arXiv subjects

Chintha Tellambura

Publications and source records attributed to Chintha Tellambura.

At least 55 records · Page 3Linked to original sources

arXiv2022

New Antenna Selection Schemes for Full-Duplex Cooperative MIMO-NOMA Systems

In this paper, we address the antenna selection (AS) problem in full-duplex (FD) cooperative non-orthogonal multiple access (NOMA) systems, where a multi-antenna FD relay bridges the connection between the multi-antenna base station and NOMA far user. Specifically, two AS schemes, namely max-$\SUu$ and max-$\SUuu$, are proposed to maximize the end-to-end signal-to-interference-plus-noise ratio at either or both near and far users, respectively. Moreover, a two-stage AS scheme, namely quality-of-service (QoS) provisioning scheme, is designed to realize a specific rate at the far user while improving the near user's rate. To enhance the performance of the QoS provisioning AS scheme, the idea of dynamic antenna clustering is applied at the relay to adaptively partition the relay's antennas into transmit and receive subsets. The proposed AS schemes' exact outage probability and achievable rate expressions are derived. To provide more insight, closed-form asymptotic outage probability expressions for the max-$\SUu$ and max-$\SUuu$ AS schemes are obtained. Our results show that while the QoS provisioning AS scheme can deliver a near-optimal performance for static antenna setup at the relay, it provides up to $12\%$ average sum rate gain over the optimum AS selection with fixed antenna setup.

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arXiv2020

Rate Analysis of Cell-Free Massive MIMO-NOMA With Three Linear Precoders

Although the hybrid of cell-free (CF) massive multiple-input multiple-output (MIMO) and non-orthogonal multiple access (NOMA) promises massive spectral efficiency gains, the type of precoders employed at the access points (APs) impacts the gains. In this paper, we thus comprehensively evaluate the system performance with maximum ratio transmission (MRT), full-pilot zero-forcing (fpZF) and modified regularized ZF (mRZF) precoders. We derive their closed-form sum rate expressions by considering Rayleigh fading channels, the effects of intra-cluster pilot contamination, inter-cluster interference, and imperfect successive interference cancellation (SIC). Our results reveal that this system supports significantly more users simultaneously at the same coherence interval compared to its OMA equivalent. However, intra-cluster pilot contamination and imperfect SIC degrade the system performance when the number of users is low. Moreover, with perfect SIC, mRZF and fpZF significantly outperform MRT. Also, we show that this system with either mRZF or fpZF precoding outperforms OMA systems with MRT. The analytical findings are verified by numerical results.

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arXiv2020

A PAPR Reduction Method Based on Artificial Bee Colony Algorithm for OFDM Signals

One of the major drawbacks of orthogonal frequency division multiplexing (OFDM) signals is the high peak to average power ratio (PAPR) of the transmitted signal. Many PAPR reduction techniques have been proposed in the literature, among which, partial transmit sequence (PTS) technique has been taken considerable investigation.However, PTS technique requires an exhaustive search over all combinations of allowed phase factors, whose complexity increases exponentially with the number of sub-blocks. In this paper, a newly suboptimal method based on modified artificial bee colony (ABC-PTS) algorithm is proposed to search the better combination of phase factors. The ABC-PTS algorithm can significantly reduce the computational complexity for larger PTS subblocks and offers lower PAPR at the same time. Simulation results show that the ABC-PTS algorithm is an efficient method to achieve significant PAPR reduction.

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arXiv2020

Genetic Algorithm Based Nearly Optimal Peak Reduction Tone Set Selection for Adaptive Amplitude Clipping PAPR Reduction

In tone reservation (TR) based OFDM systems, the peak to average power ratio (PAPR) reduction performance mainly depends on the selection of the peak reduction tone (PRT) set and the optimal target clipping level. Finding the optimal PRT set requires an exhaustive search of all combinations of possible PRT sets, which is a nondeterministic polynomial-time (NP-hard) problem, and this search is infeasible for the number of tones used in practical systems. The existing selection methods, such as the consecutive PRT set, equally spaced PRT set and random PRT set, perform poorly compared to the optimal PRT set or incur high computational complexity. In this paper, an efficient scheme based on genetic algorithm (GA) with lower computational complexity is proposed for searching a nearly optimal PRT set. While TR-based clipping is simple and attractive for practical implementation, determining the optimal target clipping level is difficult. To overcome this problem, we propose an adaptive clipping control algorithm.Simulation results show that our proposed algorithms efficiently obtain a nearly optimal PRT set and good PAPR reductions.

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arXiv2020

PAPR Reduction Method Based on Parametric Minimum Cross Entropy for OFDM Signals

The partial transmit sequence (PTS) technique has received much attention in reducing the high peak to average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, the PTS technique requires an exhaustive search of all combinations of the allowed phase factors, and the search complexity increases exponentially with the number of sub-blocks. In this paper, a novel method based on parametric minimum cross entropy (PMCE) is proposed to search the optimal combination of phase factors. The PMCE algorithm not only reduces the PAPR significantly, but also decreases the computational complexity. The simulation results show that it achieves more or less the same PAPR reduction as that of exhaustive search.

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arXiv2019

Channel Estimation for Wireless Communication Systems Assisted by Large Intelligent Surfaces

In this letter, the channel estimation problem is studied for wireless communication systems assisted by large intelligent surface. Due to features of assistant channel, channel estimation (CE) problem for the investigated system is shown as a constrained estimation error minimization problem, which differs from traditional CE problems. A Lagrange multiplier and dual ascent-based estimation scheme is then designed to obtain a closed-form solution for the estimator iteratively. Moreover, the Cramer-Rao lower bounds are deduced for performance evaluation. Simulation results show that the designed scheme could improve estimation accuracy up to 18%, compared with least square method in low signal-to-noise ratio regime.

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arXiv2019

Full-Duplex GFDM Radio Transceivers in the Presence of Phase Noise, CFO and IQ Imbalance

This paper addresses the performance of a full-duplex (FD) generalized frequency division multiplexing (GFDM) transceiver in the presence of radio frequency (RF) impairments including phase noise, carrier frequency offset (CFO) and in-phase (I) and quadrature (Q) imbalance. We study analog and digital self-interference (SI) cancellation and develop a complementary SI suppression method. Closed-form solutions for the residual SI power and the desired signal power and signal-to-interference ratio (SIR) are provided. Simulation results show that the RF impairments degrade SI cancellation and FD GFDM is more sensitive to them compares to FD orthogonal frequency division multiplexing (OFDM). Hence, we propose an FD GFDM receiver filter for maximizing the SIR. Significantly, it achieves 25 dB higher SIR than FD OFDM transceiver.

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arXiv2019

Eigenvalue Based Detection of a Signal in Colored Noise: Finite and Asymptotic Analyses

Signal detection in colored noise with an unknown covariance matrix has a myriad of applications in diverse scientific/engineering fields. The test statistic is the largest generalized eigenvalue (l.g.e.) of the whitened sample covariance matrix, which is constructed via $m$-dimensional $p $ signal-plus-noise samples and $m$-dimensional $n $ noise-only samples. A finite dimensional characterization of this statistic under the alternative hypothesis has hitherto been an open problem. We answer this problem by deriving cumulative distribution function (c.d.f.) of this l.g.e. via the powerful orthogonal polynomial approach, exploiting the deformed Jacobi unitary ensemble (JUE). Two special cases and an asymptotic version of the c.d.f. are also derived. With this new c.d.f., we comprehensively analyze the receiver operating characteristics (ROC) of the detector. Importantly, when the noise-only covariant matrix is nearly rank deficient (i.e., $ m=n$), we show that (a) when $m$ and $p$ increase such that $m/p$ is fixed, at each fixed signal-to-noise ratio (SNR), there exists an optimal ROC profile. We also establish a tight approximation of it; and (b) asymptotically, reliable signal detection is always possible (no matter how weak the signal is) if SNR scales with $m$.

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arXiv2019

Detection of a Signal in Colored Noise: A Random Matrix Theory Based Analysis

This paper investigates the classical statistical signal processing problem of detecting a signal in the presence of colored noise with an unknown covariance matrix. In particular, we consider a scenario where m-dimensional p possible signal-plus-noise samples and m-dimensional n noise-only samples are available at the detector. Then the presence of a signal can be detected using the largest generalized eigenvalue (l.g.e.) of the so called whitened sample covariance matrix. This amounts to statistically characterizing the maximum eigenvalue of the deformed Jacobi unitary ensemble (JUE). To this end, we employ the powerful orthogonal polynomial approach to determine a new finite dimensional expression for the cumulative distribution function (c.d.f.) of the l.g.e. of the deformed JUE. This new c.d.f. expression facilitates the further analysis of the receiver operating characteristics (ROC) of the detector. It turns out that, for m=n, when m and p increase such that m/p attains a fixed value, there exists an optimal ROC profile corresponding to each fixed signal-to-noise ratio (SNR). In this respect, we have established a tight approximation for the corresponding optimal ROC profile.

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arXiv2018

Outage Analysis of $2\times2 $ MIMO-MRC in Correlated Rician Fading

This paper addresses one of the classical problems in random matrix theory-- finding the distribution of the maximum eigenvalue of the correlated Wishart unitary ensemble. In particular, we derive a new exact expression for the cumulative distribution function (c.d.f.) of the maximum eigenvalue of a $2\times 2$ correlated non-central Wishart matrix with rank-$1$ mean. By using this new result, we derive an exact analytical expression for the outage probability of $2\times 2$ multiple-input multiple-output maximum-ratio-combining (MIMO-MRC) in Rician fading with transmit correlation and a strong line-of-sight (LoS) component (rank-$1$ channel mean). We also show that the outage performance is affected by the relative alignment of the eigen-spaces of the mean and correlation matrices. In general, when the LoS path aligns with the least eigenvector of the correlation matrix, in the {\it high} transmit signal-to-noise ratio (SNR) regime, the outage gradually improves with the increasing correlation. Moreover, we show that as $K$ (Rician factor) grows large, the outage event can be approximately characterized by the c.d.f. of a certain Gaussian random variable.

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arXiv2018

Closed-Form Word Error Rate Analysis for Successive Interference Cancellation Decoders

We consider the estimation of an integer vector $\hbx\in \mathbb{Z}^n$ from the linear observation $\y=\A\hbx+\v$, where $\A\in\mathbb{R}^{m\times n}$ is a random matrix with independent and identically distributed (i.i.d.) standard Gaussian $\mathcal{N}(0,1)$ entries, and $\v\in \mathbb{R}^m$ is a noise vector with i.i.d. $\mathcal{N}(0,σ^2 )$ entries with given $σ$. In digital communications, $\hbx$ is typically uniformly distributed over an $n$-dimensional box $\mathcal{B}$. For this estimation problem, successive interference cancellation (SIC) decoders are popular due to their low complexity, and a detailed analysis of their word error rates (WERs) is highly useful. In this paper, we derive closed-form WER expressions for two cases: (1) $\hbx\in \mathbb{Z}^n$ is fixed and (2) $\hbx$ is uniformly distributed over $\mathcal{B}$. We also investigate some of their properties in detail and show that they agree closely with simulated word error probabilities.

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arXiv2017

Outage Analysis of Ambient Backscatter Communication Systems

This paper addresses the problem of outage characterization of an ambient backscatter communication system with a pair of passive tag and reader. In particular, an exact expression for the effective channel distribution is derived. Then, the outage probability at the reader is analyzed rigorously. Since the expression contains an infinite sum, a tight truncation error bound has been derived to facilitate precise numerical evaluations. Furthermore, an asymptotic expression is provided for high signal-to-noise ratio (SNR) regime.

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arXiv2017

On the Success Probability of the Box-Constrained Rounding and Babai Detectors

In communications, one frequently needs to detect a parameter vector $\hbx$ in a box from a linear model. The box-constrained rounding detector $\x^\sBR$ and Babai detector $\x^\sBB$ are often used to detect $\hbx$ due to their high probability of correct detection, which is referred to as success probability, and their high efficiency of implimentation. It is generally believed that the success probability $P^\sBR$ of $\x^\sBR$ is not larger than the success probability $P^\sBB$ of $\x^\sBB$. In this paper, we first present formulas for $P^\sBR$ and $P^\sBB$ for two different situations: $\hbx$ is deterministic and $\hbx$ is uniformly distributed over the constraint box. Then, we give a simple example to show that $P^\sBR$ may be strictly larger than $P^\sBB$ if $\hbx$ is deterministic, while we rigorously show that $P^\sBR\leq P^\sBB$ always holds if $\hbx$ is uniformly distributed over the constraint box.

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arXiv2017

Storage Allocation for Multi-Class Distributed Data Storage Systems

Distributed storage systems (DSSs) provide a scalable solution for reliably storing massive amounts of data coming from various sources. Heterogeneity of these data sources often means different data classes (types) exist in a DSS, each needing a different level of quality of service (QoS). As a result, efficient data storage and retrieval processes that satisfy various QoS requirements are needed. This paper studies storage allocation, meaning how data of different classes must be spread over the set of storage nodes of a DSS. More specifically, assuming a probabilistic access to the storage nodes, we aim at maximizing the weighted sum of the probability of successful data recovery of data classes, when for each class a minimum QoS (probability of successful recovery) is guaranteed. Solving this optimization problem for a general setup is intractable. Thus, we find the optimal storage allocation when the data of each class is spread minimally over the storage nodes, i.e. minimal spreading allocation (MSA). Using upper bounds on the performance of the optimal storage allocation, we show that the optimal MSA allocation approaches the optimal performance in many practical cases. Computer simulations are also presented to better illustrate the results.

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arXiv2016

A general framework for weighted sum-rate and common-rate optimization

In this paper, we propose a framework for solving a class of optimization problems encountered in a range of power allocation problems in wireless relay networks. In particular, power allocation for weighted sum-rate and common-rate optimization problems fall in this framework. Subject to some conditions on the region of feasible powers, the optimal solutions are analytically found. The optimization problems are posed in a general form and their solutions are shown to have applications in a number of practical scenarios. Numerical results verify the optimality of the analytical approach.

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arXiv2016

Uplink and Downlink Rate Analysis of a Full-Duplex C-RAN with Radio Remote Head Association

We characterize the uplink (UL) and downlink (DL) rates of a full-duplex cloud radio access network (C-RAN) with all participate and single best remote radio head (RRH) association schemes. Specifically, multi-antenna equipped RRHs distributed according to a Poisson point process is assumed. The UL and DL sum rate of the single best RRH association scheme is maximized using receive and transmit beamformer designs at the UL and DL RRHs, respectively. In the case of the single best strategy, we study both optimum and sub-optimum schemes based on maximum ratio combining/maximal ratio transmission (MRC/MRT) and zero-forcing/MRT (ZF/MRT) processing. Numerical results show that significant performance improvements can be achieved by using the full-duplex mode as compared to the half-duplex mode. Moreover, the choice of the beamforming design and the RRH association scheme have a major influence on the achievable full-duplex gains.

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arXiv2016

Full-Duplex Cloud-RAN with Uplink/Downlink Remote Radio Head Association

This paper considers a cloud radio access network (C-RAN) where spatially distributed remote radio heads (RRHs) communicate with a full-duplex user. In order to reflect a realistic scenario, the uplink (UL) and downlink (DL) RRHs are assumed to be equipped with multiple antennas and distributed according to a Poisson point process. We consider all participate and nearest RRH association schemes with distributed beamforming in the form of maximum ratio combining/maximal ratio transmission (MRC/MRT) and zero-forcing/MRT(ZF/MRT) processing. We derive analytical expressions useful to compare the average sum rate among association schemes as a function of the number of RRHs antennas and density of the UL and DL RRHs. Numerical results show that significant performance improvements can be achieved by using the full-duplex mode as compared to the half-duplex mode, while the choice of the beamforming design as well as the RRH association scheme plays a critical role in determining the full-duplex gains.

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arXiv2015

Full-Duplex Radio for Uplink/Downlink Wireless Access with Spatially Random Nodes

A full-duplex (FD) multiple antenna access point (AP) communicating with single antenna half-duplex (HD) spatially random users to support simultaneous uplink (UL)/downlink (DL) transmissions is investigated. Since FD nodes are inherently constrained by the loopback interference (LI), we study precoding schemes for the AP based on maximum ratio combining (MRC)/maximal ratio transmission (MRT), zero-forcing and the optimal scheme for UL and DL sum rate maximization using tools from stochastic geometry. In order to shed insights into the system's performance, simple expressions for single antenna/perfect LI cancellation/negligible internode interference cases are also presented. We show that FD precoding at AP improves the UL/DL sum rate and hence a doubling of the performance of the HD mode is achievable. In particular, our results show that these impressive performance gains remain substantially intact even if the LI cancellation is imperfect. Furthermore, relative performance gap between FD and HD modes increases as the number of transmit/receive antennas becomes large, while with the MRC/MRT scheme, increasing the receive antenna number at FD AP, is more beneficial in terms of sum rate than increasing the transmit antenna number.

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