Daniel J. Ryan

Sum rates, rate allocation, and user scheduling for multi-user MIMO vector perturbation precoding

This paper considers the multiuser multiple-input multiple-output (MIMO) broadcast channel. We consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via vector perturbation. We derive expressions for the sum rate in terms of the average energy of the precoded vector, and use this to derive a high signal-to-noise ratio (SNR) closed-form upper bound, which we show to be tight via simulation. We also propose a modification to vector perturbation where different rates can be allocated to different users. We conclude that for vector perturbation precoding most of the sum rate gains can be achieved by reducing the rate allocation problem to the user selection problem. We then propose a low-complexity user selection algorithm that attempts to maximize the high-SNR sum rate upper bound. Simulations show that the algorithm outperforms other user selection algorithms of similar complexity.

Reflected Simplex Codebooks for Limited Feedback MIMO Beamforming

This paper proposes Reflected Simplex codebooks for limited feedback beamforming in multiple-input multiple-output (MIMO) wireless systems. The codebooks are a geometric construction based on simplices and the An lattice. We propose a fast codebook search and indexing algorithm. We show that such codebooks perform superior or comparable to other codebooks, with much lower implementation complexity.

Using a Sensor Network to Localize a Source under Spatially Correlated Shadowing

This paper considers the use of a sensor network to estimate the position of a transmitting radio based on the received signal strength at the sensors. A generic path loss model which includes the effects of spatially correlated shadowing is assumed. A weighted likelihood (WL) estimator is proposed, which can be seen as a simplified minimum mean square error (MMSE) estimator. This estimator can be used for localizing a source in a static scenario or it can provide the initial position estimate of a tracking algorithm. The performance of the WL estimator is simulated, and robustness to erroneous assumptions about path loss exponent, shadowing variance and correlation distance is demonstrated.

Linear-time block noncoherent detection of PSK

We propose a new algorithm for noncoherent sequence detection of M-ary phase-shift-keying (M-PSK) symbols transmitted over a block fading channel. The algorithm is of complexity O(T), where T is the sequence length, and is therefore computationally superior to existing maximum-likelihood (ML) detectors of complexity O(T logT). Our detector is based on a new approximation we propose to the noncoherent ML function. We show that by using this close approximation, the detection problem reduces to a nearest lattice point problem for the lattice An*, from which we derive our O(T) approach. Simulation results are provided that show the difference in bit error rate is negligibly small for a wide range of signal-to-noise ratios.

Performance of RVQ Limited Feedback Beamforming over Correlated Channels

This work considers the performance of multipleinput single-output (MISO) wireless systems employing beamforming over correlated wireless channels. More specifically, we examine the use of Random Vector Quantization (RVQ) as a limited feedback method of informing the transmitter of the appropriate beamforming vector. Using RVQ, we are able to derive the distribution functions of the beamforming gain in such a system in closed form. In addition, we derive the power offset in the delay-limited capacity for RVQ systems in closed form based on the approach of Au-Yeung and Love for i.i.d. channels [1]. This result is applicable to any channel model. For all of these results we derive simplifications for the case of two transmit antennas. Simulation results are provided that confirm our results and show a decrease in performance for the correlated channels.

Space-Time Vector Perturbation Precoding

Vector Perturbation Precoding (VPP) has gained recognition as a reduced-complexity method to achieve high-rates in multiuser multiple-input multiple-output (MIMO) downlink. Here we propose Space-Time VPP (STVPP), where the nonlinear lattice-based precoding operations of standard VPP are extended into the time domain. This is done by introducing temporal precoding lattices for each user, and performing the perturbation step at the transmitter for all users jointly. Although the transmitter complexity is increased, we show that by employing root lattices for the temporal precoding the computational complexity at each mobile receiver remains O(1). We provide new bounds on the required transmit energy scaling, as well as the sum rate. We show that the optimal sum rates are approached for moderate to high signal-to-noise ratio (SNR). Simulations show that significant gains can be achieved by precoding over even a few time instants, and that the proposed bounds are tight.

Sum Rates and User Scheduling for Multi-User MIMO Vector Perturbation Precoding

This paper considers the multiuser multiple-input multiple-output (MIMO) Rayleigh fading broadcast channel. We consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users via a multi-user technique known as vector perturbation. We derive expressions for the capacity in terms of the average energy of the precoded vector, and use this to derive a closed-form high-SNR upper bound, which we show to be tight via simulation. We then turn to the practical issue of user selection. We propose a low-complexity user selection algorithm that attempts to maximize the high-SNR sum rate upper bound. Simulations show that the algorithm outperforms other user selection algorithms of similar complexity.

Sum rates for regularized multi-user MIMO vector perturbation precoding

In this paper, we analyze the sum rate performance of multiuser multi-antenna downlink channel. We consider Rayleigh fading environment when regularized vector perturbation precoding (R-VPP) method is used at the transmitter. The sum rate characterization of R-VPP is difficult because of the correlation between the multiuser interference and the data symbols. We derive expressions for the sum rate in terms of the variance of the received signal. We also provide a closed form approximation for the mean squared error (MSE) which is shown to work well for the whole range of SNR. Further, we also propose a simpler expression for R-VPP sum rate based on MSE. The simulation results show that the proposed expressions for R-VPP sum rate closely match the sum rate found by the entropy estimation, and also confirm that R-VPP performs very close to dirty paper coding (DPC) for all SNR values.

Block noncoherent detection of hexagonal QAM

We consider block noncoherent detection of hexagonal quadrature amplitude modulation (QAM). We focus on hexagonal constellations generated from a Voronoi code. We find that these constellations are particularly well suited to noncoherent detection because they avoid most of the identifiability problems that occur with more traditional constellations. We describe a fast, approximate, noncoherent detection algorithm with statistical performance that is almost indistinguishable from an optimal, brute force approach, but with significantly smaller computational requirements. The performance is close to that of coherent detection when the block length is sufficiently large.

Performance of Vector Perturbation Multiuser MIMO Systems over Correlated Channels

his paper considers the performance of the multiuser multi-antenna downlink where