858 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
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
Interference Efficiency: A New Metric to Analyze the Performance of Cognitive Radio Networks
In this paper, we develop and analyze a novel performance metric, called interference efficiency, which shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the interference efficiency of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power, total transmit power, and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP) that aims to maximize ergodic sum rate of SUs and to minimize average interference power on the primary receiver. We solve the MOP by first transferring it into a single objective problem (SOP) using a weighted sum method. Considering different scenarios in terms of channel state information (CSI) availability to the SU transmitter, we investigate the effect of CSI on the performance and power allocation of the SUs. When full CSI is available, the formulated SOP is nonconvex and is solved using augmented penalty method (also known as the method of multiplier). When only statistical information of the channel gains between the SU transmitters and the PU receiver is available, the SOP is solved using Lagrangian optimization. Numerical results are conducted to corroborate our theoretical analysis
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