arXiv subjects

Antti Tölli

Publications and source records attributed to Antti Tölli.

At least 19 recordsLinked to original sources

arXiv2026

Codebook-Based Effective CSI Feedback for Precoding Design in MIMO Systems

Downlink multi-user multiple-input multiple-output (MIMO) precoding with limited channel state information (CSI) feedback in multi-cell systems is studied. Conventional codebook-based CSI feedback compresses the UE-specific physical channels, which leaves an inherent mismatch between the base-station (BS) precoders and the interference-aware UE combiners. To address this limitation, an effective CSI (ECSI) feedback framework is proposed in which UEs compute their linear combiners from precoded downlink pilots, construct corresponding post-combining effective channels, and report compact quantized representations using the same payload structure as in conventional schemes. The BS reconstructs the effective CSI and iteratively refines its precoders through over-the-air signaling without incurring additional downlink overhead. Analytical expressions are derived to characterize the effective-channel estimation error under both conventional CSI and ECSI feedback, explicitly capturing the impact of beam selection and rank truncation. Simulations demonstrate fast convergence within a few iterations and up to 30\% average sum-rate improvement over conventional CSI-based precoding, with gains reaching 100\% at the 10th percentile of per-stream rates in interference-limited conditions.

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arXiv2026

Near-Field MIMO LoS Channel Recovery Under User Antenna Asymmetry

Near-field (N-F) line-of-sight (LoS) MIMO channels admit a compact representation through a small number of geometric parameters describing the relative transceiver geometry, enabling low-overhead channel acquisition without estimating the full channel matrix. This paper considers downlink (DL) channel acquisition under practical asymmetric user-equipment (UE) antenna capabilities with multiple DL receive antennas, but only a single active uplink (UL) transmit chain. In this setting, UL observations across the large BS aperture enable accurate estimation of the relative location of the UL-active UE antenna but are insufficient to determine the orientation of the entire UE array. We propose a two-stage geometry-based N-F LoS MIMO channel acquisition framework that distributes the estimation of the channel-defining geometric parameters between the BS and UE. First, a single UL pilot sequence enables the BS to estimate two BS-side reference angles that parameterize the relative location of the UL-active UE antenna. The BS conveys these estimates to the UE and transmits two DL pilot sequences, from which the UE estimates the remaining array-orientation parameter. We derive Cramer-Rao lower bounds (CRLBs) for the first-stage parameters and a first-order error-covariance approximation for the UE orientation that explicitly captures the propagation of first-stage estimation uncertainty. Numerical results characterize the resulting error propagation and demonstrate accurate estimation of the geometric parameters and reconstruction of the LoS MIMO channel using one UL and two DL pilot sequences.

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arXiv2026

Asymmetric Stream Allocation and Linear Decodability in MIMO Coded Caching

Coded caching (CC) can transform cache memory at network devices into an active communication resource and significantly enhance the Degrees of Freedom (DoF) of multi-input multi-output (MIMO) systems by jointly exploiting global caching and spatial multiplexing gains. Existing linearly decodable MIMO-CC designs, however, largely rely on symmetric stream allocation, where all scheduled users receive the same number of streams, which induces coarse DoF granularity and may leave spatial dimensions unused. This letter studies one-shot linearly decodable MIMO-CC delivery with arbitrary per-user stream allocations. We derive a sufficient stream-count decodability condition, expressed through per-user stream counts and multicast-codeword multiplicities, that generalizes the symmetric common-stream feasibility rule. Building on this condition, we develop a greedy multicast scheduling procedure with certified linear decodability, which redistributes coded multicast messages across transmission intervals to realize asymmetric stream allocations. Numerical results show that the proposed scheduler fills DoF-granularity gaps and improves finite-SNR symmetric rates over the state of the art.

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arXiv2026

Cache-Aided Asymmetric MIMO Communications: Achievable DoF Analysis

Integrating coded caching (CC) into multiple-input multiple-output (MIMO) communications significantly enhances the achievable degrees of freedom (DoF). This paper investigates a practical cache-aided asymmetric MIMO configuration with cache ratio $γ$, where a server with $L$ transmit antennas communicates with $K$ users. The users are partitioned into $J$ groups, and each user in group $j$ has $G_j$ receive antennas. We propose four content-aware MIMO-CC strategies: \emph{min-$G$} enforces symmetry using the smallest antenna count among users; \emph{Grouping} maximizes intra-subset spatial multiplexing gain at the expense of some global caching gain; \emph{Super-grouping} aggregates users into optimized \emph{min-$G$}-based super-sets with identical effective receive multiplexing gains before applying \emph{Grouping} across them; and \emph{Phantom} redistributes spatial resources assuming "phantom" antennas at the users to bridge the performance gains of \emph{min-$G$} and \emph{Grouping}. We develop these asymmetric strategies under three reference symmetric CC placement-delivery policies with guaranteed linear decodability: a finite-search DoF-optimized policy attaining the best single-shot achievable DoF lower bound, and two closed-form policies, namely combinatorial and linear cyclic low-complexity constructions, with the cyclic policy attaining DoF performance close to the others in many operating regimes. Analytical and numerical results demonstrate significant DoF improvements across various system configurations, and that policy-strategy combinations offer flexible trade-offs between DoF and subpacketization complexity.

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arXiv2026

SEP Analysis of Quantized SIMO Systems with M-PSK over Correlated Fading Channels

The average symbol error probability (SEP) of a phase-quantized single-input multiple-output system with M-ary phase-shift keying modulation and maximum ratio combining (MRC) is analyzed under correlated Rayleigh fading and additive white Gaussian noise. Building on our prior framework for independent and identically distributed Rayleigh fading, we extend the analysis to the spatially correlated case by introducing an asymptotically equivalent MRC combiner that enables tractable SEP characterization. Using this approach, we derive closed-form expressions at high signal-to-noise ratio (SNR) that explicitly characterize the diversity and coding gains as functions of the receive correlation structure, phase-quantization resolution, and modulation order, up to a scaling factor bounded between 1 and 2. The results show that channel correlation primarily degrades the coding gain, leading to an SNR penalty, while the diversity gain is preserved when the channel covariance matrix is full-rank. The analytical findings are validated through Monte Carlo simulations, demonstrating a tight match across a wide SNR range.

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arXiv2026

SEP Analysis of a Low-Resolution SIMO System with M-PSK over Fading Channels

In this paper, the average symbol error probability (SEP) of a phase-quantized single-input multiple-output (SIMO) system with M-ary phase-shift keying (PSK) modulation is analyzed under Rayleigh fading and additive white Gaussian noise. By leveraging a novel method, we derive exact SEP expressions for a quadrature PSK (QPSK)-modulated n-bit phase-quantized SIMO system with maximum ratio combining (SIMO-MRC), along with the corresponding high signal-to-noise ratio (SNR) characterizations in terms of diversity and coding gains. For a QPSK-modulated 2-bit phase-quantized SIMO system with selection combining, the diversity and coding gains are further obtained for an arbitrary number of receive antennas, complementing existing results. Interestingly, the proposed method also reveals a duality between a SIMO-MRC system and a phase-quantized multiple-input single-output (MISO) system with maximum ratio transmission, when the modulation order, phase-quantization resolution, antenna configuration, and the channel state information (CSI) conditions are reciprocal. This duality enables direct inference to obtain the diversity of a general M-PSK-modulated n-bit phase-quantized SIMO-MRC system, and extends the results to its MISO counterpart. All the above results have been obtained assuming perfect CSI at the receiver (CSIR). Finally, the SEP analysis of a QPSK-modulated 2-bit phase-quantized SIMO system is extended to the limited CSIR case, where the CSI at each receive antenna is represented by only 2 bits of channel phase information. In this scenario, the diversity gain is shown to be further halved in general.

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arXiv2026

Data Detection for Massive MIMO Systems with 1-Bit Quantized Dithered Linear Precoding

The power consumption of the analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) in fully digital massive multiple-input multiple-output (MIMO) systems motivates the adoption of low-resolution architectures. In particular, 1-bit DACs reduce the power consumption and hardware complexity at the transmitter, but introduce severe transmit-side quantization distortion. In this paper, we investigate data detection for a point-to-point massive MIMO system with 1-bit DACs at the transmitter, where the linearly precoded signal is dithered prior to quantization, and either full-resolution or 1-bit ADCs at the receiver. Assuming that the dither vector applied at the transmitter is known at the receiver, we first develop softestimation-based data detection methods with symbol-independent dither removal for both full-resolution and 1-bit ADCs. We then introduce a new symbol-dependent linearization of the transmitted signal at the output of the 1-bit DACs and use it to derive maximum-likelihood (ML)-based data detection methods that directly recover the data symbol vector from the received signal. For full-resolution ADCs, this leads to an ML-based method with and without dither removal. For 1-bit ADCs, we develop an approximate ML-based method that exploits the derived statistics of the received signal without dither removal. We also propose low-complexity variants of the ML-based methods to mitigate the exponential complexity growth with the number of streams. Numerical results in terms of symbol error rate highlight the critical role of the dither power and demonstrate that the proposed ML-based methods (along with their low-complexity variants) achieve significant gains over a baseline based on binary ML detection via a homotopy algorithm.

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arXiv2026

Low-Subpacketization MIMO Coded Caching with Flexible Stream Allocation

Subpacketization remains a major obstacle to the practical deployment of coded caching (CC) in multi-antenna wireless networks. In this paper, we propose a low-complexity multiple-input multiple-output (MIMO) CC scheme that enables flexible delivery rate adaptation while substantially reducing subpacketization requirements. The proposed design builds on a virtual decomposition of the broadcast channel and extends the shared-cache model to multi-antenna receivers, enabling adaptive selection of feasible user and stream configurations and thereby providing explicit control over the spatial multiplexing gain under linear decodability constraints. Analytical results show that the proposed framework can asymptotically approach the best-known achievable degrees of freedom (DoF) under linear decodability constraints while requiring orders-of-magnitude lower subpacketization than existing schemes. Numerical evaluations further demonstrate that this flexibility yields notable throughput improvements at practical signal-to-noise ratios.

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arXiv2026

Over-the-Air Beamforming Design for Full-Duplex Cell-Free Massive MIMO Systems

We study a full-duplex (FD) cell-free massive MIMO system where distributed access points (APs) operate in FD mode while user equipments (UEs) remain half-duplex. Although simultaneous uplink (UL) and downlink (DL) transmissions improve spectral efficiency, they introduce residual self-interference, AP-to-AP coupling, and UE-to-UE cross-link interference. Building on prior over-the-air distributed beamforming frameworks, we develop a fully distributed beamforming design based on iterative UL and DL pilot signaling under a joint UL and DL sum mean-square error criterion that explicitly accounts for these interference components. In FD operation, simultaneous UL and DL pilot transmissions cause UE-to-UE pilot leakage, which contaminates the reconstruction of the cross terms required for AP-specific beamforming design. To mitigate this effect, we introduce a pilot-domain projection of the received signals at the UEs, which suppresses the interference component and enables accurate cross-term reconstruction at the APs. In addition, best-response updates at the UEs are employed within the alternating optimization framework to improve convergence under strong UE-to-UE interference. Numerical results demonstrate faster convergence and higher effective sum rate, with particularly significant gains for strongly interfering UEs, compared with both separate UL and DL distributed OTA beamforming training schemes and designs based solely on local channel state information.

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arXiv2026

Achievable DoF Bounds for Cache-Aided Asymmetric MIMO Communications

Integrating coded caching (CC) into multiple-input multiple-output (MIMO) communications can significantly enhance the achievable degrees of freedom (DoF) in wireless networks. This paper investigates a practical cache-aided asymmetric MIMO configuration with cache ratio $γ$, where a server equipped with $L$ transmit antennas communicates with $K$ users, each having $G_k$ receive antennas. We propose three content-aware MIMO-CC strategies: the \emph{min-G} scheme, which treats the system as symmetric by assuming all users have the same number of antennas, equal to the smallest among them; the \emph{Grouping} scheme, which maximizes spatial multiplexing gain separately within each user subset at the cost of some global caching gain; and the \emph{Phantom} scheme, which dynamically redistributes spatial resources using virtual or ``phantom'' antennas at the users, bridging the performance gains of the min-$G$ and Grouping schemes. These strategies jointly optimize the number of users, $Ω$, and the parallel streams decoded by each user, $β_k$, ensuring linear decodability for all target users. Analytical and numerical results confirm that the proposed schemes achieve significant DoF improvements across various system configurations.

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arXiv2026

The Effect of Noise Correlation on MMSE Channel Estimation in One-Bit Quantized Systems

This paper analyzes the impact of spatially correlated additive noise on the minimum mean-square error (MMSE) estimation of multiple-input multiple-output (MIMO) channels from one-bit quantized observations. Although additive noise can be correlated in practical scenarios, e.g., due to jamming, clutter, or other external disturbances, the effect of such correlation on the MMSE channel estimator in this setting remains unexplored in prior work. Against this backdrop, we derive a novel analytical expression for the general MIMO MMSE channel estimator, which is inherently nonlinear in one-bit observations, and accommodates arbitrary channel and noise correlation structures. To further characterize the impact of noise correlation, we subsequently specialize the general MMSE expression to certain tractable multi antenna configurations in which both the channel and the noise assume single-parameter constant correlation structures. Our analyses reveal nontrivial, noise-correlation-induced scenarios in which the estimator remains linear despite non-zero channel and noise correlation parameters. Moreover, the results indicate that, at low-to-medium signal-to-noise ratio, noise correlation improves the MMSE performance when channels are uncorrelated, but degrades performance when channels are strongly correlated.

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arXiv2025

Cache-Aided MIMO Communications: DoF Analysis and Transmitter Optimization

Cache-aided MIMO communications aims to jointly exploit both coded caching~(CC) and spatial multiplexing gains to enhance communication efficiency. In this paper, we analyze both the achievable degrees of freedom~(DoF) under linear processing constraint and the finite-SNR performance of a MIMO-CC system with CC gain $t$, where a server with $L$ transmit antennas communicates with $K$ users, each equipped with $G$ receive antennas. We first demonstrate that the enhanced DoF of $\max_{β, Ω} Ω\times β$ is achievable with linear processing, where the number of users $Ω$ served in each transmission is fine-tuned to maximize DoF, and $β\le \min\big(G, \nicefrac{L \binom{Ω-1}{t}}{\big(1 + (Ω- t - 1)\binom{Ω-1}{t}}\big)\big)$ represents the number of parallel streams decoded by each user. Then, we propose a new class of MIMO-CC schemes using a novel scheduling mechanism leveraging maximal multicasting opportunities to maximize delivery rates at given SNR levels while still adhering to linear processing constraints. This new class of schemes is paired with an efficient linear multicast beamformer design, resulting in a more practical, high-performance solution for integrating CC in future MIMO systems.

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arXiv2025

SEP Analysis of 1-Bit Quantized SIMO Systems with QPSK over Fading Channels

The average symbol error probability (SEP) of a 1-bit quantized single-input multiple-output (SIMO) system is analyzed under Rayleigh fading channels and quadrature phase-shift keying (QPSK) modulation. Previous studies have partially characterized the diversity gain for selection combining (SC). In this paper, leveraging a novel analytical method, an exact analytical SEP expression is derived for a 1-bit quantized SIMO system employing QPSK modulation at the transmitter and maximum ratio combining (MRC) at the receiver. The corresponding diversity and coding gains of a SIMO-MRC system are also determined. Furthermore, the diversity and coding gains of a 1-bit quantized SIMO-SC system are quantified for an arbitrary number of receive antennas, thereby extending and complementing prior results.

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arXiv2025

Massive MIMO with 1-Bit DACs: Data Detection for Quantized Linear Precoding with Dithering

To leverage high-frequency bands in 6G wireless systems and beyond, employing massive multiple-input multipleoutput (MIMO) arrays at the transmitter and/or receiver side is crucial. To mitigate the power consumption and hardware complexity across massive frequency bands and antenna arrays, a sacrifice in the resolution of the data converters will be inevitable. In this paper, we consider a point-to-point massive MIMO system with 1-bit digital-to-analog converters at the transmitter, where the linearly precoded signal is supplemented with dithering before the 1-bit quantization. For this system, we propose a new maximumlikelihood (ML) data detection method at the receiver by deriving the mean and covariance matrix of the received signal, where symbol-dependent linear minimum mean squared error estimation is utilized to efficiently linearize the transmitted signal. Numerical results show that the proposed ML method can provide gains of more than two orders of magnitude in terms of symbol error rate over conventional data detection based on soft estimation.

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arXiv2025

Coordinated Multi-BS SSB Beam Design for Enhanced Initial Access Coverage

Ensuring strong synchronization signal block (SSB) coverage is essential for reliable user equipment (UE) connection during initial access. While techniques such as power boosting and network densification are commonly used, this work explores joint transmission (JT) of SSBs as an alternative to enhance coverage. Although JT is widely applied in data transmission, its use for SSBs has not been explored due to the lack of channel state information, which prevents coherent signal alignment across base stations (BSs). To address this, we propose a repetition-based JT strategy using a small set of predefined phase configurations at the BSs. This enables the UE to coherently combine multiple SSB receptions and achieve constructive gain regardless of its location. To reduce overhead, a limited number of joint beam configurations is selected to maximize the coverage. Simulation results under the line-of-sight conditions show up to 6 dB relative SNR gain with JT of SSBs using 4 BSs, compared to independent SSB transmission under the same resource budget. These results highlight the potential of JT to improve the coverage of SSBs during the initial access.

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arXiv2025

Near-Field MIMO Channel Acquisition: Geometry-Aided Feedback and Transmission Design

Near-field (NF) line-of-sight (LoS) MIMO systems enable efficient channel state information (CSI) acquisition and precoding by exploiting known antenna geometries at both the base station (BS) and user equipment (UE). This paper introduces a compact parameterization of the NF LoS MIMO channel using two angles of departure (AoDs) and a BS-UE relative rotation angle. The inclusion of the second AoD removes the need for fine-grained distance grids imposed by conventional NF channel parametrization. To address the user-specific uplink pilot overhead in multiuser NF CSI acquisition, we propose a scheme that uses a fixed, UE-independent set of downlink pilots transmitted from a carefully selected subset of BS antennas. In dominant LoS conditions, as few as four pilots suffice, with Cramér-Rao bound (CRB) analysis confirming that increased antenna spacing improves estimation accuracy. Each UE estimates and quantizes its angular parameters and feeds them back to the BS for geometry-based CSI reconstruction, eliminating the need for full channel feedback. To enhance robustness against noise, quantization errors, and non-line-of-sight (NLoS) components, we introduce a two-stage precoding method. The initial precoding is computed from estimated LoS CSI and refined through bidirectional over-the-air (OTA) training. Furthermore, a two-step stream allocation strategy reduces pilot and computational overhead. Simulations demonstrate that the proposed approach achieves high data rates with significantly fewer OTA iterations, approaching the performance of perfect CSI.

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arXiv2025

SIC-free Multicast Scheduling for Multi-antenna Coded Caching

Multi-antenna coded caching (CC) with multicast beamforming typically relies on a complex successive interference cancellation (SIC) structure to decode a superposition of multiple streams received by each user. Signal-level CC schemes require the regeneration and cancellation of interfering signals at the physical layer of each receiver, which complicates practical implementations. To address this, we propose a bit-level multicast scheduling scheme enabling linear, SIC-free decoding of parallel streams by repeatedly transmitting data terms with linearly independent coefficients. Two reference strategies and a novel sparse strategy are considered for constructing the coefficient matrix. The reference cases include the random strategy, which lacks control over matrix construction, and the equal-distant strategy, which balances users' interference and data terms equally. In contrast, the sparse strategy minimizes the number of multicast streams transmitted in parallel during each interval. This approach simplifies both the decoding process and the beamforming design by decoupling the desired data terms for each user and reducing the number of SINR constraints, respectively. To further enhance the symmetric rate, a successive projection algorithm is applied to exploit channel properties and optimize user ordering. With the coefficient matrix and optimized user ordering in place, multicast beamformers are devised to aggregate desired data from relevant multicast streams. Numerical simulations validate the effectiveness of the sparse strategy and user scheduling, demonstrating significant gains in symmetric rate.

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arXiv2025

On Optimal MMSE Channel Estimation for One-Bit Quantized MIMO Systems

This paper focuses on the minimum mean squared error (MMSE) channel estimator for multiple-input multiple-output (MIMO) systems with one-bit quantization at the receiver side. Despite its optimality and significance in estimation theory, the MMSE channel estimator has not been fully investigated in this context due to its general non-linearity and computational complexity. Instead, the typically suboptimal Bussgang linear MMSE (BLMMSE) estimator has been widely adopted. In this work, we develop a new framework to compute the MMSE channel estimator that hinges on computation of the orthant probability of the multivariate normal distribution. Based on this framework, we determine a necessary and sufficient condition for the BLMMSE channel estimator to be optimal and equivalent to the MMSE estimator. Under the assumption of specific channel correlation or pilot symbols, we further utilize the framework to derive analytical expressions for the MMSE channel estimator that are particularly convenient for computation when certain system dimensions become large, thereby enabling a comparison between the BLMMSE and MMSE channel estimators in these cases.

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