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Tharmalingam Ratnarajah

Publications and source records attributed to Tharmalingam Ratnarajah.

At least 37 records · Page 2Linked to original sources

Rate-Energy Balanced Precoding Design for SWIPT based Two-Way Relay Systems

Simultaneous wireless information and power transfer (SWIPT) technique is a popular strategy to convey both information and RF energy for harvesting at receivers. In this regard, we consider a two-way relay system with multiple users and a multi-antenna relay employing SWIPT strategy, where splitting the received signal leads to a rate-energy trade-off. In literature, the works on transceiver design have been studied using computationally intensive and suboptimal convex relaxation based schemes. In this paper, we study the balanced precoder design using chordal distance (CD) decomposition, which incurs much lower complexity, and is flexible to dynamic energy requirements. It is analyzed that given a non-negative value of CD, the achieved harvested energy for the proposed balanced precoder is higher than that for the perfect interference alignment (IA) precoder. The corresponding loss in sum rates is also analyzed via an upper bound. Simulation results add that the IA schemes based on mean-squared error are better suited for the SWIPT maximization than the subspace alignment-based methods.

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Design of Full-Duplex Millimeter-Wave Integrated Access and Backhaul Networks

One of the key technologies for the future cellular networks is full duplex (FD)-enabled integrated access and backhaul (IAB) networks operating in the millimeter-wave (mmWave) frequencies. The main challenge in realizing FD-IAB networks is mitigating the impact of self-interference (SI) in the wideband mmWave frequencies. In this article, we first introduce the 3GPP IAB network architectures and wideband mmWave channel models. By utilizing the subarray-based hybrid precoding scheme at the FD-IAB node, multiuser interference is mitigated using zero-forcing at the transmitter, whereas the residual SI after successfully deploying antenna and analog cancellation is canceled by a minimum mean square error baseband combiner at the receiver. The spectral efficiency (SE) is evaluated for the RF insertion loss (RFIL) with different kinds of phase shifters and channel uncertainty. Simulation results show that, in the presence of the RFIL, the almost double SE, which is close to that obtained from fully connected hybrid precoding, can be achieved as compared to half duplex systems when the uncertainties are of low strength.

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Reinforcement Learning based Per-antenna Discrete Power Control for Massive MIMO Systems

Power consumption is one of the major issues in massive MIMO (multiple input multiple output) systems, causing increased long-term operational cost and overheating issues. In this paper, we consider per-antenna power allocation with a given finite set of power levels towards maximizing the long-term energy efficiency of the multi-user systems, while satisfying the QoS (quality of service) constraints at the end users in terms of required SINRs (signal-to-interference-plus-noise ratio), which depends on channel information. Assuming channel states to vary as a Markov process, the constraint problem is modeled as an unconstraint problem, followed by the power allocation based on Q-learning algorithm. Simulation results are presented to demonstrate the successful minimization of power consumption while achieving the SINR threshold at users.

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Learning to Cache: Distributed Coded Caching in a Cellular Network With Correlated Demands

Design of distributed caching mechanisms is considered as an active area of research due to its promising solution in reducing data load in the backhaul link of a cellular network. In this paper, the problem of distributed content caching in a small-cell Base Stations (sBSs) wireless network that maximizes the cache hit performance is considered. Most of the existing works focus on static demands, however, here, data at each sBS is considered to be correlated across time and sBSs. The caching strategy is assumed to be a weighted combination of past caching strategies. A high probability generalization guarantees on the performance of the proposed caching strategy is derived. The theoretical guarantee provides following insights on obtaining the caching strategy: (i) run regret minimization at each sBS to obtain a sequence of caching strategies across time, and (ii) maximize an estimate of the bound to obtain a set of weights for the caching strategy which depends on the discrepancy. Also, theoretical guarantee on the performance of the LRFU caching strategy is derived. Further, federated learning based heuristic caching algorithm is also proposed. Finally, it is shown through simulations using Movie Lens dataset that the proposed algorithm significantly outperforms LRFU algorithm.

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On Range Sidelobe Reduction for Dual-functional Radar-Communication Waveforms

In this paper, we propose a novel waveform design for multi-input multi-output (MIMO) dual-functional radar-communication systems by taking the range sidelobe control into consideration. In particular, we focus on optimizing the weighted summation of communication and radar metrics under per-antenna power budget. While the formulated optimization problem is non-convex, we develop a first-order descent algorithm by exploiting the manifold structure of its feasible region, which finds a near-optimal solution within a low computational overhead. Numerical results show that the proposed waveform design outperforms the conventional techniques by improving the communication rate while reducing the range sidelobe level.

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Coexistence of MIMO Radar and FD MIMO Cellular Systems with QoS Considerations

In this work, the feasibility of spectrum sharing between a multiple-input multiple-output (MIMO) radar system (RS) and a MIMO cellular system (CS), comprising of a full duplex (FD) base station (BS) serving multiple downlink and uplink users at the same time and frequency is investigated. While a joint transceiver design technique at the CS's BS and users is proposed to maximise the probability of detection (PoD) of the MIMO RS, subject to constraints of quality of service (QoS) of users and transmit power at the CS, null-space based waveform projection is used to mitigate the interference from RS towards CS. In particular, the proposed technique optimises the performance of PoD of RS by maximising its lower bound, which is obtained by exploiting the monotonically increasing relationship of PoD and its non-centrality parameter. Numerical results show the utility of the proposed spectrum sharing framework, but with certain trade-offs in performance corresponding to RS's transmit power, RS's PoD, CS's residual self interference power at the FD BS and QoS of users.

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Doppler Effect Assisted Wireless Communication for Interference Mitigation

Doppler effect is a fundamental phenomenon that appears in wave propagation, where a moving observer experiences dilation or contraction of wavelength of a wave. It also appears in radio frequency (RF) wireless communication when there exists a relative movement between the transmitter and the receiver, and is widely considered as a major impairment for reliable wireless communication. The current paper proposes Doppler Assisted Wireless Communication that exploits Doppler effect for co-channel interference mitigation. The proposed system also exploits the propagation environment and the network topology, and consists of an access point with a rotating thin drum antenna. The rotating drum receive antenna is designed in such a way that it shifts the interference signals away from the desired signal band. This paper includes a detailed system model, and the results show that under favourable fading conditions, co-channel interference can be significantly reduced. Therefore, it is anticipated that more sophisticated wireless systems and networks can be designed by extending the basic system proposed herein.

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Multi-user Communication in Difficult Interference

The co-channel interference (CCI) is one of the major impairments in wireless communication. CCI typically reduces the reliability of wireless communication links, but the difficult CCI which is no more or less strong to the desired signals destroys wireless links despite having myriad of CCI mitigation methods. It is shown in this paper that M-QAM (Quadrature Amplitude Modulation) or similar modulation schemes which modulate information both in in-phase and quadrature-phase are particularly vulnerable to difficult CCI. Despite well-known shortcomings, it is shown in this paper that M-PAM or similar schemes that use a single dimension for modulation provides an important mean for difficult CCI mitigation.

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Analysis of Cached-Enabled Hybrid Millimter Wave & Sub-6 GHz Massive MIMO Networks

This paper focuses on edge caching in mm/μWave hybrid wireless networks, in which all mmWave SBSs and μWave MBSs are capable of storing contents to alleviate the traffic burden on the backhaul link that connect the BSs and the core network to retrieve the non-cached contents. The main aim of this work is to address the effect of capacity-limited backhaul on the average success probability (ASP) of file delivery and latency. In particular, we consider a more practical mmWave hybrid beamforming in small cells and massive MIMO communication in macro cells. Based on stochastic geometry and a simple retransmission protocol, we derive the association probabilities by which the ASP of file delivery and latency are derived. Taking no caching event as the benchmark, we evaluate these QoS performance metrics under MC and UC placement policies. The theoretical results demonstrate that backhaul capacity indeed has a significant impact on network performance especially under weak backhaul capacity. Besides, we also show the tradeoff among cache size, retransmission attempts, ASP of file delivery, and latency. The interplay shows that cache size and retransmission under different caching placement schemes alleviates the backhaul requirements. Simulation results are present to valid our analysis.

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Nuts and Bolts of a Realistic Stochastic Geometric Analysis of mmWave HetNets: Hardware Impairments and Channel Aging

Motivated by heterogeneous networks (HetNets) design in improving coverage and by millimeter-wave (mmWave) transmission offering an abundance of extra spectrum, we present a general analytical framework shedding light to the downlink of realistic mmWave HetNets consisting of $K$ tiers of randomly located base stations (BSs). Specifically, we model, by virtue of stochastic geometry tools, the \textit{multi-tier} \textit{multi-user multiple-input multiple-output (MU-MIMO) mmWave} network degraded by the inevitable \textit{residual additive transceiver hardware impairments (RATHIs)} and \textit{channel aging}. Given this setting, we derive the coverage probability and the area spectral efficiency (ASE), and we subsequently evaluate the impact of residual transceiver hardware impairments (RTHIs) and channel aging on these metrics. Different path-loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) are accounted for the analysis, which are among the distinguishing features of mmWave systems. Among the findings, we show that the RATHIs have a meaningful impact at the high signal-to-noise ratio (SNR) regime, while the transmit additive distortion degrades further than the receive distortion the system performance. Moreover, serving fewer users proves to be preferable, and the more directive the mmWaves are, the higher the ASE becomes.

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Online Learning Models for Content Popularity Prediction In Wireless Edge Caching

Caching popular contents in advance is an important technique to achieve the low latency requirement and to reduce the backhaul costs in future wireless communications. Considering a network with base stations distributed as a Poisson point process (PPP), optimal content placement caching probabilities are derived for known popularity profile, which is unknown in practice. In this paper, online prediction (OP) and online learning (OL) methods are presented based on popularity prediction model (PPM) and Grassmannian prediction model (GPM), to predict the content profile for future time slots for time-varying popularities. In OP, the problem of finding the coefficients is modeled as a constrained non-negative least squares (NNLS) problem which is solved with a modified NNLS algorithm. In addition, these two models are compared with log-request prediction model (RPM), information prediction model (IPM) and average success probability (ASP) based model. Next, in OL methods for the time-varying case, the cumulative mean squared error (MSE) is minimized and the MSE regret is analyzed for each of the models. Moreover, for quasi-time varying case where the popularity changes block-wise, KWIK (know what it knows) learning method is modified for these models to improve the prediction MSE and ASP performance. Simulation results show that for OP, PPM and GPM provides the best ASP among these models, concluding that minimum mean squared error based models do not necessarily result in optimal ASP. OL based models yield approximately similar ASP and MSE, while for quasi-time varying case, KWIK methods provide better performance, which has been verified with MovieLens dataset.

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Modeling and Performance of Uplink Cache-Enabled Massive MIMO Heterogeneous Networks

A significant burden on wireless networks is brought by the uploading of user-generated contents to the Internet by means of applications such as the social media. To cope with this mobile data tsunami, we develop a novel MIMO network architecture with randomly located base stations (BSs) a large number of antennas employing cache-enabled \textit{uplink} transmission. In particular, we formulate a scenario, where the users upload their content to their strongest base stations (BSs), which are Poisson point process (PPP) distributed. In addition, the BSs, exploiting the benefits of massive MIMO, upload their contents to the core network by means of a finite-rate backhaul. After proposing the caching policies, where we propose the {modified} von Mises distribution as the popularity distribution function, we derive the outage probability and the average delivery rate by taking advantage of tools from the deterministic equivalent (DE) and stochastic geometry analyses. Numerical results investigate the realistic performance gains of the proposed heterogeneous cache-enabled uplink on the network in terms of cardinal operating parameters. For example, insights regarding the BSs storage size are exposed. Moreover, the impacts of the key parameters such the file popularity distribution, and the target bitrate are investigated. Specifically, the outage probability decreases if the storage size is increased, while the average delivery rate increases. In addition, the concentration parameter, defining the number of files stored at the intermediate nodes (popularity), affects directly the proposed metrics. A higher target rate results in higher outage because fewer users obey this constraint. Also, we demonstrate that a denser network decreases the outage and increases the delivery rate. Hence, the introduction of caching at the uplink of the system design ameliorates the network performance.

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Rate-Splitting Robustness in Multi-Pair Massive MIMO Relay Systems

Relay systems improve both coverage and system capacity. Towards this direction, full-duplex (FD) technology, being able to boost the spectral efficiency by transmitting and receiving simultaneously on the same frequency and time resources, is envisaged to play a key role in future networks. However, its benefits come at the expense of self-interference (SI) from their own transmit signal. At the same time, massive MIMO systems, bringing unconventionally many antennas, emerge as a promising technology with huge degrees-of-freedom (DoF). To this end, this paper considers a multi-pair decode-and-forward FD relay channel, where the relay station is deployed with a large number of antennas. Moreover, the rate-splitting (RS) transmission has recently been shown to provide significant performance benefits in various multi-user scenarios with imperfect channel state information at the transmitter (CSIT). Engaging the RS approach, we employ the deterministic equivalent (DE) analysis to derive the corresponding sum-rates in the presence of interferences. Initially, numerical results demonstrate the robustness of RS in half-duplex (HD) systems, since the achievable sum-rate increases without bound, i.e., it does not saturate at high signal-to-noise ratio (SNR). Next, we tackle the detrimental effect of SI in FD. In particular, and most importantly, not only FD outperforms HD, but also RS enables increasing the range of SI over which FD outperforms HD. Furthermore, increasing the number of relay station antennas, RS appears to be more efficacious due to imperfect CSIT, since SI decreases. Interestingly, increasing the number of users, the efficiency of RS worsens and its implementation becomes less favorable under these conditions. Finally, we verify that the proposed DEs, being accurate for a large number of relay station antennas, are tight approximations even for realistic system dimensions.

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Offloading of Users in NOMA-HetNet Using Repulsive Point Process

Ever increasing number of cellular users and their high data requirements, necessitates need for improvement in the present heterogeneous cellular networks (HetNet). Carrier sensing prevents base stations within a certain range of the transmitter from transmitting and hence aids in reducing the interference. Non-orthogonal multiple access (NOMA) has proven its superiority for the 5th generation (5G) networks. This work proposes a mathematical model for an improved HetNet with macro base station (MBS) and femto base station (FBS) tier. The FBS tier is equipped to support NOMA and carrier sensing for its transmissions. Offloading is performed for load balancing in HetNet where the macro users (MU) from congested MBS tier are offloaded to the FBS tier. The FBS tier pairs the offloaded MU (OMU) with an appropriate pairing user (PU) to perform NOMA. The performance of the OMU is studied under different channel conditions with respect to the available PU at the FBS and some useful observations are drawn. A decrease in outage probability by $74.04\%$ for cell center user (CCU) and $48.65\%$ for cell edge user (CEU) is observed for low density FBS. The outage probability decreases by $99.60\%$, for both the CCU and CEU, for high density FBS using the proposed carrier sensing in NOMA. The results are validated using simulations.

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An Analysis on Caching Placement for Millimeter/Micro Wave Hybrid Networks

In this paper, we consider a hybrid millimeter wave (mmWave) and micro wave ($μ$Wave) network from the perspective of \emph{wireless caching} and study the optimal probabilistic content/file caching placement at desirable base stations (BSs) using a stochastic geometric framework. Considering the average success probability (ASP) of file delivery as the performance metric, we derive expressions for the association probability of the typical user to the mmWave and $μ$Wave networks. Accordingly, we provide an upper bound for the ASP of file delivery and formulate the content caching placement scheme as an optimization problem with respect to caching probabilities, that jointly optimizes the ASP of file delivery considering both content placement and delivery phases. In particular, we consider the caching placement strategy under both noise-limited and interference-limited environments. We numerically evaluate the performance of the proposed caching schemes under essential factors, such as blockages in the mmWave network, cluster radius, BS density, and path loss and compare it with uniform caching placement, caching $M$ most popular contents, and random caching placement. Numerical results demonstrate the superiority of the proposed caching scheme over others, albeit certain trade-offs.

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Robust MIMO Beamforming for Cellular and Radar Coexistence

In this letter, we consider the coexistence and spectrum sharing between downlink multi-user multiple-input-multiple-output (MU-MIMO) communication and a MIMO radar. For a given performance requirement of the downlink communication system, we design the transmit beamforming such that the detection probability of the radar is maximized. While the original optimization problem is non-convex, we exploit the monotonically increasing relationship of the detection probability with the non-centrality parameter of the resulting probability distribution to obtain a convex lower-bound optimization. The proposed beamformer is designed to be robust to imperfect channel state information (CSI). Simulation results verify that the proposed approach facilitates the coexistence between radar and communication links, and illustrates a scalable trade-off between the two systems' performance.

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Interference Exploitation for Radar and Cellular Coexistence: The Power-Efficient Approach

We propose a novel approach to enable the coexistence between Multi-Input-Multi-Output (MIMO) radar and downlink multi-user Multi-Input-Single-Output (MU-MISO) communication system. By exploiting the constructive multi-user interference (MUI), the proposed approach trades-off useful MUI power for reducing the transmit power, to obtain a power efficient transmission. This paper focuses on two optimization problems: a) Transmit power minimization at the base station (BS) while guaranteeing the receive signal-to-interference-plus-noise ratio (SINR) level of downlink users and the interference-to-noise ratio (INR) level to radar; b) Minimization of the interference from BS to radar for a given requirement of downlink SINR and transmit power budget. To reduce the computational overhead of the proposed scheme in practice, an algorithm based on gradient projection is designed to solve the power minimization problem. In addition, we investigate the trade-off between the performance of radar and communication, and analytically derive the key metrics for MIMO radar in the presence of the interference from the BS. Finally, a robust power minimization problem is formulated to ensure the effectiveness of the proposed method in the case of imperfect Channel State Information (CSI). Numerical results show that the proposed method achieves a significant power saving compared to conventional approaches, while obtaining a favorable performance-complexity trade-off.

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Rate-Splitting to Mitigate Residual Transceiver Hardware Impairments in Massive MIMO Systems

Rate-Splitting (RS) has recently been shown to provide significant performance benefits in various multi-user transmission scenarios. In parallel, the huge degrees-of-freedom provided by the appealing massive Multiple-Input Multiple-Output (MIMO) necessitate the employment of inexpensive hardware, being more prone to hardware imperfections, in order to be a cost-efficient technology. Hence, in this work, we focus on a realistic massive Multiple-Input Single-Output (MISO) Broadcast Channel (BC) hampered by the inevitable hardware impairments. We consider a general experimentally validated model of hardware impairments, accounting for the presence of \textit{multiplicative distortion} due to phase noise, \textit{additive distortion noise} and \textit{thermal noise amplification}. Under both scenarios with perfect and imperfect channel state information at the transmitter (CSIT), we analyze the potential robustness of RS to each separate hardware imperfection. We analytically assess the sum-rate degradation due to hardware imperfections. Interestingly, in the case of imperfect CSIT, we demonstrate that RS is a robust strategy for multiuser MIMO in the presence of phase and amplified thermal noise, since its sum-rate does not saturate at high signal-to-noise ratio (SNR), contrary to conventional techniques. On the other hand, the additive impairments always lead to a sum-rate saturation at high SNR, even after the application of RS. However, RS still enhances the performance. Furthermore, as the number of users increases, the gains provided by RS decrease not only in ideal conditions, but in practical conditions with RTHIs as well.

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