arXiv subjects

Zoran Hadzi-Velkov

Publications and source records attributed to Zoran Hadzi-Velkov.

At least 19 recordsLinked to original sources

arXiv2026

Spatially Robust Near-Field SWIPT Using Pinching Antennas: Rate-Energy Tradeoff Bounds

Pinching Waveguide Antennas (PWAs) offer significant potential for simultaneous wireless information and power transfer (SWIPT) by enabling precise near-field energy focusing. However, existing optimization frameworks are largely point-based (targeting a single coordinate for maximum gain), and thus highly sensitive to positioning errors and mobility, as near-field signals fluctuate significantly even over small spatial displacements. In this paper, we propose a spatially robust design framework based on discrete antenna selection optimized for service area (SA) coverage. Unlike point-based approaches, our model guarantees quality of service within predefined SAs for both information decoding (ID) and energy harvesting (EH) receivers, thereby improving robustness to user displacements. We formulate the problem as a non-convex binary quadratic program aimed at maximizing harvested energy within the EH SA subject to robust rate constraints in the ID SA. To characterize fundamental performance limits, we develop a semidefinite relaxation (SDR) framework that provides an upper bound on the achievable rate-energy (R-E) region. For the lower bound, we employ a low-complexity swap-based local search algorithm enforcing binary hardware constraints. Numerical results demonstrate that the proposed coverage-oriented design yields a robust R-E tradeoff and maintains stable performance across service regions, highlighting the advantages of discrete antenna activation over point-based near-field optimization approaches.

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arXiv2026

Leveraging Convolutional Sparse Autoencoders for Robust Movement Classification from Low-Density sEMG

Reliable control of myoelectric prostheses is often hindered by high inter-subject variability and the clinical impracticality of high-density sensor arrays. This study proposes a deep learning framework for accurate gesture recognition using only two surface electromyography (sEMG) channels. The method employs a Convolutional Sparse Autoencoder (CSAE) to extract temporal feature representations directly from raw signals, eliminating the need for heuristic feature engineering. On a 6-class gesture set, our model achieved a multi-subject F1-score of 94.3% $\pm$ 0.3%. To address subject-specific differences, we present a few-shot transfer learning protocol that improved performance on unseen subjects from a baseline of 35.1% $\pm$ 3.1% to 92.3% $\pm$ 0.9% with minimal calibration data. Furthermore, the system supports functional extensibility through an incremental learning strategy, allowing for expansion to a 10-class set with a 90.0% $\pm$ 0.2% F1-score without full model retraining. By combining high precision with minimal computational and sensor overhead, this framework provides a scalable and efficient approach for the next generation of affordable and adaptive prosthetic systems.

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arXiv2024

Gradient Descent Methods for Regularized Optimization

Regularization is a widely recognized technique in mathematical optimization. It can be used to smooth out objective functions, refine the feasible solution set, or prevent overfitting in machine learning models. Due to its simplicity and robustness, the gradient descent (GD) method is one of the primary methods used for numerical optimization of differentiable objective functions. However, GD is not well-suited for solving $\ell^1$ regularized optimization problems since these problems are non-differentiable at zero, causing iteration updates to oscillate or fail to converge. Instead, a more effective version of GD, called the proximal gradient descent employs a technique known as soft-thresholding to shrink the iteration updates toward zero, thus enabling sparsity in the solution. Motivated by the widespread applications of proximal GD in sparse and low-rank recovery across various engineering disciplines, we provide an overview of the GD and proximal GD methods for solving regularized optimization problems. Furthermore, this paper proposes a novel algorithm for the proximal GD method that incorporates a variable step size. Unlike conventional proximal GD, which uses a fixed step size based on the global Lipschitz constant, our method estimates the Lipschitz constant locally at each iteration and uses its reciprocal as the step size. This eliminates the need for a global Lipschitz constant, which can be impractical to compute. Numerical experiments we performed on synthetic and real-data sets show notable performance improvement of the proposed method compared to the conventional proximal GD with constant step size, both in terms of number of iterations and in time requirements.

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arXiv2024

Convergence Rate Maximization for Split Learning-based Control of EMG Prosthetic Devices

Split Learning (SL) is a promising Distributed Learning approach in electromyography (EMG) based prosthetic control, due to its applicability within resource-constrained environments. Other learning approaches, such as Deep Learning and Federated Learning (FL), provide suboptimal solutions, since prosthetic devices are extremely limited in terms of processing power and battery life. The viability of implementing SL in such scenarios is caused by its inherent model partitioning, with clients executing the smaller model segment. However, selecting an inadequate cut layer hinders the training process in SL systems. This paper presents an algorithm for optimal cut layer selection in terms of maximizing the convergence rate of the model. The performance evaluation demonstrates that the proposed algorithm substantially accelerates the convergence in an EMG pattern recognition task for improving prosthetic device control.

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arXiv2023

Performance Comparison Between A Simple Full-Duplex Multi-Antenna Relay And A Passive Reflecting Intelligent Surface

In this paper, we propose to investigate a single RF chain multi-antenna full-duplex (FD) relay built with $b$-bit analog phase shifters and passive self-interference cancellation. Next, assuming only passive self-interference cancellation at the FD relay, we derive the achievable data rate of a system comprised of a source, the proposed FD relay, and a destination. We then compare the achievable data rate of the proposed FD relaying system with the achievable data rate of the same system but with the FD relay replaced by an ideal passive RIS. Our results show that the proposed relaying system with 2-bit quantized analog phase shifters significantly outperforms the RIS-assisted system. In fact, the performance gains are so large, at least for small to intermediate numbers of antenna elements, that we believe it makes this result of interest to the wireless community. The proposed FD relay can also be built with reconfigurable holographic surfaces, one surface for the transmit-side and one for the receive-side. For such a scenario, we derive the energy efficiency of the relay-assisted system and compare it with the RIS-assisted system. Our numerical results show that the energy efficiency of the relay-assisted system built with reconfigurable holographic surfaces is significantly higher than the energy efficiency of the RIS-assisted system. Intuitively, the RIS system is at a disadvantage since there the total transmit power $P_T$ is used entirely by the source, whereas in the FD relaying system the total transmit power $P_T$ is shared by the source and the FD relay in addition to the noise-cleansing process performed by the decode-and-forwarding at the FD relay.

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arXiv2021

Designing Wireless Powered Networks assisted by Intelligent Reflecting Surfaces with Mechanical Tilt

In this paper, we propose a fairness-aware rate maximization scheme for a wireless powered communications network (WPCN) assisted by an intelligent reflecting surface (IRS). The proposed scheme combines user scheduling based on time division multiple access (TDMA) and (mechanical) angular displacement of the IRS. Each energy harvesting user (EHU) has dedicated time slots with optimized durations for energy harvesting and information transmission whereas, the phase matrix of the IRS is adjusted to focus its beam to a particular EHU. The proposed scheme exploits the fundamental dependence of the IRS channel path-loss on the angle between the IRS and the node's line-of-sight, which is often overlooked in the literature. Additionally, the network design can be optimized for large number of IRS unit cells, which is not the case with the computationally intensive state-of-the-art schemes. In fact, the EHUs can achieve significant rates at practical distances of several tens of meters to the base station (BS) only if the number of IRS unit cells is at least a few thousand.

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arXiv2021

Wireless Powered Communication Networks with Non-Ideal Circuit Power Consumption

Assuming non-ideal circuit power consumption at the energy harvesting (EH) nodes, we propose two practical protocols that optimize the performance of the harvest-then-transmit wireless powered communication networks (WPCNs) under two different objectives: (1) proportional fair (PF) resource allocation, and (2) sum rate maximization. These objectives lead to optimal allocations for the transmit power by the base station (BS), which broadcasts RF radiation over the downlink, and optimal durations of the EH phase and the uplink information transmission phases within the dynamic time-division multiple access (TDMA) frame. Compared to the max-sum-rate protocol, the PF protocol attains a higher level of system fairness at the expense of the sum rate degradation. The PF protocol is advantageous over the max-sum-rate protocol in terms of system fairness regardless of the circuit power consumption, whereas the uplink sum rates of both protocols converge when this power consumption increases.

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arXiv2021

Optimal Power and Time Allocation for WPCNs with Piece-wise Linear EH Model

We propose a novel transmission protocol for harvest-then-transmit wireless powered communication networks, which takes into account the non-linearity of the energy harvesting (EH) process at the EH users and maximizes the sum rate in the uplink. We assume a piece-wise linear energy harvesting model and provide expressions for the optimal transmit power of the base station (BS), the duration of the EH phase, and the duration of the uplink information transmission phases of the users. The obtained solution provides insight regarding the significance of the non-linear EH model on the optimal resource allocation. Simulations unveil the growing impact of the saturation effect, which occurs for high received radio frequency powers, as the average and the maximum instantaneous transmit powers of the BS increase.

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arXiv2019

On the Secrecy Capacity of a Full-Duplex Wirelessly Powered Communication System

In this paper, we investigate the secrecy capacity of a point-to-point, full-duplex (FD) wirelesly powered communication system in the presence of a passive eavesdropper (EVE). The considered system is comprised of an energy transmitter (ET), an energy harvesting user (EHU), and a passive EVE. The ET transmits radio-frequency energy, which is used for powering the EHU as well as for generating interference at the EVE. The EHU uses the energy harvested from the ET to transmit confidential messages back to the ET. As a consequence of the FD mode of operation, both the EHU and the ET are subjected to self-interference, which has different effects at the two nodes. In particular, the self-interference impairs the decoding of the received message at the ET, whilst it serves as an additional energy source at the EHU. For this system model, we derive an upper and a lower bound on the secrecy capacity. For the lower bound, we propose a simple achievability scheme. Our numerical results show significant improvements in terms of achievable secrecy rate when the proposed communication scheme is employed against its half-duplex counterpart, even for practical self-interference values at the ET.

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arXiv2018

Proportional Fairness in ALOHA Networks with RF Energy Harvesting

In this paper, we study wireless powered communication networks that employ the slotted ALOHA protocol, which is the preferred protocol for simple and uncoordinated networks. In the energy harvesting (EH) phase, the base station broadcasts radio frequency energy to the EH users (EHUs). The EHUs harvest the broadcasted energy and use it to transmit information back to the base station by contending for access to the uplink channel in the random access (RA) phase. In order to ensure fairness among the users, we propose a proportionally fair resource allocation scheme that exploits the RA nature of slotted ALOHA. Specifically, assuming statistical channel state information, we determine the optimal transmit power at the base station, the optimal durations of the EH and RA phases, the channel access probability, and the rate of each EHU.

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arXiv2017

Capacity of a Full-Duplex Wirelessly Powered Communication System with Self-Interference and Processing Cost

In this paper, we investigate the capacity of a point-to-point, full-duplex (FD), wirelessly powered communication system impaired by self-interference. This system is comprised of an energy transmitter (ET) and an energy harvesting user (EHU), both operating in a FD mode. The ET transmits energy towards the EHU. The EHU harvests this energy and uses it to transmit information back to the ET. As a result of the FD mode, both nodes are affected by self-interference. The self-interference has a different effect at the two nodes: it impairs the decoding of the received signal at the ET, however, it provides an additional source of energy for the EHU. This paper derives the capacity of this communication system assuming a processing cost at the EHU and additive white Gaussian noise channel with block fading. Thereby, we show that the capacity achieving scheme is relatively simple and therefore applicable to devices with limited resources. Moreover, our numerical results show significant improvements in terms of data rate when the capacity achieving strategy is employed compared to half-duplex transmission. Moreover, we show the positive and negative effects of the self-interference at the EHU and the ET, respectively. Furthermore, we show the crippling effect of the processing cost and demonstrate that failing to take it into consideration gives a false impression in terms of achievable rate.

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arXiv2017

Asymptotically Optimal Power Allocation for Energy Harvesting Communication Networks

For a general energy harvesting (EH) communication network, i.e., a network where the nodes generate their transmit power through EH, we derive the asymptotically optimal online power allocation solution which optimizes a general utility function when the number of transmit time slots, $N$, and the battery capacities of the EH nodes, $B_{\rm max}$, satisfy $N\to\infty$ and $B_{\rm max}\to\infty$. The considered family of utility functions is general enough to include the most important performance measures in communication theory such as the average data rate, outage probability, average bit error probability, and average signal-to-noise ratio. The proposed power allocation solution is very simple. Namely, the asymptotically optimal power allocation for the EH network is identical to the optimal power allocation for an equivalent non-EH network whose nodes have infinite energy available but their average transmit power is constrained to be equal to the average harvested power and/or the maximum average transmit power of the corresponding nodes in the EH network. Moreover, the maximum average performance of a general EH network converges to the maximum average performance of the corresponding equivalent non-EH network, when $N\to\infty$ and $B_{\rm max}\to\infty$. Although the proposed solution is asymptotic in nature, it is applicable to EH systems transmitting in a large but finite number of time slots and having a battery capacity much larger than the average harvested power and/or the maximum average transmit power.

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arXiv2016

Wireless Networks with Energy Harvesting and Power Transfer: Joint Power and Time Allocation

In this paper, we consider wireless powered communication networks which could operate perpetually, as the base station (BS) broadcasts energy to the multiple energy harvesting (EH) information transmitters. These employ "harvest then transmit" mechanism, as they spend all of their energy harvested during the previous BS energy broadcast to transmit the information towards the BS. Assuming time division multiple access (TDMA), we propose a novel transmission scheme for jointly optimal allocation of the BS broadcasting power and time sharing among the wireless nodes, which maximizes the overall network throughput, under the constraint of average transmit power and maximum transmit power at the BS. The proposed scheme significantly outperforms "state of the art" schemes that employ only the optimal time allocation. If a single EH transmitter is considered, we generalize the optimal solutions for the case of fixed circuit power consumption, which refers to a much more practical scenario.

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arXiv2016

Rate Maximization of Decode-and-Forward Relaying Systems with RF Energy Harvesting

We consider a three-node decode-and-forward (DF) half-duplex relaying system, where the source first harvests RF energy from the relay, and then uses this energy to transmit information to the destination via the relay. We assume that the information transfer and wireless power transfer phases alternate over time in the same frequency band, and their {\it time fraction} (TF) may change or be fixed from one transmission epoch (fading state) to the next. For this system, we maximize the achievable average data rate. Thereby, we propose two schemes: (1) jointly optimal power and TF allocation, and (2) optimal power allocation with fixed TF. Due to the small amounts of harvested power at the source, the two schemes achieve similar information rates, but yield significant performance gains compared to a benchmark system with fixed power and fixed TF allocation.

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arXiv2015

Optimal time sharing in underlay cognitive radio systems with RF energy harvesting

Due to the fundamental tradeoffs, achieving spectrum efficiency and energy efficiency are two contending design challenges for the future wireless networks. However, applying radio-frequency (RF) energy harvesting (EH) in a cognitive radio system could potentially circumvent this tradeoff, resulting in a secondary system with limitless power supply and meaningful achievable information rates. This paper proposes an online solution for the optimal time allocation (time sharing) between the EH phase and the information transmission (IT) phase in an underlay cognitive radio system, which harvests the RF energy originating from the primary system. The proposed online solution maximizes the average achievable rate of the cognitive radio system, subject to the $\varepsilon$-percentile protection criteria for the primary system. The optimal time sharing achieves significant gains compared to equal time allocation between the EH and IT phases.

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arXiv2014

Multiple-access Fading Channel with Wireless Power Transfer and Energy Harvesting

We consider the achievable average rates of a multiple-access system, which consists of N energy-harvesting users (EHUs) that transmit information over a block fading multiple-access channel (MAC) and a base station (BS) that broadcasts radio frequency (RF) energy to the EHUs for wireless power transfer. The information (over the uplink) and power (over the downlink) can be transmitted either in time division duplex or frequency division duplex. For the case when the EHUs battery capacities and the number of transmission slots are both infinite, we determine the optimal power allocation for the BS and the optimal rates and power allocations for the EHUs that maximize the achievable rate region of the MAC. The resulting online solution is asymptotically optimal, and also applicable for a finite number of transmission slots and finite battery capacities.

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arXiv2014

Optimal Power Control for Analog Bidirectional Relaying with Long-Term Relay Power Constraint

Wireless systems that carry delay-sensitive information (such as speech and/or video signals) typically transmit with fixed data rates, but may occasionally suffer from transmission outages caused by the random nature of the fading channels. If the transmitter has instantaneous channel state information (CSI) available, it can compensate for a significant portion of these outages by utilizing power allocation. In a conventional dual-hop bidirectional amplify-and-forward (AF) relaying system, the relay already has instantaneous CSI of both links available, as this is required for relay gain adjustment. We therefore develop an optimal power allocation strategy for the relay, which adjusts its instantaneous output power to the minimum level required to avoid outages, but only if the required output power is below some cutoff level; otherwise, the relay is silent in order to conserve power and prolong its lifetime. The proposed scheme is proven to minimize the system outage probability, subject to an average power constraint at the relay and fixed output powers at the end nodes.

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arXiv2014

Optimal Power Allocation for Three-phase Bidirectional DF Relaying with Fixed Rates

Wireless systems that carry delay-sensitive information (such as speech and/or video signals) typically transmit with fixed data rates, but may occasionally suffer from transmission outages caused by the random nature of the fading channels. If the transmitter has instantaneous channel state information (CSI) available, it can compensate for a significant portion of these outages by utilizing power allocation. In this paper, we consider optimal power allocation for a conventional dual-hop bidirectional decode-and-forward (DF) relaying system with a three-phase transmission protocol. The proposed strategy minimizes the average power consumed by the end nodes and the relay, subject to some maximum allowable system outage probability (OP), or equivalently, minimizes the system OP while meeting average power constraints at the end nodes and the relay. We show that in the proposed power allocation scheme, the end nodes and the relay adjust their output powers to the minimum level required to avoid outages, but will sometimes be silent, in order to conserve power and prolong their lifetimes. For the proposed scheme, the end nodes use the instantaneous CSI of their respective source-relay links and the relay uses the instantaneous CSI of both links.

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