are obtained by maximizing the
ergodic capacity, subject to average transmit power and average interference
power constraints. To study the effect of fading channel, we considered three
scenarios: 1) when SUtx knows fading channels between SUtx and PUrx, PUtx and
SUrx, SUtx and SUrx, 2) when SUtx knows only the channel between SUtx and SUrx,
and statistics of the other two channels, and, 3) when SUtx only knows the
statistics of these three fading channels. For each scenario, we explore the
optimal SUtx transmit power levels and the optimal directions of SUtx and SUrx
antennas, such that the ergodic capacity is maximized, while the power
constraints are satisfied
Generalized Area Spectral Efficiency: An Effective Performance Metric for Green Wireless Communications
Area spectral efficiency (ASE) was introduced as a metric to quantify the
spectral utilization efficiency of cellular systems. Unlike other performance
metrics, ASE takes into account the spatial property of cellular systems. In
this paper, we generalize the concept of ASE to study arbitrary wireless
transmissions. Specifically, we introduce the notion of affected area to
characterize the spatial property of arbitrary wireless transmissions. Based on
the definition of affected area, we define the performance metric, generalized
area spectral efficiency (GASE), to quantify the spatial spectral utilization
efficiency as well as the greenness of wireless transmissions. After
illustrating its evaluation for point-to-point transmission, we analyze the
GASE performance of several different transmission scenarios, including
dual-hop relay transmission, three-node cooperative relay transmission and
underlay cognitive radio transmission. We derive closed-form expressions for
the GASE metric of each transmission scenario under Rayleigh fading environment
whenever possible. Through mathematical analysis and numerical examples, we
show that the GASE metric provides a new perspective on the design and
optimization of wireless transmissions, especially on the transmitting power
selection. We also show that introducing relay nodes can greatly improve the
spatial utilization efficiency of wireless systems. We illustrate that the GASE
metric can help optimize the deployment of underlay cognitive radio systems.Comment: 11 pages, 8 figures, accepted by TCo
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