1,676 research outputs found
A Robust Nonlinear Beamforming Assisted Receiver for BPSK Signalling
Nonlinear beamforming designed for wireless communications is investigated. We derive the optimal nonlinear beamforming assisted receiver designed for binary phase shift keying (BPSK) signalling. It is shown that this optimal Bayesian beamformer significantly outperforms the classic linear minimum mean square error (LMMSE) beamformer at the expense of an increased complexity. Hence the achievable user capacity of the wireless system invoking the proposed beamformer is substantially enhanced. In particular, when the angular separation between the desired and interfering signals is below a certain threshold, a linear beamformer will fail while a nonlinear beamformer can still perform adequately. Blockadaptive implementation of the optimal Bayesian beamformer can be realized using a Radial Basis Function network based on the Relevance Vector Machine (RVM) for classification, and a recursive sample-by-sample adaptation is proposed based on an enhanced ?-means clustering aided recursive least squares algorithm
Directional Relays for Multi-Hop Cooperative Cognitive Radio Networks
In this paper, we investigate power allocation and beamforming in a relay assisted cognitive radio (CR) network. Our objective is to maximize the performance of the CR network while limiting interference in the direction of the primary users (PUs). In order to achieve these goals, we first consider joint power allocation and beamforming for cognitive nodes in direct links. Then, we propose an optimal power allocation strategy for relay nodes in indirect transmissions. Unlike the conventional cooperative relaying networks, the applied relays are equipped with directional antennas to further reduce the interference to PUs and meet the CR network requirements. The proposed approach employs genetic algorithm (GA) to solve the optimization problems. Numerical simulation results illustrate the quality of service (QoS) satisfaction in both primary and secondary networks. These results also show that notable improvements are achieved in the system performance if the conventional omni-directional relays are replaced with directional ones
Initial Access in 5G mm-Wave Cellular Networks
The massive amounts of bandwidth available at millimeter-wave frequencies
(roughly above 10 GHz) have the potential to greatly increase the capacity of
fifth generation cellular wireless systems. However, to overcome the high
isotropic pathloss experienced at these frequencies, high directionality will
be required at both the base station and the mobile user equipment to establish
sufficient link budget in wide area networks. This reliance on directionality
has important implications for control layer procedures. Initial access in
particular can be significantly delayed due to the need for the base station
and the user to find the proper alignment for directional transmission and
reception. This paper provides a survey of several recently proposed techniques
for this purpose. A coverage and delay analysis is performed to compare various
techniques including exhaustive and iterative search, and Context Information
based algorithms. We show that the best strategy depends on the target SNR
regime, and provide guidelines to characterize the optimal choice as a function
of the system parameters.Comment: 6 pages, 3 figures, 3 tables, 15 references, submitted to IEEE COMMAG
201
Massive MIMO for Internet of Things (IoT) Connectivity
Massive MIMO is considered to be one of the key technologies in the emerging
5G systems, but also a concept applicable to other wireless systems. Exploiting
the large number of degrees of freedom (DoFs) of massive MIMO essential for
achieving high spectral efficiency, high data rates and extreme spatial
multiplexing of densely distributed users. On the one hand, the benefits of
applying massive MIMO for broadband communication are well known and there has
been a large body of research on designing communication schemes to support
high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT)
is still a developing topic, as IoT connectivity has requirements and
constraints that are significantly different from the broadband connections. In
this paper we investigate the applicability of massive MIMO to IoT
connectivity. Specifically, we treat the two generic types of IoT connections
envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable
low-latency communication (URLLC). This paper fills this important gap by
identifying the opportunities and challenges in exploiting massive MIMO for IoT
connectivity. We provide insights into the trade-offs that emerge when massive
MIMO is applied to mMTC or URLLC and present a number of suitable communication
schemes. The discussion continues to the questions of network slicing of the
wireless resources and the use of massive MIMO to simultaneously support IoT
connections with very heterogeneous requirements. The main conclusion is that
massive MIMO can bring benefits to the scenarios with IoT connectivity, but it
requires tight integration of the physical-layer techniques with the protocol
design.Comment: Submitted for publicatio
Improving CubeSat downlink capacity with active phased array antennas
Master's Project (M.S.) University of Alaska Fairbanks, 2017Power budgets on small satellites are restricted by the limited surface area for solar panels. This limits the power available for radio communications, which constrains the downlink budget. The limited transmit power translates to low downlink data rates on small satellites. Antenna gain from directive antennas may be a power efficient way of improving the downlink budget, thereby increasing the downlink rate of small satellites. This project focuses on the design and development of a prototype low-power, electrically-steered S-band phased array RF front-end suitable for a CubeSat that could efficiently increase the EIRP, permitting higher data rates. A prototype of the array has been constructed and tested in an anechoic chamber. The four element array provides a minimum gain of 2.5 dB and average gain of 5 dB compared to a single patch antenna element with a 5W power envelope across a range of up to 60 degrees from broadside of the array
Block-Online Multi-Channel Speech Enhancement Using DNN-Supported Relative Transfer Function Estimates
This work addresses the problem of block-online processing for multi-channel
speech enhancement. Such processing is vital in scenarios with moving speakers
and/or when very short utterances are processed, e.g., in voice assistant
scenarios. We consider several variants of a system that performs beamforming
supported by DNN-based voice activity detection (VAD) followed by
post-filtering. The speaker is targeted through estimating relative transfer
functions between microphones. Each block of the input signals is processed
independently in order to make the method applicable in highly dynamic
environments. Owing to the short length of the processed block, the statistics
required by the beamformer are estimated less precisely. The influence of this
inaccuracy is studied and compared to the processing regime when recordings are
treated as one block (batch processing). The experimental evaluation of the
proposed method is performed on large datasets of CHiME-4 and on another
dataset featuring moving target speaker. The experiments are evaluated in terms
of objective and perceptual criteria (such as signal-to-interference ratio
(SIR) or perceptual evaluation of speech quality (PESQ), respectively).
Moreover, word error rate (WER) achieved by a baseline automatic speech
recognition system is evaluated, for which the enhancement method serves as a
front-end solution. The results indicate that the proposed method is robust
with respect to short length of the processed block. Significant improvements
in terms of the criteria and WER are observed even for the block length of 250
ms.Comment: 10 pages, 8 figures, 4 tables. Modified version of the article
accepted for publication in IET Signal Processing journal. Original results
unchanged, additional experiments presented, refined discussion and
conclusion
- …