16 research outputs found
Feedback Subsampling in Temporally-Correlated Slowly-Fading Channels using Quantized CSI
This paper studies the problem of feedback subsampling in temporally-correlated wireless networks utilizing quantized channel state information (CSI). Under both peak and average power constraints, the system data transmission efficiency is studied in two scenarios. First, we focus on the case where the codewords span one fading block. In the second scenario, the throughput is determined for piecewise slowly-fading channels where the codewords are so long that a finite number of correlated gain realizations are experienced during each codeword transmission. Considering different temporal correlation conditions in both scenarios, substantial throughput increment is observed with feedback rates well below 1 bit per slot
Reinforcement-based data transmission in temporally-correlated fading channels: Partial CSIT scenario
Reinforcement algorithms refer to the schemes where the results of the
previous trials and a reward-punishment rule are used for parameter setting in
the next steps. In this paper, we use the concept of reinforcement algorithms
to develop different data transmission models in wireless networks. Considering
temporally-correlated fading channels, the results are presented for the cases
with partial channel state information at the transmitter (CSIT). As
demonstrated, the implementation of reinforcement algorithms improves the
performance of communication setups remarkably, with the same feedback
load/complexity as in the state-of-the-art schemes.Comment: Accepted for publication in ISWCS 201
Predictor Antenna Systems: Exploiting Channel State Information for Vehicle Communications
Vehicle communication is one of the most important use cases in the fifth
generation of wireless networks (5G). The growing demand for quality of service
(QoS) characterized by performance metrics, such as spectrum efficiency, peak
data rate, and outage probability, is mainly limited by inaccurate
prediction/estimation of channel state information (CSI) of the rapidly
changing environment around moving vehicles. One way to increase the prediction
horizon of CSI in order to improve the QoS is deploying predictor antennas
(PAs). A PA system consists of two sets of antennas typically mounted on the
roof of a vehicle, where the PAs positioned at the front of the vehicle are
used to predict the CSI observed by the receive antennas (RAs) that are aligned
behind the PAs. In realistic PA systems, however, the actual benefit is
affected by a variety of factors, including spatial mismatch, antenna
utilization, temporal correlation of scattering environment, and CSI estimation
error. This thesis investigates different resource allocation schemes for the
PA systems under practical constraints.Comment: Licentiate thesis, Chalmers University of Technolog
Predictor Antenna Systems: Exploiting Channel State Information for Vehicle Communications
Vehicle communication is one of the most important use cases in the fifth generation of wireless networks (5G).\ua0 The growing demand for quality of service (QoS) characterized by performance metrics, such as spectrum efficiency, peak data rate, and outage probability, is mainly limited by inaccurate prediction/estimation of channel state information (CSI) of the rapidly changing environment around moving vehicles. One way to increase the prediction horizon of CSI in order to improve the QoS is deploying predictor antennas (PAs).\ua0 A PA system consists of two sets of antennas typically mounted on the roof of a vehicle, where the PAs positioned at the front of the vehicle are used to predict the CSI observed by the receive antennas (RAs) that are aligned behind the PAs. In realistic PA systems, however, the actual benefit is affected by a variety of factors, including spatial mismatch, antenna utilization, temporal correlation of scattering environment, and CSI estimation error. This thesis investigates different resource allocation schemes for the PA systems under practical constraints, with main contributions summarized as follows.First, in Paper A, we study the PA system in the presence of the so-called spatial mismatch problem, i.e., when the channel observed by the PA is not exactly the same as the one experienced by the RA. We derive closed-form expressions for the throughput-optimized rate adaptation, and evaluate the system performance in various temporally-correlated conditions for the scattering environment. Our results indicate that PA-assisted adaptive rate adaptation leads to a considerable performance improvement, compared to the cases with no rate adaptation. Then, to simplify e.g., various integral calculations as well as different operations such as parameter optimization, in Paper B, we propose a semi-linear approximation of the Marcum Q-function, and apply the proposed approximation to the evaluation of the PA system. We also perform deep analysis of the effect of various parameters such as antenna separation as well as CSI estimation error. As we show, our proposed approximation scheme enables us to analyze PA systems with high accuracy.The second part of the thesis focuses on improving the spectral efficiency of the PA system by involving the PA into data transmission. In Paper C, we analyze the outage-limited performance of PA systems using hybrid automatic repeat request (HARQ). With our proposed approach, the PA is used not only for improving the CSI in the retransmissions to the RA, but also for data transmission in the initial round.\ua0 As we show in the analytical and the simulation results, the combination of PA and HARQ protocols makes it possible to improve the spectral efficiency and adapt transmission parameters to mitigate the effect of spatial mismatch
On the Required Number of Antennas in a Point-to-Point Large-but-Finite MIMO System: Outage-Limited Scenario
This paper investigates the performance of the point-to-point
multiple-input-multiple-output (MIMO) systems in the presence of a large but
finite numbers of antennas at the transmitters and/or receivers. Considering
the cases with and without hybrid automatic repeat request (HARQ) feedback, we
determine the minimum numbers of the transmit/receive antennas which are
required to satisfy different outage probability constraints. Our results are
obtained for different fading conditions and the effect of the power amplifiers
efficiency on the performance of the MIMO-HARQ systems is analyzed. Moreover,
we derive closed-form expressions for the asymptotic performance of the
MIMO-HARQ systems when the number of antennas increases. Our analytical and
numerical results show that different outage requirements can be satisfied with
relatively few transmit/receive antennas.Comment: Under review in IEEE Transactions on Communication
On the Performance of MIMO-ARQ Systems with Channel State Information at the Receiver
This paper investigates the performance of multiple-input-multiple-output (MIMO) systems in the presence of automatic repeat request (ARQ) feedback. We show that, for a large range of performance metrics, the data transmission efficiency of the ARQ schemes is determined by a set of parameters which are scheme-dependent and not metric-dependent. Then, the results are used to study different aspects of MIMO-ARQ such as the effect of nonlinear power amplifiers, large-scale MIMO-ARQ, adaptive power allocation and different data communication models. The results, which are valid for various forward and feedback channel models, show the efficiency of the MIMO-ARQ techniques in different conditions
Towards Context Information-based High-Performing Connectivity in Internet of Vehicle Communications
Internet-of-vehicles (IoV) is one of the most important use cases in the fifth generation (5G) of wireless networks and beyond. Here, IoV communications refer to two types of scenarios: serving the in-vehicle users with moving relays (MRs); and supporting vehicle-to-everything (V2X) communications for, e.g., connected vehicle functionalities. Both of them can be achieved by transceivers on top of vehicles with growing demand for quality of service (QoS), such as spectrum efficiency, peak data rate, and coverage probability. However, the performance of MRs and V2X is limited by challenges such as the inaccurate prediction/estimation of the channel state information (CSI), beamforming mismatch, and blockages. Knowing the environment and utilizing such context information to assist communication could alleviate these issues. This thesis investigates various context information-based performance enhancement schemes for IoV networks, with main contributions listed as follows.In order to mitigate the channel aging issue, i.e., the CSI becomes inaccurate soon at high speeds, the first part of the thesis focuses on one way to increase the prediction horizon of CSI in MRs: predictor antennas (PAs). A PA system is designed as a system with two sets of antennas on the roof of a vehicle, where the PAs positioned at the front of the vehicle are used to predict the CSI observed by the receive antennas (RAs) that are aligned behind the PAs. In PA systems, however, the benefit is affected by a variety of factors. For example, 1) spatial mismatch between the point where the PA estimates the channel and the point where the RA reaches several time slots later, 2) antenna utilization efficiency of the PA, 3) temporal evolution, and 4) estimation error of the PA-base station (BS) channel. First, in Paper A, we study the PA system in the presence of the spatial mismatch problem, and propose an analytical channel model which is used for rate adaptation. In paper B, we propose different approximation schemes for the analytical investigation of PA systems, and study the effect of different parameters on the network performance. Then, involving PAs into data transmission, Paper C and Paper D analyze the outage- and the delay-limited performance of PA systems using hybrid automatic repeat request (HARQ), respectively. As we show in the analytical and the simulation results in Papers C-D, the combination of PA and HARQ protocols makes it possible to improve spectral efficiency and adapt the transmission parameters to mitigate the effect of spatial mismatch. Finally, a review of PA studies in the literature, the challenges and potentials of PA as well as some to-be-solved issues are presented in Paper E.The second part of the thesis focuses on using advanced technologies to further improve the MR/IoV performance. In Paper F, a cooperative PA scheme in IoV networks is proposed to mitigate both the channel aging effect and blockage sensitivity in millimeter-wave channels by collaborative vehicles and BS handover. Then, in Paper G, we study the potentials and challenges of dynamic blockage pre-avoidance in IoV networks
Goal-Oriented Quantization: Analysis, Design, and Application to Resource Allocation
In this paper, the situation in which a receiver has to execute a task from a
quantized version of the information source of interest is considered. The task
is modeled by the minimization problem of a general goal function for
which the decision has to be taken from a quantized version of the
parameters . This problem is relevant in many applications e.g., for radio
resource allocation (RA), high spectral efficiency communications, controlled
systems, or data clustering in the smart grid. By resorting to high resolution
(HR) analysis, it is shown how to design a quantizer that minimizes the gap
between the minimum of (which would be reached by knowing perfectly)
and what is effectively reached with a quantized . The conducted formal
analysis both provides quantization strategies in the HR regime and insights
for the general regime and allows a practical algorithm to be designed. The
analysis also allows one to provide some elements to the new and fundamental
problem of the relationship between the goal function regularity properties and
the hardness to quantize its parameters. The derived results are discussed and
supported by a rich numerical performance analysis in which known RA goal
functions are studied and allows one to exhibit very significant improvements
by tailoring the quantization operation to the final task