1,465 research outputs found
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
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
Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks
In this correspondence, the comprehensive problem of joint power, rate, and
subcarrier allocation have been investigated for enhancing the spectral
efficiency of multi-user orthogonal frequency-division multiple access (OFDMA)
cognitive radio (CR) networks subject to satisfying total average transmission
power and aggregate interference constraints. We propose novel optimal radio
resource allocation (RRA) algorithms under different scenarios with
deterministic and probabilistic interference violation limits based on a
perfect and imperfect availability of cross-link channel state information
(CSI). In particular, we propose a probabilistic approach to mitigate the total
imposed interference on the primary service under imperfect cross-link CSI. A
closed-form mathematical formulation of the cumulative density function (cdf)
for the received signal-to-interference-plus-noise ratio (SINR) is formulated
to evaluate the resultant average spectral efficiency (ASE). Dual decomposition
is utilized to obtain sub-optimal solutions for the non-convex optimization
problems. Through simulation results, we investigate the achievable performance
and the impact of parameters uncertainty on the overall system performance.
Furthermore, we present that the developed RRA algorithms can considerably
improve the cognitive performance whilst abide the imposed power constraints.
In particular, the performance under imperfect cross-link CSI knowledge for the
proposed `probabilistic case' is compared to the conventional scenarios to show
the potential gain in employing this scheme
Error Rate Analysis of Cognitive Radio Transmissions with Imperfect Channel Sensing
This paper studies the symbol error rate performance of cognitive radio
transmissions in the presence of imperfect sensing decisions. Two different
transmission schemes, namely sensing-based spectrum sharing (SSS) and
opportunistic spectrum access (OSA), are considered. In both schemes, secondary
users first perform channel sensing, albeit with possible errors. In SSS,
depending on the sensing decisions, they adapt the transmission power level and
coexist with primary users in the channel. On the other hand, in OSA, secondary
users are allowed to transmit only when the primary user activity is not
detected. Initially, for both transmission schemes, general formulations for
the optimal decision rule and error probabilities are provided for arbitrary
modulation schemes under the assumptions that the receiver is equipped with the
sensing decision and perfect knowledge of the channel fading, and the primary
user's received faded signals at the secondary receiver has a Gaussian mixture
distribution. Subsequently, the general approach is specialized to rectangular
quadrature amplitude modulation (QAM). More specifically, optimal decision rule
is characterized for rectangular QAM, and closed-form expressions for the
average symbol error probability attained with the optimal detector are derived
under both transmit power and interference constraints. The effects of
imperfect channel sensing decisions, interference from the primary user and its
Gaussian mixture model, and the transmit power and interference constraints on
the error rate performance of cognitive transmissions are analyzed
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