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Massive MIMO systems, where base stations are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of users increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this work, we propose a random access procedure that resolves collisions and also performs timing, channel, and power estimation...
In this paper we consider a constant envelope pilot signal based carrier frequency offset (CFO) estimation in massive multiple-input multiple-output (MIMO) systems. The proposed algorithm performs spatial averaging on the periodogram of the received pilots across the base station (BS) antennas. Our study reveals that the proposed algorithm has complexity only linear in (the number of BS antennas)...
Two new non-data-aided (NDA) signal-to-noise ratio (SNR) estimators for multiple antenna systems are presented. The proposed estimators rely on higher- order moments of the received signal and employ the time-diversity of the fading channel. While one requires a priori knowledge about the number of transmit antennas, the other estimates the SNR without such knowledge. The performance of the proposed...
In modern cognitive ratio systems, the spectrum is becoming increasingly crowded and expensive; thus spectrum sensing becomes more important than ever before. Traditional spectrum sensing assumes Gaussian noise (or of other given distributions) in general. However when secondary users (SUs) have no prior information about the measurement distributions, the spectrum sensing schemes assuming given distribution...
Data-driven solutions to Electric Vehicle (EV) range estimation is attracting attention recently due to the prevalence of Internet of Things (IoT). However, there raise the Big Data problems with the increased volume and number of sensory sources of unstructured data collected from the EV equipped with In-Vehicle Networks. This means that traditional statistical analysis and Machine Learning tools...
In this paper, we have proposed an iterative space alternating generalized expectation maximization (SAGE) based semi-blind channel estimation technique for massive multiple-input multiple-output (MIMO) system in multi-cell pilot contamination prone scenario. The benefits of massive MIMO depend largely on the accuracy of channel state information (CSI) available at the base station (Transmitter)....
In this paper, we study the optimum sensing of a time-varying random event with a sensor powered by energy harvesting devices. The system aims at reconstructing a band-unlimited continuous-time random process by using discrete-time samples collected by a sensor. Due to the random nature of the harvested energy, the sensor might not have sufficient energy to perform a sensing operation at a desired...
An optimized relaying method for multi-antennas cooperative networks, estimate-and-forward (EF) strategy for MIMO relay, is proposed and analyzed in this paper. According to our theoretical analysis, it performs like amplify-and-forward (AF) for the low signal noise ratio (SNR) region and behaves like detect-and-forward (DF) for the high SNR region. For the relay networks with a large number of antennas...
This paper presents an OFDMA channel estimation technique that jointly considers the effects of coarse timing error and multipath propagation. Many conventional approaches only consider an optimistic scenario where timing synchronization is perfect and each of the channel delays is an integer number of system samples. In realistic scenarios, timing offsets and echo delays are not integer multiples...
In this paper, we propose a new frequency synchronization scheme for multiuser orthogonal frequency division multiplexing (OFDM) uplink with a large-scale uniform linear array (ULA) at base station (BS). Considering that the incident signal at BS from each user can be restricted within a narrow angular spread, the proposed scheme performs carrier frequency offset (CFO) estimation for each user individually...
Per-flow traffic measurement is a fundamental problem in the era of big network data, providing critical information for many practical applications including capacity planning, traffic engineering, data accounting, resource management, and scan/intrusion detection in modern computer networks. It is challenging to design highly compact data structures for approximate per-flow measurements. In this...
A distributed consensus algorithm for estimating the degree distribution of a graph is proposed. The proposed algorithm is based on average consensus and in-network empirical mass function estimation. It is fully distributed in the sense that each node in the network only needs to know its own degree, and nodes do not need to be labeled. The algorithm works for any connected graph structure in the...
In this paper, two novel channel parameter estimation algorithms are proposed under the "wideband assumption" (WBA), where a wavefront varies significantly when traversing through the sensors of an array. The first is a covariance-based algorithm that utilizes the cross-covariance matrix between two subvectors of the received signal vector and its singular value decomposition to reconstruct...
Provisioning of cost-effective Ethernet-based fronthaul by reusing the LAN infrastructure available in most commercial buildings is challenging predominantly in terms of the required bandwidth and synchronization. In contrast to a synchronous fronthaul, a PTP-based Ethernet network must cope with estimation noise introduced by packet delay variation (PDV) for synchronization recovery. The SYNC packet...
This paper presents sparse Bayesian learning (SBL)-based estimation schemes for an approximately sparse wireless multipath channel impulse response (MCIR) in a space-time trellis coded (STTC) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. The proposed schemes consider space-time trellis encoding over consecutive OFDM symbols and employ the multiple...
A majority of 5G verticals have the potential to generate large revenues, but are expected to have strict Quality of Service (QoS) guarantees, and are projected to be delivered as a service chain of multiple, independent operators. Such multi-operator service delivery requires a set of interdependent Service Level Agreements (SLAs) between operators. The amount and aggregation-level of information...
We derive for the first time closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of the joint channel phase, and carrier frequency offset (CFO) estimates from turbo-coded (TC) Pulse-amplitude modulation (PAM) and rectangular-QAM (RQAM) modulated signals over flat-fading channels. After wisely exploiting the properties of Gray mapping, we are able to simplify the log-likelihood...
New waveform candidates are being investigated for the fifth generation wireless systems. Among the promising candidates, generalized frequency division multiplexing (GFDM) offers the flexibility to address a wide range of requirements (e.g. low latency, coarse synchronization, etc.). Due to the non- orthogonality of GFDM, the transmit signal subjects to inter-symbol and inter-carrier interference...
The heart rate variability (HRV) is the variation in the pulsing frequency of the human heart. Measuring this parameter can reveal important information on the real-time interaction between the autonomic nervous system and the cardiocirculatory system. It can provide useful insight on an individual's state of stress or well being even outside a clinical setting, thanks to inexpensive and unobtrusive...
In this paper, we consider the problem of signal-to-noise ratio (SNR) estimation from turbo-coded (TC) PAM and rectangular-QAM (RQAM) modulated signals over flat-fading channels. We derive for the first time closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of the SNR estimates. We exploit the structure of the binary-reflected-Gray-code (BRGC) for bits-to-symbols mapping, so...
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