Channel Frequency Correlation Research Articles

CNN-Based LOS/NLOS Identification in 3-D Massive MIMO Systems

In this letter, we propose to identify line-of-sight (LOS) and non-line-of-sight (NLOS) conditions based on a convolutional neural network (CNN) in urban 3-D massive MIMO systems. The proposed method includes two parts. In the first part, given that the paths spread differently in time domain, we combine the normalized tap energy distribution on each antenna utilizing sounding reference signals and construct the coordinated tap energy matrix. In the second part, we train a CNN to analyze the matrix and identify the LOS/NLOS conditions. A 3-D massive MIMO channel model is considered in our simulation. Results show that error rates of the worst performance using proposed identification algorithm are lower than 2.4%, and a remarkable improvement is achieved compared with schemes that exploit the space–time–frequency channel correlation features.

Spreading code allocation strategy for downlink multicarrier code division multiple access transmission in a correlated Rayleigh fading channel

In this paper, we address the problem of multiple access interference MAI in a downlink multicarrier code division multiple access system. Because in the realistic case of correlated faded subcarriers, MAI greatly depends on the codes assigned to users, one way of improving performance without increasing receiver complexity consists in an appropriate code selection. We propose a code allocation strategy with the following properties: possible use with any code sequence and equalizer, low complexity, and efficient management of load variations. The allocation problem is formulated as a minimization problem of a cost function related to MAI. First, we provide analytical expressions for the channel frequency correlation function after maximum ratio combining, equal gain combining, and minimum mean square error equalization and for the MAI power. Then, by approximating these expressions, we define a simple cost function and build an iterative algorithm on the basis of the minimum maximum criterion to select the spreading codes. Finally, a complete analysis of the allocation efficiency is provided versus key parameters, in particular, the degree of correlation between the faded subcarriers, the system load, and the equalization techniques. Copyright © 2012 John Wiley & Sons, Ltd.

Novel High Performance MIMO-OFDM Based Measures for NLOS Identification in Time-Varying Frequency and Space Selective Channels

This paper proposes new measures for non-line-of-sight (NLOS) identification in wireless localization systems. The measures are defined based on the space-time-frequency channel correlation features of multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Here, space-time channel correlation refers to the correlation across antenna elements and time, and frequency channel correlation refers to the correlation across subcarriers. The probability-of-detection performance of these NLOS identification methods is investigated. The results represent a high identification performance when the LOS and NLOS powers are in the same order of magnitude.

Iterative Channel Estimation for Nonbinary LDPC-Coded OFDM Signals

This work deals with the issue of channel estimation in the context of non-binary LDPC-coded OFDM systems over doubly selective multipath channels. In particular, we show how to derive an iterative Wiener-filter-based estimation method using both time and frequency channel correlation and considering the particular characteristics of the channel code. The proposed algorithm can use either soft information or hard decisions fed back by the decoder to refine the channel estimation, so as to improve the system performance at the expense of an increased receiver complexity. Simulation results under typical working conditions are presented to compare the performance of the proposed method with respect to classical techniques.

5-GHz-Band Vehicle-to-Vehicle Channels: Models for Multiple Values of Channel Bandwidth

In Sen and Matolak's earlier paper, 5-GHz-band vehicle-to-vehicle (V2V) channel models were presented for channel bandwidths of 5 and 10 MHz. In this paper, we provide additional tapped delay line models for bandwidths of 1, 20, 33.33, and 50 MHz based upon the data used in Sen and Matolak's paper. We provide tables of channel parameters for five types of V2V channel classes and also include example tap correlation coefficients. Root-mean-square delay spread values are summarized, as are values of bandwidth for which the channel frequency correlation takes values of 0.7 and 0.5. As with the results from Sen and Matolak's paper, these models should be useful for designers in future V2V communication systems.

Channel state feedback schemes for multiuser MIMO-OFDM downlink

Channel state feedback schemes for the MIMO broadcast downlink have been widely studied in the frequency flat case. This work focuses on the more relevant frequency selective case, where some important new aspects emerge. We consider a MIMO-OFDM broadcast channel and compare achievable ergodic rates under three channel state feedback schemes: analog feedback, direction quantized feedback and channel quantized feedback. The first two schemes are direct extensions of previously proposed schemes. The third scheme is novel, and it is directly inspired by rate-distortion theory of Gaussian correlated sources. For each scheme we derive the conditions under which the system achieves full multiplexing gain. The key difference with respect to the widely treated frequency-flat case is that in MIMO-OFDM the frequency domain channel transfer function is a Gaussian correlated source. The new time-domain quantization scheme takes advantage of the channel frequency correlation structure and outperforms the other schemes. Furthermore, it is by far simpler to implement than complicated spherical vector quantization. In particular, we observe that no structured codebook design and vector quantization is actually needed for efficient channel state information feedback.

On the problems of symbol‐spaced tapped‐delay‐line models for WSSUS channels

AbstractThis paper analyzes the validity and statistical behavior of symbol‐spaced tapped‐delay‐line (SSTDL) models for wide‐sense stationary uncorrelated scattering (WSSUS) mobile radio channels. SSTDL models are obtained by sampling the channel impulse response (CIR) in delay domain at a rate equal to the reciprocal of the symbol duration. They were proposed more than four decades ago as canonical channel models for band‐limited time‐variant linear (TVL) systems, and are nowadays widely in use for assessing the performance of several wireless communication systems. The applicability of these tapped‐delay‐line (TDL) models seems to be unquestionable, as they were developed in the framework of the sampling theorem. Nonetheless, we show here that SSTDL models should be used with care to model WSSUS channels, because the channel's uncorrelated scattering (US) condition might easily be violated. Furthermore, we show that SSTDL models suffer from strong limitations in emulating the channel frequency correlation function (FCF). This drawback leads to an inaccurate performance evaluation of wireless communication systems sensitive to the FCF. To cope with this problem, we present a simple solution by doubling the channel's sampling rate. The benefits of this solution are demonstrated with some exemplary simulation results. Copyright © 2008 John Wiley & Sons, Ltd.

Low-Complexity LMMSE-Based MIMO-OFDM Channel Estimation Via Angle-Domain Processing

In many situations, multiple-input-multiple-output with orthogonal frequency division multiplexing (MIMO-OFDM) channels tend to be spatially correlated due, for example, to limited scattering. Prior knowledge of this channel spatial correlation and the channel frequency correlation can be exploited by using the linear minimum-mean-square-error (LMMSE) technique. However, the complexity of the 2-D LMMSE technique, which fully utilizes both the channel spatial and frequency correlation is quite high. To solve this problem, this paper presents and analyzes several low-complexity, suboptimal, approximated LMMSE channel estimation techniques in the angle domain, where the channel model lends itself to a physical interpretation. The choice of angle-domain techniques is largely dependent on the extent of channel stochastic information (e.g., channel correlation or power) that is available to the receiver. Nevertheless, all the proposed angle-domain techniques have much lower complexity compared to the 2-D LMMSE technique. Further, all the angle-domain techniques improve over the conventional least square (LS) technique for all the typical MIMO-OFDM models under consideration. More importantly, our simulation results show that the angle-domain quasi 1-D (Ql-D) LMMSE technique can achieve similar performance compared to the 2-D LMMSE technique for all typical MIMO-OFDM models with significantly lower complexity.

Further Results Concerning the Effect of Frequency-Selective Fading on Differentially Coherent Matched Filter Receivers

In this correspondence, error probabilities are calculated for binary DPSK communication through frequency-selective channels with predetection diversity matched filter reception. A method due to Bello and Nelin is used to carry out the calculations. Error probabilities are calculated for three different combinations of signaling pulse shape and channel frequency correlation function. One of these cases was investigated previously by Bello and Nelin, but some errors were made in their calculations. It is shown that for each of the three cases, an irreducible error probability exists that is proportional to the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2L</tex> power of the relative data rate (where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</tex> is the order of diversity) when the data rate is small. Also, when the results for the three cases are suitably compared, it is found that the error probabilities are more sensitive to the shape of the signaling pulse than to the shape of the channel frequency correlation function.