Youngchul Sung

Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems

In this paper, the problem of pilot beam pattern design for channel estimation in massive multiple-input multiple-output systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam pattern design for optimal channel estimation is proposed under the assumption that the channel is a stationary Gauss-Markov random process. The proposed algorithm designs the pilot beam pattern sequentially by exploiting the properties of Kalman filtering and the associated prediction error covariance matrices and also the channel statistics such as spatial and temporal channel correlation. The resulting design generates a sequentially-optimal sequence of pilot beam patterns with low complexity for a given set of system parameters. Numerical results show the effectiveness of the proposed algorithm.

Least Squares Approach to Joint Beam Design for Interference Alignment in Multiuser Multi-Input Multi-Output Interference Channels

In this correspondence, the problem of interference alignment for K-user time-invariant multi-input multi-output interference channels is considered. The necessary and sufficient conditions for interference alignment are converted to a system of linear equations that have dummy variables. Based on this linear system, a new algorithm for beam design for interference alignment is proposed by minimizing the overall interference misalignment. The proposed algorithm consists of solving a least squares problem iteratively. The convergence of the proposed algorithm is established, and its complexity is analyzed. The performance of the proposed algorithm is also evaluated numerically. It is shown that the proposed algorithm has faster convergence and lower complexity than the previous method with a comparable sum rate performance in the most practical case of two receive antennas.

Blind decorrelating RAKE receivers for long-code WCDMA

The problem of blind and semiblind channel estimation and symbol detection is considered for long-code wideband code division multiple access (CDMA) systems, including systems with multirate and multicode transmissions. A decorrelating matched filter, implemented efficiently in state-space, eliminates multiaccess interference and produces a bank of vector processes. Each vector process spans a one-dimensional (1-D) subspace from which channel parameters and data symbols of one user are estimated jointly by least squares. A new identifiability condition is established, which suggests that channels unidentifiable, in short-code CDMA systems are almost surely identifiable when aperiodic spreading codes are used. The decorrelating matched filter is implemented efficiently based on time-varying state-space realizations that exploit the structure of sparsity of the code matrix. The mean square error of the estimated channel is compared to the Cramer-Rao bound, and a bit error rate (BER) expression for the proposed algorithm is presented.

Two-Stage Beamformer Design for Massive MIMO Downlink By Trace Quotient Formulation

In this paper, the problem of outer beamformer design based only on channel statistic information is considered for two-stage beamforming for multi-user massive MIMO downlink, and the problem is approached based on signal-to-leakage-plus-noise ratio (SLNR). To eliminate the dependence on the instantaneous channel state information, a lower bound on the average SLNR is derived by assuming zero-forcing (ZF) inner beamforming, and an outer beamformer design method that maximizes the lower bound on the average SLNR is proposed. It is shown that the proposed SLNR-based outer beamformer design problem reduces to a trace quotient problem (TQP), which is often encountered in the field of machine learning. An iterative algorithm is presented to obtain an optimal solution to the proposed TQP. The proposed method has the capability of optimally controlling the weighting factor between the signal power to the desired user and the interference leakage power to undesired users according to different channel statistics. Numerical results show that the proposed outer beamformer design method yields significant performance gain over existing methods.

Randomly-Directional Beamforming in Millimeter-Wave Multiuser MISO Downlink

In this paper, the performance of opportunistic random beamforming (RBF) and the multiuser (MU) gain in millimeter-wave (mm-wave) MU multiple-input single-output (MISO) downlink systems are analyzed based on the uniform random single-path (UR-SP) channel model suitable for highly directional mm-wave radio propagation channels. It is shown that under the UR-SP channel model, RBF achieves linear sum rate scaling with respect to (w.r.t.) the number of transmit antennas and, furthermore, yields optimal sum rate performance when the number of transmit antennas is large, if the number of users increases linearly w.r.t. the number of transmit antennas. Several beam training and user selection methods are investigated to yield insights into the most effective beamforming and scheduling choice for mm-wave MU-MISO in various operating conditions. Simulation results validate our analysis based on asymptotic techniques for finite cases.

RawPEACH: Multiband CSMA/CA-based cognitive radio networks

A new medium access control (MAC) scheme embedding physical channels into multiband carrier sense multiple access/collision avoidance (CSMA/CA) networks is proposed to provide strict quality of service (QoS) guarantee to high priority users. In the proposed scheme, two priority classes of users, primary and secondary users, are supported. For primary users physical channels are provided to ensure strict QoS, whereas secondary users are provided with best-effort service using CSMA/CA modified for multiband operation. The performance of the proposed MAC scheme is investigated using a new multiband CSMA/CA Markov chain model capturing the primary user activity and the operation of secondary users in multiple bands. The throughput of secondary users is obtained as a function of the primary user activity and other CSMA/CA parameters. It is shown that the new MAC scheme yields larger throughput than the conventional single-band CSMA/CA when both schemes use the same bandwidth.

Outage Probability and Outage-Based Robust Beamforming for MIMO Interference Channels with Imperfect Channel State Information

In this paper, the outage probability and outage-based beam design for multiple-input multiple-output (MIMO) interference channels are considered. First, closed-form expressions for the outage probability in MIMO interference channels are derived under the assumption of Gaussian-distributed channel state information (CSI) error, and the asymptotic behavior of the outage probability as a function of several system parameters is examined by using the Chernoff bound. It is shown that the outage probability decreases exponentially with respect to the quality of CSI measured by the inverse of the mean square error of CSI. Second, based on the derived outage probability expressions, an iterative beam design algorithm for maximizing the sum outage rate is proposed. Numerical results show that the proposed beam design algorithm yields significantly better sum outage rate performance than conventional algorithms such as interference alignment developed under the assumption of perfect CSI.

How Much Information Can One Get From a Wireless Ad Hoc Sensor Network Over a Correlated Random Field

New large-deviations results that characterize the asymptotic information rates for general d-dimensional (d -D) stationary Gaussian fields are obtained. By applying the general results to sensor nodes on a two-dimensional (2-D) lattice, the asymptotic behavior of ad hoc sensor networks deployed over correlated random fields for statistical inference is investigated. Under a 2-D hidden Gauss-Markov random field model with symmetric first-order conditional autoregression and the assumption of no in-network data fusion, the behavior of the total obtainable information [nats] and energy efficiency [nats/J] defined as the ratio of total gathered information to the required energy is obtained as the coverage area, node density, and energy vary. When the sensor node density is fixed, the energy efficiency decreases to zero with rate Theta(area-1/2 ) and the per-node information under fixed per-node energy also diminishes to zero with rate O(Nt -1/3) as the number Nt of network nodes increases by increasing the coverage area. As the sensor spacing dn increases, the per-node information converges to its limit D with rate D-radic(dn)e-alphadn for a given diffusion rate alpha. When the coverage area is fixed and the node density increases, the per-node information is inversely proportional to the node density. As the total energy Et consumed in the network increases, the total information obtainable from the network is given by O(logEt ) for the fixed node density and fixed coverage case and by Theta(Et 2/3 ) for the fixed per-node sensing energy and fixed density and increasing coverage case.

Beam Tracking for Interference Alignment in Slowly Fading MIMO Interference Channels: A Perturbations Approach Under a Linear Framework

In this paper, the beam design for signal-space interference alignment in slowly fading multiuser multiple-input multiple-output (MIMO) interference channels is considered. Based on a linear formulation for interference alignment, a predictive beam tracking algorithm is proposed using matrix perturbation theory. The proposed algorithm, based on a mixture of iteration and update, computes interference-aligning beamforming vectors at the current time by updating the previous beam vectors based on the channel difference between the two time steps during the predictively updating phase, and yields significant reduction in computational complexity compared with existing methods recalculating beams at each time step. The tracking performance of the algorithm is analyzed in terms of mean square error and sum rate loss between the predictively updating approach and the recalculating approach, and the impact of imperfect channel knowledge is also investigated under the state-space channel model. Numerical results show that the proposed algorithm has almost the same performance as non-predictive methods in sum rate. Thus, the proposed algorithm provides a very efficient way to realize interference alignment in a realistic slowly fading MIMO channel environment.

A least squares approach to joint beam design for interference alignment in multiuser interference channels

The problem of interference alignment for K-user time-invariant multi-input multi-output (MIMO) interference channels is considered. A sufficient condition for perfect interference alignment is converted to a linear system of equations which is overdetermined for K≥ 4. It is shown that this linear system is infeasible almost surely. To obtain the approximate solution to this problem, we use a least squares (LS) approach. Various constraints are considered for the LS formulation, including the total signal power, individual user power and individual user beam power constraints. Numerical results are provided to evaluate the proposed design method.