Ngoc Phuc Le

Antenna Selection Strategies for MIMO-OFDM Wireless Systems: An Energy Efficiency Perspective

In this paper, we investigate antenna selection strategies for multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless systems from an energy efficiency (EE) perspective. We first derive closed-form expressions of the EE and the energy efficiency-spectral efficiency (EE-SE) tradeoff in conventional antenna selection MIMO-OFDM systems. The obtained results show that these systems suffer from a significant loss in EE. To achieve a better EE performance, we propose an adaptive antenna selection method where both the number of active radio-frequency chains and the antenna indexes are selected depending on the channel condition. This selection scheme could be implemented by an exhaustive search technique for a small number of antennas. Moreover, we develop a greedy algorithm that achieves a near-optimal performance with much lower complexity compared with the (optimal) exhaustive search method when the number of antennas is large. In addition, the efficacy of power loading across subcarriers for improved EE in the conventional and proposed antenna selection MIMO-OFDM systems is considered. Monte Carlo simulation results are provided to validate our analyses.

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.

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 antenna selection multi-input multi-output automatic repeat request systems over Nakagami-m fading channels

In this study, the authors investigate energy efficiency in antenna selection multi-input multi-output automatic repeat request (MIMO ARQ) wireless systems. The authors first derive an approximate expression for the average frame-error rate (FER) in antenna selection MIMO systems over quasi-static Nakagami-m fading channels. The FER approximation is then used to obtain an analytical expression of an energy-efficiency metric that is defined as the total energy required to successfully deliver one information bit. The authors prove that this energy-efficiency metric is a quasi-convex function with respect to the average signal-to-noise ratio value. Based on this analysis, the authors obtain the optimal value of the average energy per transmitted data symbol such that the total energy consumption in the system is minimised. The results show that the energy efficiency in antenna selection MIMO ARQ systems is improved when the number of equipped antennas is increased. Simulation results are provided to validate the analysis.

Adaptive antenna selection for energy-efficient MIMO-OFDM wireless systems

In this paper, we investigate energy-efficiency in antenna selection OFDM-based systems. We show that an OFDM system with conventional antenna selection approaches, including per-subcarrier selection (i.e., selecting antennas independently for each subcarrier) and bulk-selection (i.e., choosing the same antennas for all subcarriers), suffers from a significant loss in energy-efficiency. To achieve a better energy-efficiency performance, we propose an adaptive antenna selection scheme where both the number of active RF (radio frequency) chains and the antenna indices are selected depending on the channel condition. This selection scheme could be implemented by exhaustive search. Moreover, we develop an algorithm that achieves a near-optimal performance with much lower complexity when the number of antennas is large, compared to the (optimal) exhaustive search method. Simulation results demonstrate a significant improvement in terms of energy-efficiency in the proposed system compared to the conventional counterparts.

Very high data rate MB-OFDM UWB systems with transmit diversity techniques

In this paper, the application of space time block codes in a very high data rate multiband-OFDM ultra-wideband (VHDR MB-OFDM UWB) system, where the Modified Dual Carrier Modulation (MDCM) scheme and Low Density Parity Check codes are deployed, is investigated. First, we present a new table-based mapping approach and derive soft-demapping expressions for the MDCM scheme. We then propose a space-time-frequency coded VHDR MB-OFDM UWB system by incorporating space time block codes into the conventional VHDR MB-OFDM UWB system. Numerical simulations of the system supporting a data rate of 1Gbps over the IEEE 802.15.3a channel models are implemented. The simulation results confirm the new mapping/demapping method as well as demonstrate the significant improvement in terms of packet error rate performance of the proposed system over the standard one.

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.

Combined adaptive lattice reduction-aided detection and antenna shuffling for DSTTD-OFDM systems

In this paper, we consider lattice reduction (LR) aided linear detection in a DSTTD-OFDM (double space-time transmit diversity-orthogonal frequency division multiplexing) system with antenna shuffling. We first derive an antenna shuffling criterion for the LR-aided DSTTD-OFDM system. Next, we propose a combined reduced-feedback and adaptive LR algorithm by exploiting the correlation between OFDM subcarriers in the frequency domain. The LR-aided DSTTD-OFDM system with this algorithm requires low computational effort for the LR operation and small feedback information. Simulation results show that a significant improvement could be achieved in the proposed system compared to previous (non-LR-aided) systems under spatially correlated channels. Also, the proposed complexity-reduced approach could greatly lower the system complexity while exhibiting a slight performance loss.

Transmit antenna subset selection with power balancing for high data rate MIMO-OFDM UWB systems

This paper proposes per-subcarrier transmit antenna subset selection with power balancing for MIMO-OFDM UWB systems to simultaneously improve the system error performance and increase data rates. The deployment of the per-subcarrier antenna subset selection may result in a power unbalance across antennas, which could cause power amplifiers (PAs) to operate in their non-linear regions. To overcome this disadvantage, we formulate a linear optimization problem for the optimal allocation of data subcarriers under a constraint that all antennas have the same number of assigned data symbols. This optimization problem could be applied to systems with an arbitrary number of multiplexed data streams, antennas, and with different selection criteria. The efficacy of the proposed allocation scheme from the PA linearity perspective is validated by analyzing the distribution of the peak amplitude of time-domain signals. Simulation results demonstrate that the proposed system outperforms the system without a balancing constraint.

Double space-time transmit diversity for very high data rate MB-OFDM UWB systems

In this paper, we investigate a multiband-orthogonal frequency division multiplexing ultra-wideband (MB-OFDM UWB) system with very high data rates (VHDR) of several gigabits per second (Gbps). We propose a DSTTD-based VHDR MB-OFDM UWB system by incorporating a double space-time transmit diversity (DSTTD) scheme into the conventional MB-OFDM UWB system. At the receiver, an efficient soft-demapper that takes into consideration the noise enhancement due to a zero-forcing equalization is developed. Numerical simulations of the proposed system at a very high data rate of 2.Gbps over the IEEE 802.15.3a channel models are implemented. The simulation results show that this system could achieve a very good performance in a low signal-to-noise ratio (SNR) region.