Vinod Kristem

A Novel, Balanced, and Energy-Efficient Training Method for Receive Antenna Selection

In receive antenna selection (AS), only signals from a subset of the antennas are processed at any time by the limited number of radio frequency (RF) chains available at the receiver. Hence, the transmitter needs to send pilots multiple times to enable the receiver to estimate the channel state of all the antennas and select the best subset. Conventionally, the sensitivity of coherent reception to channel estimation errors has been tackled by boosting the energy allocated to all pilots to ensure accurate channel estimates for all antennas. Energy for pilots received by unselected antennas is mostly wasted, especially since the selection process is robust to estimation errors. In this paper, we propose a novel training method uniquely tailored for AS that transmits one extra pilot symbol that generates accurate channel estimates for the antenna subset that actually receives data. Consequently, the transmitter can selectively boost the energy allocated to the extra pilot. We derive closed-form expressions for the proposed schemes symbol error probability for MPSK and MQAM, and optimize the energy allocated to pilot and data symbols. Through an insightful asymptotic analysis, we show that the optimal solution achieves full diversity and is better than the conventional method.

A Kernel-Power-Density-Based Algorithm for Channel Multipath Components Clustering

Cluster-based channel modeling has been an important trend in the development of channel model, as it maintains accuracy while reducing complexity. Whereas a large number of channel measurements have shown that multipath components (MPCs) are distributed as groups, i.e., clusters, existing clustering algorithms have various drawbacks with respect to complexity, threshold choices, and/or assumptions about prior knowledge. In this paper, a kernel-power-density (KPD)-based algorithm is proposed for MPC clustering. It uses the kernel density of MPCs to incorporate the modeled behavior of MPCs and takes into account the power of the MPCs. Furthermore, the KPD algorithm only considers the

Coherent UWB Ranging in the Presence of Multiuser Interference

K

Ultrawideband MIMO Channel Measurements and Modeling in a Warehouse Environment

nearest MPCs in the density estimation to better identify the local density variations of MPCs. A heuristic approach of cluster merging is used to improve the performance. Both simulation and channel measurements validate the KPD algorithm, and almost no performance degradation is found even with a large number of clusters and large cluster angular spread, which outperforming other algorithms. The KPD algorithm enables applications in multiple-input-multiple-output channels with no prior knowledge about the clusters, such as number and initial locations. It also has a fairly low computational complexity and can be used for cluster-based channel modeling.

3D MIMO Outdoor to Indoor Macro/Micro-Cellular Channel Measurements and Modeling

Roundtrip time-of-arrival (ToA) measurements employing ultra-wideband (UWB) signals can provide high-precision ranging information. However, the accuracy is degraded by multiuser interference (MUI), in particular in the presence of multipath propagation. While the processing gain of time-hopping impulse radio (TH-IR) can be used to suppress the MUI, this is often insufficient. We propose instead a nonlinear processing scheme of TH-IR that effectively suppresses MUI without requiring knowledge of the time-hopping sequences of the interfering users. The principle is that multipath components (MPCs) of interferers do not align closely, for the majority of transmission frames, with the MPCs of the desired signal. Through a judicious choice of algorithm parameters we show that our algorithm is superior to existing (realizable) thresholding and median filter algorithms, and in some cases can even beat genie-aided thresholding algorithms. The performance is robust to both strength and number of the interferers. The results are validated with both standardized 802.15.4a channel models and measured outdoor UWB channels.

Cluster-based analysis of 3D MIMO channel measurement in an urban environment

This paper presents a detailed description of a propagation channel measurement campaign performed in a warehouse environment and provide a comprehensive channel model for this environment. Using a vector network analyzer, we explored both line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios over a 2-8 GHz frequency range. We extracted both small-scale and large-scale channel parameters such as distance-dependent path loss exponent, frequency-dependent path loss exponent, shadowing variance, and amplitude fading statistics of the channel. We also provide the clustering analysis of the channel impulse responses by using a modified Saleh-Valenzuela approach. Our model is validated by comparing the distributions of the root-mean-square (RMS) delay spread obtained from our model and measurement data, respectively. The model developed can be used for realistic performance evaluations of ultrawideband (UWB) communications and localization systems in warehouse environments.

Experimental determination of UWB ranging errors in an outdoor environment

3-dimensional Multiple-Input Multiple-Output (3D MIMO) systems have received great interest recently because of the spatial diversity advantage and capability for full-dimensional beamforming, making them promising candidates for practical realization of massive MIMO. For 3D MIMO system design, it is important to have full characterization of the 3D MIMO propagation channel, i.e., characterize both the elevation and azimuth characteristics of the wireless propagation channel, especially at the base station end. In this paper, we present first results from a measurement campaign for obtaining these characteristics. For those measurements we use a hybrid switched/virtual cylindrical array with 480 antenna elements at the base station (BS), and a switched array with 24 antenna elements at the user equipment (UE). We perform outdoor-to-indoor (O2I) channel measurements in an urban macro-cellular (UMa) and a micro-cellular (UMi) environments. We provide the elevation and azimuth angular spreads at the transmitter and receiver, and study their dependence on the UE height. With the increase in the UE height, the BS elevation spreads decreased from 1.24 deg to 1 deg and 1.15 deg to 0.78 deg respectively for UMa and UMi; the azimuth spreads remained approximately the same (7.5 deg). Based on the measurements done with the UE placed on different floors, we study the feasibility of separating users in the elevation domain. Users were separable in 44% and 54.17% scenarios respectively for the UMa and UMi environments.

Statistical Modeling of Ultrawideband MIMO Propagation Channel in a Warehouse Environment

Massive MIMO (multiple - input - multiple - output) and full-dimensional MIMO systems in next-generation cellular communications systems as well as high-data-rate military systems have garnered considerable attention recently. For the assessment of their performance, knowledge of the 3D propagation channel characteristics, i.e., azimuth and elevation of the multipath components (MPCs) is essential. In this paper, we present first results of a 3D outdoor propagation channel measurement campaign performed in an urban macro-cellular environment. The measurements were performed with a 20 MHz wideband polarimetric MIMO channel sounder centered at 2.53 GHz. At each measurement location, parameters of all MPCs observed were extracted with RIMAX, an iterative maximum likelihood high-resolution algorithm. It was observed that MPCs naturally grouped into clusters. We then present a cluster-based analysis of the propagation channel providing some results of the intra and inter cluster parameters and their relevant statistics. Correlation between all extracted cluster parameters are also provided. Parameters such as elevation and azimuth spread (at the base-station) in this work have been used as input to recent international channel model standardization.

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Ultra-wideband (UWB) technology is a good candidate to provide accurate position information indoors and in dense urban environments where Global Positioning System (GPS) is usually not reliable. This paper provides the results of a UWB ranging measurement campaign carried out in a dense urban environment. Measurements were taken with two different antenna heights in line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. It is observed that the ranging errors increases when the antennas are closer to the ground, and is more significant in NLOS conditions. Also, in NLOS conditions ranging errors of more than 10 meters were observed when the LOS component is completely blocked by a building. Errors of such magnitude are typically not captured by IEEE 802.15.4a CM6 (outdoor NLOS) channel model. Since the conventional thresholding schemes provide bad ranging accuracy in presence of multiuser interference (MUI), we propose a nonlinear processing scheme of time-hopping impulse radio (TH-IR) and apply it to our measurements to show that it gives much better ranging accuracy.

3D MIMO Outdoor-to-Indoor Propagation Channel Measurement

This paper describes an extensive propagation channel measurement campaign in a warehouse environment for line-of-sight (LOS) and nonline-of-sight (NLOS) scenarios. The measurement setup employs a vector network analyzer operating in the 2-8-GHz frequency band combined with an 8 × 8 virtual multiple-input multiple-output (MIMO) antenna array. We develop a comprehensive statistical propagation channel model based on high-resolution extraction of multipath components and subsequent spatiotemporal clustering analysis. The intracluster direction of departure (DoD), direction of arrival (DoA), and the time of arrival (ToA) are independent, both for the LOS and NLOS scenarios. The intracluster DoD and DoA can be approximated by the Laplace distribution, and the intracluster ToA can be approximated by an exponential mixture distribution. The intercluster analysis, however, shows a dependency between the cluster DoD, DoA, and ToA. To capture this dependency, we separately model the clusters caused by single and multiple bounce scattering along the aisles in the warehouse. The intercluster DoD distribution follows a Laplace distribution, while the cluster DoA conditioned on the DoD is approximated by a Gaussian mixture distribution. The model was validated using the capacity and delay-spread values.