Sang Rim Lee

Generalized channel inversion methods for multiuser MIMO systems

Block diagonalization (BD) is a well-known precoding method in multiuser multi-input multi-output (MIMO) broadcast channels. This scheme can be considered as a extension of the zero-forcing (ZF) channel inversion to the case where each receiver is equipped with multiple antennas. One of the limitation of the BD is that the sum rate does not grow linearly with the number of users and transmit antennas at low and medium signal-to-noise ratio regime, since the complete suppression of multi-user interference is achieved at the expense of noise enhancement. Also it performs poorly under imperfect channel state information. In this paper, we propose a generalized minimum mean-squared error (MMSE) channel inversion algorithm for users with multiple antennas to overcome the drawbacks of the BD for multiuser MIMO systems. We first introduce a generalized ZF channel inversion algorithm as a new approach of the conventional BD. Applying this idea to the MMSE channel inversion for identifying orthonormal basis vectors of the precoder, and employing the MMSE criterion for finding its combining matrix, the proposed scheme increases the signal-to-interference-plus-noise ratio at each users receiver. Simulation results confirm that the proposed scheme exhibits a linear growth of the sum rate, as opposed to the BD scheme. For block fading channels with four transmit antennas, the proposed scheme provides a 3 dB gain over the conventional BD scheme at 1% frame error rate. Also, we present a modified precoding method for systems with channel estimation errors and show that the proposed algorithm is robust to channel estimation errors.

Capacity Analysis of Distributed Antenna Systems in a Composite Fading Channel

In this paper, we investigate a behavior of the cell average ergodic capacity for distributed antenna systems (DAS) in a composite fading channel model which contains small-scale and large-scale fadings. For small-scale Rayleigh fadings, based on the proof of asymptotic normality, the mean and the variance of the instantaneous capacity were recently presented as a closed form solution. However, this solution is too complicated to be applied directly for obtaining the average ergodic capacity over a cell. In this work, we derive a simple and accurate expression for the ergodic capacity by utilizing the high signal to noise ratio (SNR) analysis. Our simple solution provides meaningful insight on how the ergodic capacity is affected as SNR, pathloss and antenna configurations change. Also it is useful for capturing quantitative performance measures such as the multiplexing gain and the power offset. In addition, we analyze the cell average ergodic capacity by taking into account the shadowing effect and the pathloss on the basis of our results on the small-scale fadings. These expressions lead to some insights on the performance of DAS under practical environments. Finally, numerical results confirm the validity of our analytical results.

Transmission Schemes Based on Sum Rate Analysis in Distributed Antenna Systems

In this paper, we study single cell multi-user downlink distributed antenna systems (DAS) where antenna ports are geographically separated in a cell. First, we derive an expression of the ergodic sum rate for the DAS in the presence of pathloss. Then, we propose a transmission selection scheme based on the derived expressions which does not require channel state information at the transmitter. Utilizing the knowledge of distance information from a user to each distributed antenna (DA) port, we consider the optimization of pairings of DA ports and users to maximize the system performance. Based on the ergodic sum rate expressions, the proposed scheme chooses the best mode maximizing the ergodic sum rate among mode candidates. In our proposed scheme, the number of mode candidates are greatly reduced compared to that of ideal mode selection. In addition, we analyze the signal to noise ratio cross-over point for different modes using the sum rate expressions. Through Monte Carlo simulations, we show the accuracy of our derivations for the ergodic sum rate. Moreover, simulation results with the pathloss modeling confirm that the proposed scheme produces the average sum rate identical to the ideal mode selection with significantly reduced candidates.

A New Channel Quantization Strategy for MIMO Interference Alignment with Limited Feedback

In K-user multiple-input multiple-output (MIMO) interference channels, it was shown that interference alignment (IA) achieves a full spatial multiplexing gain when perfect channel state information (CSI) is available at each transmitter in the network. When the CSI is fed back from receivers using the limited number of feedback bits, a significant performance loss is inevitable in the IA due to quantized channel knowledge. In this paper, we propose a new channel quantization strategy to optimize the performance of the IA with limited feedback. In our proposed scheme, we introduce an additional receive filter to minimize the chordal distance which accounts for the quantization error on Grassmann manifold. Besides, we analyze a reduction in terms of the chordal distance in our scheme compared to conventional methods. Simulation results verify that the proposed scheme provides substantially better performance than the conventional method as the number of feedback bits is increased. We show that our scheme exhibits 30% and 40% sum rate gains compared to the conventional scheme when the numbers of the feedback bits are 10 and 15, respectively, with two antennas per node.

Antenna Placement Optimization for Distributed Antenna Systems

In this paper, we propose new algorithms to determine the antenna location for downlink distributed antenna systems (DASs) in single-cell and two-cell environments. We consider the composite fading channel which includes small and large scale fadings. First, for the single-cell DAS, we formulate the optimization problem of distributed antenna (DA) port locations by maximizing the lower bound of the expected signal to noise ratio (SNR). In comparison to the conventional algorithm based on the squared distance criterion which requires an iterative method, our problem generates a closed form solution. Next, for the two-cell DAS, we propose a gradient ascent algorithm which determines the optimum DA locations by maximizing the lower bound of the expected signal to leakage ratio (SLR). In our work, we consider selection transmission, maximal ratio transmission and zero-forcing beamforming (ZFBF) under sum power constraint and study equal gain transmission and scaled ZFBF under per-antenna power constraint. Simulation results show that our proposed algorithms based on both the SNR and the SLR criteria offer a capacity gain over the conventional centralized antenna systems.

Optimal Beamforming Designs for Wireless Information and Power Transfer in MISO Interference Channels

This paper investigates the optimal transmit beamforming designs for simultaneous wireless information and power transfer (SWIPT) in multiple-input single-output interference channels (IFC). Based on cooperation level among transmitters and receivsers, we classify the SWIPT IFC systems into two categories. First, we consider the IFC with partial cooperation, where only channel state information (CSI) is available at transmitters and receivers, but not the signal waveform. Second, we examine the IFC with signal cooperation, where both the CSI and the signal waveforms are known to transmitters and receivers. Then, for the both scenarios, we identify the Pareto boundary of the achievable rate-energy (R-E) region which characterizes the optimal tradeoff between the information rate and the harvested energy. To this end, the problems for maximizing the information rate are formulated with minimum required harvested energy constraint. To solve these non-convex problems, we introduce parameterization techniques for characterizing the R-E region. As a result, the original problem is separated into two subproblems, for which closed-form solutions are obtained by addressing the line search method. Finally, we provide numerical examples for the Pareto boundary of the R-E region through simulations.

Optimal Power Allocation Scheme for Energy Efficiency Maximization in Distributed Antenna Systems

In this paper, we present a power allocation method for a distributed antenna system (DAS) to maximize energy efficiency (EE), which is defined as the ratio of the transmission rate to the total consumed power. Different from conventional EE maximization schemes that require iterative numerical methods, we derive the optimal solution as a closed form by solving Karush-Kuhn-Tucker conditions. The obtained closed-form expression is applicable to DAS with an arbitrary number of distributed antenna (DA) ports and general per-DA port power constraints and is also guaranteed to be globally optimum. Then, we provide several interesting observations on the proposed EE maximizing power allocation scheme. Based on these results, we propose a simplified practical power allocation method that employs the DA port selection and computes the power level in a distributed manner. Through Monte Carlo simulations, we show that the proposed optimal power allocation method produces the EE identical to exhaustive search with significantly reduced computational complexity. In addition, it is shown that the proposed simplified power allocation method based on the DA port selection exhibits little performance loss compared to the optimal algorithm with a remarkable reduction in the system overhead.

Optimal Beamforming Schemes and its Capacity Behavior for Downlink Distributed Antenna Systems

In this paper, we investigate the outage and ergodic capacity of downlink distributed antenna systems (DAS) where each distributed antenna unit (DAU) has multiple antennas with per-DAU power constraint. We first derive the optimal beamforming vector in a closed form by applying a matrix minor condition to relax the positive semi-definite constraint. We observe that our derived solution has a form of maximum ratio transmission per each DAU with full power. Based on the derived optimal beamforming, the outage and ergodic capacity under Rayleigh fading channels are analyzed. To this end, we show that a distribution of the received signal-to-noise ratio is characterized as a Gamma distribution by approximating a sum of non-identical independent Nakagami-m random variables as a single Nakagami-m random variable based on the moment matching method. Then, we present an accurate formula of the outage and ergodic capacity in a closed form which matches well with the simulation results. Furthermore, we derive an upper bound of an achievable average rate of DAS with limited feedback. We then propose a new feedback bit allocation algorithm to maximize the derived metric. Simulation results confirm the accuracy of the derived outage and ergodic capacity expressions and the efficiency of the proposed bit allocation method.

Downlink Vertical Beamforming Designs for Active Antenna Systems

In this paper, we study a vertical beamforming technique for multiple-input multiple-output downlink multi-user systems. In general, the transmit antenna gain is controlled by adjusting the boresight of antennas in directional antennas, and thus the cell average rate varies according to the angle of the boresight. First, we compute the tilting angles for directional antenna systems which maximize the cell average rate. To this end, the probability density function of a three-dimensional user distribution is derived. Based on the result, we analyze the average rate gain of active antenna systems over passive antenna systems for a single user case. Furthermore, for a multi-user active antenna system, beamforming designs to maximize the weighted sum rate are proposed by optimizing the transmit antenna gain and power allocation. Since finding joint optimal parameters requires prohibitively high computational complexity, we separate the optimization problem into two sub-problems of the vertical beamforming and the power allocation. Then a simple vertical beamforming algorithm based on a high signal-to-noise ratio assumption is presented. Also, for a multi-user passive antenna system, we provide a beamforming scheme based on a multi-sector concept. Simulation results show that the proposed beamforming schemes outperform the conventional beamforming schemes.

Optimal power allocation for energy efficiency maximization in distributed antenna systems

In this paper, we present a power allocation method for a distributed antenna system (DAS) to maximize energy efficiency (EE) which is defined as the ratio of the transmission rate to the total consumed power. Different from conventional EE maximization schemes which require iterative numerical methods, we derive the optimal solution as closed form by solving Karush-Kuhn-Tucker conditions. The obtained closed form expression is applicable to DAS with an arbitrary number of distributed antenna (DA) ports and general per-DA port power constraints, and is also guaranteed to be globally optimum. Through Monte Carlo simulations, we show that the proposed power allocation method produces the optimal average EE identical to exhaustive search with significantly reduced computational complexity. In addition, we demonstrate that DAS is more beneficial in terms of EE compared to conventional antenna systems.