Per-subcarrier Antenna Selection Research Articles

Performance Analysis of Antenna Selection Techniques in MIMO-OFDM System with Hardware Impairments: Energy Efficiency perspective

<p>In this paper we propose a new MIMO-OFDM model in which we consider various antenna selection techniques like Bulk selection and Per-subcarrier selection etc. with hardware impairments such as non-linearties of amplifiers, quantization noise, phase noise and I-Q imbalance etc. As we know that the transceiver hardware impairments limit the channel capacity and the energy efficiency of MIMO-OFDM system, so we can not neglect the fundamental impacts of these hardware impairments {Kappa (0.05 0.1)} on the energy efficiency in the high SNR domain. Therefore we analyze the Energy Efficiency of Bulk and Per-subcarrier antenna selection techniques with or without hardware impairments. It has been observed that the energy efficiency decreases as the value of these hardware impairments increases. As we compared the Bulk antenna selection with the Per-subcarrier antenna selection scheme, the Per-subcarrier antenna selection requires more number of RF (radio frequency) chains and transmits power in comparison to the Bulk selection. Due to this, the Bulk antenna selection technique is more energy efficient than Per-subcarrier antenna selection.</p>

Energy Efficiency Analysis of Antenna Selection Techniques in Massive MIMO-OFDM System with Hardware Impairments

In massive multiple-input multiple-output (M-MIMO) systems, a large number of antennas increase system complexity as well as the cost of hardware. In this paper, we propose an M-MIMO-OFDM model using per-subcarrier antenna selection and bulk antenna selection schemes to mitigate these problems. Also, we derive a new uplink and downlink energy efficiency (EE) equation for the M-MIMO-OFDM system by taking into consideration the antenna selection schemes, power scaling factor (g=0.25, 0.5), and a range of hardware impairments {κBS, κUEϵ (0, 0.052, 0.12)}. In addition, we investigate a trend of EE by varying various parameters like number of base station antennas (BSAs), SNR, level of hardware impairments, total circuit power consumption, power optimization, antenna selection schemes, and power scaling factor in the proposed M-MIMO-OFDM model. The simulation results thus obtained show that the EE increases with increase in the value of SNR. Also, it increases abruptly up to 100 number of BSA. However, the increase in the EE is not significant in the range of 125 to 400 number of BSA. Further, the bulk antenna selection technique has comparatively more EE than the per-subcarrier antenna selection. Moreover, EE gaps between antenna selection schemes decrease with increase in the value of hardware impairments and power scaling factor. However, as the hardware degradation effect increases, the EE of the bulk antenna selection scheme suffers more degradation as compared to the Per-subcarrier antenna selection scheme. It has also been observed that EE performance is inversely proportional to the total circuit power consumption (λ+γ) and it increases with the power optimization.

Antenna Selection for Reliable MIMO-OFDM Interference Alignment Systems: Measurement-Based Evaluation

Interference alignment (IA) is a promising transmission technology enabling, essentially, the maximum achievable degrees of freedom (DOF) in $K$ -user multiple-input–multiple-output (MIMO) interference channels. The ideal DOF of IA systems have been obtained using independent MIMO channels, which is, usually rarely observed in reality, particularly in indoor environments. Therefore, the data sum rate and symbol error-rate of IA are dramatically degraded in real-world scenarios since the correlation between MIMO channels decreases the signal-to-noise ratio (SNR) of the received signal after alignment. For this reason, an acceptable sum rate of IA in real MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels was obtained in the literature by modifying the distance between network nodes and the separation between the antennas within each node to minimize the spatial correlation. In this paper, we propose to apply transmit antenna selection to MIMO-OFDM IA systems either through bulk or per-subcarrier selection, aiming at improving the sum-rate and/or error-rate performance under real-world channel circumstances, while keeping the minimum spatial antenna separation of 0.5 wavelengths within each node. Two selection criteria are considered: maximum sum rate (Max-SR) and minimum error rate (Min-ER). To avoid subcarrier imbalance across the antennas of each user, which is caused by per-subcarrier selection, a constrained per-subcarrier antenna selection is operated. Furthermore, a suboptimal antenna selection algorithm is proposed to reduce the computational complexity of the optimal algorithm. An experimental validation of MIMO-OFDM IA with antenna selection in an indoor wireless network scenario is presented. The experimental results are compared with deterministic channels that are synthesized using hybrid electromagnetic (EM) ray-tracing models. Our performance evaluation shows that the practical feasibility of MIMO-OFDM IA systems is significantly increased by antenna selection in real-world scenarios.

Optimal Design for Energy-Efficient Per-Subcarrier Antenna Selection MIMO–OFDM Wireless Systems

In this paper, we consider a novel optimal design for per-subcarrier antenna selection multi-input multi-output orthogonal frequency division multiplexing systems from an energy-efficiency perspective. The optimal number of antennas, i.e., the number of radio frequency chains, that needs to be built-in on a transmitter to achieve the maximum energy-efficiency is determined. Specifically, an optimization problem for maximizing the average energy-efficiency with respect to the number of antennas is formulated. To solve this optimization problem, we first derive a closed-form formula expressing the cost function (i.e., the average energy-efficiency) as a function of the number of antennas. Search algorithms are then designed to obtain the optimal number of antennas. It is shown that the optimal number of equipped antennas depends on particular values of the circuit power consumption, the actual transmitted power, and the channel characteristics. Simulation results are provided to validate the analysis.

Transmit antenna subset selection for high-rate MIMO-OFDM systems in the presence of nonlinear power amplifiers

The deployment of antenna subset selection on a per-subcarrier basis in MIMO-OFDM systems could improve the system performance and/or increase data rates. This paper investigates this technique for the MIMO-OFDM systems suffering nonlinear distortions due to high-power amplifiers. At first, some problems pertaining to the implementation of the conventional per-subcarrier antenna selection approach, including power imbalance across transmit antennas and noncausality of antenna selection criteria, are identified. Next, an optimal selection scheme is devised by means of linear optimization to overcome those drawbacks. This scheme optimally allocates data subcarriers under a constraint that all antennas have the same number of data symbols. The formulated optimization problem to realize the constrained scheme could be applied to the systems with an arbitrary number of multiplexed data streams and with different antenna selection criteria. Finally, a reduced complexity strategy that requires smaller feedback information and lower computational effort for solving the optimization problem is developed. The efficacy of the constrained antenna selection approach over the conventional selection approach is analyzed directly in nonlinear fading channels. Simulation results demonstrate that a significant improvement in terms of error performance could be achieved in the proposed system with a constrained selection compared to its counterpart.

Energy-Efficiency Analysis of Per-Subcarrier Antenna Selection with Peak-Power Reduction in MIMO-OFDM Wireless Systems

The use of per-subcarrier antenna subset selection in OFDM wireless systems offers higher system capacity and/or improved link reliability. However, the implementation of the conventional per-subcarrier selection scheme may result in significant fluctuations of the average power and peak power across antennas, which affects the potential benefits of the system. In this paper, power efficiency of high-power amplifiers and energy efficiency in per-subcarrier antenna selection MIMO-OFDM systems are investigated. To deliver the maximum overall power efficiency, we propose a two-step strategy for data-subcarrier allocation. This strategy consists of an equal allocation of data subcarriers based on linear optimization and peak-power reduction via cross-antenna permutations. For analysis, we derive the CCDF (complementary cumulative distribution function) of the power efficiency as well as the analytical expressions of the average power efficiency. It is proved from the power-efficiency perspective that the proposed allocation scheme outperforms the conventional scheme. We also show that the improvement in the power efficiency translates into an improved capacity and, in turn, increases energy efficiency of the proposed system. Simulation results are provided to validate our analyses.

Rate-lossless PAPR reduction in per-subcarrier antenna selection OFDM systems

We propose a generalised rate-lossless technique for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing systems employing antenna selection on a per-subcarrier basis. The proposed technique, which is from the family of the active constellation extension (ACE) approaches to PAPR reduction, exploits the nulled subcarriers (for a given antenna) that arise through the antenna selection process to reduce the PAPR by introducing a controlled level of distortion to these subcarriers. We demonstrate that known PAPR reduction methods are unsuitable for per-subcarrier antenna selection systems, which motivates our modifications. We then show that our proposal achieves a much lower PAPR than traditional ACE methods for the given systems. Moreover, we demonstrate through a detailed theoretical analysis of the bit-error rate and a simulation analysis of the distortion transmitted on the nulled subcarriers, that the interference to the data signal caused by this distortion will not hinder practical system performance. Finally, we show that the efficacy of the proposed technique increases with the number of transmit antennas.

Per-subcarrier antenna selection with power constraints in OFDM systems

In an OFDM system, antenna selection can be performed on a per-subcarrier basis, which can exploit the frequency selectivity of the channel. However, this may cause power imbalance across the antennas, which may lead to problems with the power amplifiers (PA). To avoid this problem, we devise a scheme that allocates the same number of subcarriers to all antennas, while still offering substantial diversity gains. This is achieved by using integer optimization and we show that this is solvable by linear relaxation, which results in a reduced complexity. The constrained antenna selection is analyzed and it is shown that choosing the cost function as BER offers better diversity gains than using SNR. Simulations with a nonlinear PA show that the integer optimization scheme performs better than unconstrained antenna selection and a previously published ad hoc method.