arXiv subjects

Nemanja Stefan Perović

Publications and source records attributed to Nemanja Stefan Perović.

At least 19 recordsLinked to original sources

arXiv2026

DL-Driven Optimization for ISAC System Equipped With Pinching and Movable Antennas

Integrated sensing and communication (ISAC) is considered one of the key technologies for future wireless networks, due to its ability to provide accurate environment awareness and improve energy, spectral and hardware efficiency. Moreover, the introduction of recently developed pinching antennas (PAs) and movable antennas (MAs) has the potential to further improve the performance gains of ISAC. Therefore, our goal is to study the optimization of the sum-rate for an ISAC system equipped with PAs and MAs, capable of satisfying minimal sensing requirements. To achieve it, we derive a closed-form solution for the optimal sensing receive combiner, and show that it is determined by other optimization variables. For these other variables (i.e., the positions of the transmit PAs, the positions of the users' MAs, the communication precoding matrices, and the sensing transmit beamformer), we propose a deep learning (DL) network that finds their optimal values. To train the network in an unsupervised manner, we formulate a loss function consisting of the objective function, as well as the penalty terms related to the constraints for the PAs and MAs positions. Simulation results show that using PAs and MAs in ISAC systems provides a larger sum-rate compared to ISAC systems with only fixed antennas, and that this performance advantage is increased with the maximum transmit power. Furthermore, we demonstrate that the communication performance of the considered system is a bit more affected by the sensing signal-to-interference-plus-noise ratio (SINR) threshold compared to the sensing performance.

cs.IT↗

arXiv2026

Weighted Sum Rate Optimization for Movable Antenna Enabled Near-Field ISAC

Integrated sensing and communication (ISAC) has been recognized as one of the key technologies capable of simultaneously improving communication and sensing services in future wireless networks. Moreover, the introduction of recently developed movable antennas (MAs) has the potential to further increase the performance gains of ISAC systems. Achieving these gains can pose a significant challenge for MA-enabled ISAC systems operating in the near-field due to the corresponding spherical wave propagation. Motivated by this, in this paper we maximize the weighted sum rate (WSR) for communication users while maintaining a minimal sensing requirement in an MA-enabled near-field ISAC system. To achieve this goal, we propose an algorithm that optimizes the sensing receive combiner, the communication precoding matrices, the sensing transmit beamformer and the positions of the users' MAs in an alternating manner. Simulation results show that using MAs in near-field ISAC systems provides a substantial performance advantage compared to near-field ISAC systems with only fixed antennas. Additionally, we demonstrate that the highest WSR is obtained when larger weights are allocated to the users placed closer to the BS, and that the sensing performance is significantly more affected by the minimum sensing signal-to-interference-plus-noise ratio (SINR) threshold compared to the communication performance.

cs.IT↗

arXiv2025

Optimal Beamforming Design for Multi-user MIMO Near-Field ISAC Systems with Movable Antennas

Integrated sensing and communication (ISAC) has been recognized as one of the key technologies capable of simultaneously improving communication and sensing services in future wireless networks. Moreover, the introduction of recently developed movable antennas (MAs) has the potential to further increase the performance gains of ISAC systems. Although the gains of MA-enabled ISAC systems are relatively well studied in the far field, they remain almost unexplored in near-field scenarios. Motivated by this, in this paper we maximize the weighted sum rate (WSR) for communication users while maintaining a minimum sensing requirement in an MA-enabled near-field ISAC system. To achieve this goal, we propose algorithms that optimize the communication precoding matrices, the sensing transmit beamformer, the sensing receive combiner, the positions of the users' MAs and the positions of the base station (BS) transmit MAs in an alternating manner for the considered ISAC system, for the cases where linear procoding and zero-forcing (ZF) precoding are employed at the BS. Simulation results show that using MAs in near-field ISAC systems provides a substantial performance advantage compared to near-field ISAC systems equipped with fixed antennas only. We show that the scheme with linear precoding achieves larger WSR for unequal users' weight rates, while the scheme with ZF precoding maintains an approximately constant WSR for all users' weight rates. Additionally, we demonstrate that the WSRs of the proposed schemes are highly dependent on the inter-antenna interference between different user's MAs, and that the sensing performance is significantly more affected by the minimum sensing signal-to-interference-plus-noise ratio (SINR) threshold compared to the communication performance.

cs.IT↗

arXiv2025

Energy-Efficient Designs for SIM-Based Broadcast MIMO Systems

Stacked intelligent metasurface (SIM), which consists of multiple layers of intelligent metasurfaces, is emerging as a promising solution for future wireless communication systems. In this timely context, we focus on broadcast multiple-input multiple-output (MIMO) systems and aim to characterize their energy efficiency (EE) performance. To explore the potential of SIM, we consider both dirty paper coding (DPC) and linear precoding (LP) and formulate the corresponding EE maximization problems. For DPC, we employ the broadcast channel (BC)-multiple-access channel (MAC) duality to obtain an equivalent problem, and optimize users' covariance matrices using the successive convex approximation (SCA) and Dinkelbach's methods. Since the phase shift optimization problem of the SIM meta-elements is one of extremely large size, we adopt a conventional projected gradient-based method for its simplicity. A similar approach is followed for the case of LP. Simulation results show that the proposed optimization methods for the considered SIM-based systems can significantly improve the EE, compared to conventional counterparts. Also, we demonstrate that the number of SIM meta-elements and their distribution across the SIM layers have a significant impact on both the achievable sum-rate and EE performance.

cs.IT↗

arXiv2025

Scaling Achievable Rates in SIM-aided MIMO Systems with Metasurface Layers: A Hybrid Optimization Framework

We investigate the achievable rate (AR) of a stacked intelligent metasurface (SIM)-aided holographic multiple-input multiple-output (HMIMO) system by jointly optimizing the SIM phase shifts and power allocation. Contrary to earlier studies suggesting that the AR decreases when the number of metasurface layers increases past a certain point for \emph{a fixed SIM thickness}, our findings demonstrate consistent increase. To achieve this, we introduce two problem formulations: one based on directly maximizing the AR (RMax) and the other focused on minimizing inter-stream interference (IMin). To solve the RMax problem, we apply Riemannian manifold optimization (RMO) and weighted minimum mean square error (WMMSE) methods to optimize the SIM phase shifts and power allocation alternately. For the IMin problem, we derive an efficient algorithm that iteratively updates each meta-atom's phase shift using a closed-form expression while keeping others fixed. Our key contribution is integrating these two approaches, where the IMin solution initializes the SIM phase shifts in the first algorithm. This hybrid strategy enhances AR performance across varying numbers of metasurface layers. Simulation results demonstrate that the proposed algorithms outperform existing benchmarks. Most importantly, we show that increasing the number of metasurface layers while keeping the SIM thickness fixed leads to significant AR improvements.

eess.SP↗

arXiv2025

Sensing Rate Optimization for Multi-Band Cooperative ISAC Systems

Integrated sensing and communication (ISAC) has been recognized as one of the key technologies for future wireless networks, which potentially need to operate in multiple frequency bands to satisfy ever-increasing demands for both communication and sensing services. Motivated by this, we consider the sum sensing rate (SR) optimization for a cooperative ISAC system with linear precoding, where each base station (BS) works in a different frequency band. With this aim, we propose an optimization algorithm based on the semi-definite rank relaxation that introduces covariance matrices as optimization variables, and we apply the inner approximation (IA) method to deal with the nonconvexity of the resulting problem. Simulation results show that the proposed algorithm increases the SR by approximately 25 % and 40 % compared to the case of equal power distribution in a cooperative ISAC system with two and three BSs, respectively. Additionally, the algorithm converges in only a few iterations, while its most beneficial implementation scenario is in the low power regime

cs.IT↗

arXiv2024

On the Joint Beamforming Design for Large-scale Downlink RIS-assisted Multiuser MIMO Systems

Reconfigurable intelligent surfaces (RISs) have huge potential to improve spectral and energy efficiency in future wireless systems at a minimal cost. However, early prototype results indicate that deploying hundreds or thousands of reflective elements is necessary for significant performance gains. Motivated by this, our study focuses on \emph{large-scale } RIS-assisted multi-user (MU) multiple-input multiple-output (MIMO) systems. In this context, we propose an efficient algorithm to jointly design the precoders at the base station (BS) and the phase shifts at the RIS to maximize the weighted sum rate (WSR). In particular, leveraging an equivalent lower-dimensional reformulation of the WSR maximization problem, we derive a closed-form solution to optimize the precoders using the successive convex approximation (SCA) framework. While the equivalent reformulation proves to be efficient for the precoder optimization, we offer numerical insights into why the original formulation of the WSR optimization problem is better suited for the phase shift optimization. Subsequently, we develop a scaled projected gradient method (SPGM) and a novel line search procedure to optimize RIS phase shifts. Notably, we show that the complexity of the proposed method \emph{scales linearly with the number of BS antennas and RIS reflective elements}. Extensive numerical experiments demonstrate that the proposed algorithm significantly reduces both time and computational complexity while achieving higher WSR compared to baseline algorithms.

eess.SP↗

arXiv2024

On the Bit Error Probability of DMA-Based Systems

Dynamic metasurface antennas (DMAs) are an alternative application of metasurfaces as active reconfigurable antennas with advanced analog signal processing and beamforming capabilities, which have been proposed to replace conventional antenna arrays for next generation transceivers. Motivated by this, we investigate the bit error probability (BEP) optimization in a DMA-based system, propose an iterative optimization algorithm, which adjusts the transmit precoder and the weights of the DMA elements, prove its convergence and derive complexity.

cs.IT↗

arXiv2024

Mutual Information Optimization for SIM-Based Holographic MIMO Systems

In the context of emerging stacked intelligent metasurface (SIM)-based holographic MIMO (HMIMO) systems, a fundamental problem is to study the mutual information (MI) between transmitted and received signals to establish their capacity. However, direct optimization or analytical evaluation of the MI, particularly for discrete signaling, is often intractable. To address this challenge, we adopt the channel cutoff rate (CR) as an alternative optimization metric for the MI maximization. In this regard, we propose an alternating projected gradient method (APGM), which optimizes the CR of a SIM-based HMIMO system by adjusting signal precoding and the phase shifts across the transmit and receive SIMs on a layer-by-layer basis. Simulation results indicate that the proposed algorithm significantly enhances the CR, achieving substantial gains, compared to the case with random SIM phase shifts, that are proportional to those observed for the corresponding MI. This justifies the effectiveness of using the channel CR for the MI optimization. Moreover, we demonstrate that the integration of digital precoding, even on a modest scale, has a significant impact on the ultimate performance of SIM-aided systems.

cs.IT↗

arXiv2024

Optimization of RIS-aided SISO Systems Based on a Mutually Coupled Loaded Wire Dipole Model

The electromagnetic (EM) features of reconfigurable intelligent surfaces (RISs) fundamentally determine their operating principles and performance. Motivated by these considerations, we study a single-input single-output (SISO) system in the presence of an RIS, which is characterized by a circuit-based EM-consistent model. Specifically, we model the RIS as a collection of thin wire dipoles controlled by tunable load impedances, and we propose a gradient-based algorithm for calculating the optimal impedances of the scattering elements of the RIS in the presence of mutual coupling. Furthermore, we prove the convergence of the proposed algorithm and derive its computational complexity in terms of number of complex multiplications. Numerical results show that the proposed algorithm provides better performance and converges faster than a benchmark algorithm.

cs.IT↗

arXiv2022

On the Maximum Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel

Reconfigurable intelligent surfaces (RISs) represent a new technology that can shape the radio wave propagation and thus offers a great variety of possible performance and implementation gains. Motivated by this, we investigate the achievable sum-rate optimization in a broadcast channel (BC) in the presence of RISs. We solve this problem by exploiting the well-known duality between the Gaussian multiple-input multiple-output (MIMO) BC and the multiple-access channel (MAC), and we correspondingly derive three algorithms which optimize the users' covariance matrices and the RIS phase shifts in the dual MAC. The users' covariance matrices are optimized by a dual decomposition method with block coordinate maximization (BCM), or by a gradient-based method. The RIS phase shifts are either optimized sequentially by using a closed-form expression, or are computed in parallel by using a gradient-based method. We present a computational complexity analysis for the proposed algorithms. Simulation results show that the proposed algorithms tend to converge to the same achievable sum-rate overall, but may produce different sum-rate performance for some specific situations, due to the non-convexity of the considered problem. Also, the gradient-based optimization methods are generally more time efficient. In addition, we demonstrate that the proposed algorithms can provide a significant gain in the RIS-assisted BC assisted by multiple RISs and that the gain depends on the placement of the RISs.

cs.IT↗

arXiv2022

Intelligent Omni-Surfaces (IOSs) for the MIMO Broadcast Channel

In this paper, we consider intelligent omni-surfaces (IOSs), which are capable of simultaneously reflecting and refracting electromagnetic waves. We focus our attention on the multiple-input multiple-output (MIMO) broadcast channel, and we introduce an algorithm for jointly optimizing the covariance matrix at the base station, the matrix of reflection and transmission coefficients at the IOS, and the amount of power that is reflected and refracted from the IOS. The distinguishable feature of this work lies in taking into account that the reflection and transmission coefficients of an IOS are tightly coupled. Simulation results are illustrated to show the convergence of the proposed algorithm and the benefits of using surfaces with simultaneous reflection and refraction capabilities.

eess.SP↗

arXiv2022

Joint CFO and Channel Estimation for RIS-aided Multi-user Massive MIMO Systems

Accurate channel estimation is essential to achieve the performance gains promised by the use of reconfigurable intelligent surfaces (RISs) in wireless communications. In the uplink of multi-user orthogonal frequency division multiple access (OFDMA) systems, synchronization errors such as carrier frequency offsets (CFOs) can significantly degrade the channel estimation performance. This becomes more critical in RIS-aided communications, as even a small channel estimation error leads to a significant performance loss. Motivated by this, we propose a joint CFO and channel estimation method for RIS-aided multi-user massive multiple-input multiple-output (MIMO) systems. Our proposed pilot structure allows accurate estimation of the CFOs without multi-user interference (MUI), using the same pilot resources for both CFO estimation and channel estimation. For joint estimation of multiple users' CFOs, a correlation-based approach is devised using the received signals at all BS antennas. Using least-squares (LS) estimation with the obtained CFO values, the channels of all users are jointly estimated. For optimization of the RIS phase shifts at the data transmission stage, we propose a projected gradient method (PGM). Simulation results demonstrate that the proposed method provides an improvement in the normalized mean-square error (NMSE) of channel estimation as well as in the bit error rate (BER) performance.

eess.SP↗

arXiv2021

Low-Complexity Joint CFO and Channel Estimation for RIS-aided OFDM Systems

Accurate channel estimation is essential for achieving the performance gains offered by reconfigurable intelligent surface (RIS)-aided wireless communications. A variety of channel estimation methods have been proposed for such systems; however, none of the existing methods takes into account the effect of synchronization errors such as carrier frequency offset (CFO). In general, CFO can significantly degrade channel estimation performance of orthogonal frequency division multiplexing (OFDM) systems. Motivated by this, we investigate the effect of CFO on channel estimation for RIS-aided OFDM systems. Furthermore, we propose a joint CFO and channel impulse response (CIR) estimation method for these systems. Simulation results demonstrate the effectiveness of our proposed method, and also demonstrate that the use of time-domain rather than frequency-domain estimation in this context results in an improvement in the mean-squared error (MSE) performance of channel estimation as well as a significantly lower overall computational complexity.

eess.SP↗

arXiv2021

Achievable Rate Optimization for MIMO Systems with Reconfigurable Intelligent Surfaces

Reconfigurable intelligent surfaces (RISs) represent a radical new technology that can shape the radio wave propagation in wireless communication systems and offers a great variety of possible performance and implementation gains. Motivated by this, in this paper we study the achievable rate optimization for a multi-stream multiple-input multiple-output (MIMO) system equipped with an RIS, and formulate a joint optimization problem of the covariance matrix of the transmitted signal and the RIS elements. To solve this problem, we propose an iterative optimization algorithm that is based on the projected gradient method (PGM). We derive the step size that guarantees the convergence of the proposed algorithm and we define a backtracking line search to improve its convergence rate. Furthermore, we introduce the total free space path loss (FSPL) ratio of the indirect and direct links as a first-order measure of the applicability of an RIS in the considered communication system. Simulation results show that the proposed PGM achieves the same achievable rate as a state-of-the-art benchmark scheme, but with a significantly lower computational complexity. In addition, it is demonstrated that the RIS application is particularly suitable to increase the achievable rate in an indoor environment, as in this case even a small number of RIS elements is sufficient to provide a substantial achievable rate gain.

cs.IT↗

arXiv2021

Optimization of RIS-aided MIMO Systems via the Cutoff Rate

The main difficulty concerning optimizing the mutual information (MI) in reconfigurable intelligent surface (RIS)-aided communication systems with discrete signaling is the inability to formulate this optimization problem in an analytically tractable manner. Therefore, we propose to use the cutoff rate (CR) as a more tractable metric for optimizing the MI and introduce two optimization methods to maximize the CR, assuming perfect knowledge of the channel state information (CSI). The first method is based on the projected gradient method (PGM), while the second method is derived from the principles of successive convex approximation (SCA). Simulation results show that the proposed optimization methods significantly enhance the CR and the corresponding MI.

cs.IT↗

arXiv2021

On the Achievable Sum-rate of the RIS-aided MIMO Broadcast Channel

cs.IT↗

arXiv2021

Multilevel Polar Coded Space-Shift Keying

Multilevel coding (MLC) is a coded modulation technique which can achieve excellent performance over a range of communication channels. Polar codes have been shown to be quite compatible with communication systems using MLC, as the rate allocation of the component polar codes follows the natural polarization inherent in polar codes. MLC based techniques have not yet been studied in systems that use spatial modulation (SM). SM makes the polar code design difficult as the spatial bits actually select a channel index for transmission. To solve this problem, we propose a Monte Carlo based evaluation of the ergodic capacities for the individual bit levels under the capacity rule for a space-shift keying (SSK) system, where we also make use of a single antenna activation to approximate the transmission channel for the design of the multilevel polar code. Our simulation results show that the multilevel polar coded 16 $\times$ 1 SSK system outperforms the corresponding system that uses bit-interleaved polar coded modulation by 2.9 dB at a bit-error rate (BER) of $10^{-4}$.

cs.IT↗