2,051 research outputs found
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
Energy Efficient Coordinated Beamforming for Multi-cell MISO Systems
In this paper, we investigate the optimal energy efficient coordinated
beamforming in multi-cell multiple-input single-output (MISO) systems with
multiple-antenna base stations (BS) and single-antenna mobile stations
(MS), where each BS sends information to its own intended MS with cooperatively
designed transmit beamforming. We assume single user detection at the MS by
treating the interference as noise. By taking into account a realistic power
model at the BS, we characterize the Pareto boundary of the achievable energy
efficiency (EE) region of the links, where the EE of each link is defined
as the achievable data rate at the MS divided by the total power consumption at
the BS. Since the EE of each link is non-cancave (which is a non-concave
function over an affine function), characterizing this boundary is difficult.
To meet this challenge, we relate this multi-cell MISO system to cognitive
radio (CR) MISO channels by applying the concept of interference temperature
(IT), and accordingly transform the EE boundary characterization problem into a
set of fractional concave programming problems. Then, we apply the fractional
concave programming technique to solve these fractional concave problems, and
correspondingly give a parametrization for the EE boundary in terms of IT
levels. Based on this characterization, we further present a decentralized
algorithm to implement the multi-cell coordinated beamforming, which is shown
by simulations to achieve the EE Pareto boundary.Comment: 6 pages, 2 figures, to be presented in IEEE GLOBECOM 201
Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments
In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered at the IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case with ideal hardware. Moreover, the performance degradation at high SNR is shown to be mainly affected by the AP hardware impairments rather than by the phase noise at the IRS. We further obtain in closed form the optimal transmit power for energy efficiency maximization. Simulation results are provided to verify the obtained results
Energy-Efficient Coordinated Multi-Cell Multigroup Multicast Beamforming with Antenna Selection
This paper studies energy-efficient coordinated beamforming in multi-cell
multi-user multigroup multicast multiple-input single-output systems. We aim at
maximizing the network energy efficiency by taking into account the fact that
some of the radio frequency chains can be switched off in order to save power.
We consider the antenna specific maximum power constraints to avoid non-linear
distortion in power amplifiers and user-specific quality of service (QoS)
constraints to guarantee a certain QoS levels. We first introduce binary
antenna selection variables and use the perspective formulation to model the
relation between them and the beamformers. Subsequently, we propose a new
formulation which reduces the feasible set of the continuous relaxation,
resulting in better performance compared to the original perspective
formulation based problem. However, the resulting optimization problem is a
mixed-Boolean non-convex fractional program, which is difficult to solve. We
follow the standard continuous relaxation of the binary antenna selection
variables, and then reformulate the problem such that it is amendable to
successive convex approximation. Thereby, solving the continuous relaxation
mostly results in near-binary solution. To recover the binary variables from
the continuous relaxation, we switch off all the antennas for which the
continuous values are smaller than a small threshold. Numerical results
illustrate the superior convergence result and significant achievable gains in
terms of energy efficiency with the proposed algorithm.Comment: 6 pages, 5 figures, accepted to IEEE ICC 2017 - International
Workshop on 5G RAN Desig
Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation
Symbol-level precoding is a new paradigm for multiuser downlink systems which
aims at creating constructive interference among the transmitted data streams.
This can be enabled by designing the precoded signal of the multiantenna
transmitter on a symbol level, taking into account both channel state
information and data symbols. Previous literature has studied this paradigm for
MPSK modulations by addressing various performance metrics, such as power
minimization and maximization of the minimum rate. In this paper, we extend
this to generic multi-level modulations i.e. MQAM and APSK by establishing
connection to PHY layer multicasting with phase constraints. Furthermore, we
address adaptive modulation schemes which are crucial in enabling the
throughput scaling of symbol-level precoded systems. In this direction, we
design signal processing algorithms for minimizing the required power under
per-user SINR or goodput constraints. Extensive numerical results show that the
proposed algorithm provides considerable power and energy efficiency gains,
while adapting the employed modulation scheme to match the requested data rate
Energy-Efficient Symbol-Level Precoding in Multiuser MISO Based on Relaxed Detection Region
This paper addresses the problem of exploiting interference among
simultaneous multiuser transmissions in the downlink of multiple-antenna
systems. Using symbol-level precoding, a new approach towards addressing the
multiuser interference is discussed through jointly utilizing the channel state
information (CSI) and data information (DI). The interference among the data
streams is transformed under certain conditions to a useful signal that can
improve the signal-to-interference noise ratio (SINR) of the downlink
transmissions and as a result the system's energy efficiency. In this context,
new constructive interference precoding techniques that tackle the transmit
power minimization (min power) with individual SINR constraints at each user's
receiver have been proposed. In this paper, we generalize the CI precoding
design under the assumption that the received MPSK symbol can reside in a
relaxed region in order to be correctly detected. Moreover, a weighted
maximization of the minimum SNR among all users is studied taking into account
the relaxed detection region. Symbol error rate analysis (SER) for the proposed
precoding is discussed to characterize the tradeoff between transmit power
reduction and SER increase due to the relaxation. Based on this tradeoff, the
energy efficiency performance of the proposed technique is analyzed. Finally,
extensive numerical results show that the proposed schemes outperform other
state-of-the-art techniques.Comment: Submitted to IEEE transactions on Wireless Communications. arXiv
admin note: substantial text overlap with arXiv:1408.470
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