9,033 research outputs found
Energy efficiency-spectral efficiency trade-off of transmit antenna selection
We investigate the energy efficiency-spectral efficiency (EE-SE) trade-off of transmit antenna selection/maximum ratio combining (TAS) scheme. A realistic power consumption model (PCM) is considered, and it is shown that using TAS can provide significant energy savings when compared to multiple-input multiple-output (MIMO) in the low to medium SE region, regardless the number of antennas, as well as outperform transmit beamforming scheme (MRT) for the entire SE range. For a fixed number of receive antennas, our results also show that the EE gain of TAS over MIMO becomes even greater as the number of transmit antennas increases. The optimal value of SE that maximizes the EE is obtained analytically, and confirmed by numerical results. Moreover, the influence of receiver correlation is also evaluated and it is shown that considering a non-realistic PCM can lead to mistakes when comparing TAS and MIMO
Energy Efficiency-Spectral Efficiency Trade-Off of Transmit Antenna Selection
We investigate the energy efficiency-spectral efficiency (EE-SE) trade-off of transmit antenna selection/maximum ratio combining (TAS) scheme. A realistic power consumption model (PCM) is considered, and it is shown that using TAS can provide significant energy savings when compared to multiple-input multiple-output (MIMO) in the low to medium SE region, regardless the number of antennas, as well as outperform transmit beamforming scheme (MRT) for the entire SE range. For a fixed number of receive antennas, our results also show that the EE gain of TAS over MIMO becomes even greater as the number of transmit antennas increases. The optimal value of SE that maximizes the EE is obtained analytically, and confirmed by numerical results. Moreover, the influence of receiver correlation is also evaluated and it is shown that considering a non-realistic PCM can lead to mistakes when comparing TAS and MIMO
On the Area Energy Efficiency of Multiple Transmit Antenna Small Base Stations
We analyze the area energy efficiency (AEE) of
spatial multiplexing (SM) and transmit antenna selection (TAS),
considering a realistic power consumption model for small base
stations (BSs), which includes the power consumed by the
backhaul as well as different interference attenuation levels. Our
results show an optimum number of BSs for each technique that
maximizes the AEE. Moreover, we also show that TAS has a
larger AEE than SM when the demand for system capacity is
low, while SM becomes more energy efficient when the demanded
capacity is larger. Additionally, when the capacity demand and
the area to be covered are fixed, the number of BSs needed to
be deployed is smaller for SM than for the other techniques.
Finally, the system performance in terms of AEE is shown to be
strongly dependent on the amount of interference, which in turn
depends on the employed interference-mitigation scheme, and on
the employed power consumption model
Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks
The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter
Employing Antenna Selection to Improve Energy-Efficiency in Massive MIMO Systems
Massive MIMO systems promise high data rates by employing large number of
antennas, which also increases the power usage of the system as a consequence.
This creates an optimization problem which specifies how many antennas the
system should employ in order to operate with maximal energy efficiency. Our
main goal is to consider a base station with a fixed number of antennas, such
that the system can operate with a smaller subset of antennas according to the
number of active user terminals, which may vary over time. Thus, in this paper
we propose an antenna selection algorithm which selects the best antennas
according to the better channel conditions with respect to the users, aiming at
improving the overall energy efficiency. Then, due to the complexity of the
mathematical formulation, a tight approximation for the consumed power is
presented, using the Wishart theorem, and it is used to find a deterministic
formulation for the energy efficiency. Simulation results show that the
approximation is quite tight and that there is significant improvement in terms
of energy efficiency when antenna selection is employed.Comment: To appear in Transactions on Emerging Telecommunications
Technologies, 12 pages, 8 figures, 2 table
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