LO-Free Receiver: Next-Gen Low-Power Joint Communication and Sensing

This paper introduces and analyzes Spatial Phase Manifold Communications (SPMC), a paradigm that facilitates joint communication and sensing (JCAS) over Local Oscillator (LO) free receiver. Information is embedded in, and recovered from, the relative spatial phase between antennas. In contrast to conventional coherent receivers that rely on LOs and on channel estimation/equalization, SPMC exploits antenna-domain correlation to form a baseband observable that is a function of inter-antenna phase differences. Since these phase differences are fundamentally tied to Direction-of-Arrival (DoA) and vice-versa, the formulation recasts communication and sensing as inference over the unit-circle manifold and thus naturally supports JCAS decomposition, i.e., data and spatial sensing are encoded and recovered through DoA signatures. We develop a comprehensive framework comprising: (i) a manifold-domain signal model and corresponding phase-alphabet design; (ii) an LO-free quadrature spatial-correlator receiver architecture that resolves the phase-sign ambiguity without requiring an LO; and (iii) an analysis of error probability and sensing precision, including robustness to phase noise. The proposed paradigm is particularly suited to massive Internet-of-Things (IoT) deployments, for which hardware simplicity, LO distribution cost, power consumption, and seamless sensing integration are critical, especially at millimeter-wave and higher carrier frequencies.

Performance Analysis of HAPS-RIS-Assisted MIMO Systems Under Phase-Dependent Amplitude Response Using Saddle Point Approximation

This letter proposes a novel mathematical framework for the statistical characterization of reconfigurable intelligent surface (RIS)-mounted high-altitude platform station (HAPS)-assisted MIMO systems over cascaded Rician fading channels. Due to the inherent coupling introduced by the RIS, the resulting cascaded channel does not satisfy the independence assumptions required for conventional Wishart-based modeling, which motivates a tractable alternative approach. By adopting a line-of-sight (LoS)-aligned precoding strategy, the received signal-to-noise ratio (SNR) is represented as a non-central quadratic form with a structured covariance matrix. Exploiting this structure, a saddle point approximation (SPA)-based framework is developed to characterize the SNR distribution. Closed-form expressions for the probability density function (PDF), cumulative distribution function (CDF), and outage probability are derived. The proposed framework further incorporates practical RIS hardware impairments, including discrete phase shifts and phase-dependent amplitude responses. The accuracy of the proposed analysis is validated through Monte Carlo simulations.

A Novel CSI-RS Reporting Scheme for RIS Optimization in O-RAN-based NextG Networks

Reconfigurable intelligent surface (RIS) technology is a promising enabler for next-generation (NextG) wireless systems, capable of dynamically shaping the propagation environment. Integrating RIS within the open radio access network (O-RAN) architecture enables flexible and intelligent control of wireless links. However, practical RIS-assisted operation requires efficient acquisition and reporting of channel state information (CSI) to support real-time control from the base station side. This paper proposes a CSI reference signal (CSI-RS)-based reporting scheme for downlink complex channel information (CCI) to facilitate RIS optimization in an O-RAN-compliant environment. The proposed framework establishing CCI extraction and CSI-RS reporting procedures is experimentally validated on a real-world testbed integrating an open-source O-RAN system with an RIS prototype operating in the n78 frequency band. Existing channel estimation-based RIS optimization algorithms, including Hadamard and orthogonal matching pursuit (OMP), are tailored for integration into the O-RAN architecture. Experimental results demonstrate notable improvements in received signal power for both near and far users, highlighting the effectiveness and practical viability of the proposed scheme.

Propagation and Rate-Aware Cell Switching Optimization in HAPS-Assisted Wireless Networks

Cell switching is a promising approach for improving energy efficiency in wireless networks; however, existing studies largely rely on simplified models and energy-centric formulations that overlook key performance-limiting factors. This paper revisits the cell switching concept by redefining its modeling assumptions and mathematical formulation, explicitly incorporating realistic propagation effects such as building entry loss (BEL) and atmospheric losses relevant to non-terrestrial networks (NTN), particularly high-altitude platform station (HAPS). Beyond proposing a new cell switching strategy, the conventional energy-focused problem is reformulated as a multi-objective optimization framework that jointly minimizes power consumption, unconnected users, and data rate degradation. Through this reformulation, the proposed methods ensure that energy-efficient operation is achieved without compromising user connectivity and data rate performance, thereby inherently supporting sustainability objectives for sixth-generation (6G) networks. To solve this reformulated problem, two complementary approaches are employed: the weighted sum method (WSM), which enables flexible and adaptive weighting mechanism, and the {ε-constraint-inspired method (εCM), which converts connectivity and rate-related objectives into constraints within the conventional energy-focused problem. Moreover, unlike prior work relying only on simulations, this study combines system-level simulations with Sionna-OpenAirInterface (OAI) based emulation on a smaller network to validate the proposed cell switching concept under realistic conditions. The results show that, compared to the conventional approach, WSM reduces rate degradation for up to 70% for high-loss indoor users and eliminates the 44% drop for low-loss indoor users.

ISAC-over-NTN: HAPS-UAV Framework for Post-Disaster Responsive 6G Networks

In disaster scenarios, ensuring both reliable communication and situational awareness becomes a critical challenge due to the partial or complete collapse of terrestrial networks. This paper proposes an integrated sensing and communication (ISAC) over non-terrestrial networks (NTN) architecture referred to as ISAC-over-NTN that integrates multiple uncrewed aerial vehicles (UAVs) and a high-altitude platform station (HAPS) to maintain resilient and reliable network operations in post-disaster conditions. We aim to achieve two main objectives: i) provide a reliable communication infrastructure, thereby ensuring the continuity of search-and-rescue activities and connecting people to their loved ones, and ii) detect users, such as those trapped under rubble or those who are mobile, using a Doppler-based mobility detection model. We employ an innovative beamforming method that simultaneously transmits data and detects Doppler-based mobility by integrating multi-user multiple-input multiple-output (MU-MIMO) communication and monostatic sensing within the same transmission chain. The results show that the proposed framework maintains reliable connectivity and achieves high detection accuracy of users in critical locations, reaching 90% motion detection sensitivity and 88% detection accuracy.

Joint Phase Shift Optimization and Precoder Selection for RIS-Assisted 5G NR MIMO Systems

By intelligently reconfiguring wireless propagation environment, reconfigurable intelligent surfaces (RISs) can enhance signal quality, suppress interference, and improve channel conditions, thereby serving as a powerful complement to multiple-input multiple-output (MIMO) architectures. However, jointly optimizing the RIS phase shifts and the MIMO transmit precoder in 5G and beyond networks remains largely unexplored. This paper addresses this gap by proposing a singular value ($\lambda$)-based RIS optimization strategy, where the phase shifts are configured to maximize the dominant singular values of the cascaded channel matrix, and the corresponding singular vectors are utilized for MIMO transmit precoding. The proposed precoder selection does not require mutual information computation across subbands, thereby reducing time complexity. To solve the $\lambda$-based optimization problem, maximum cross-swapping algorithm (MCA) is applied while an effective rank-based method is utilized for benchmarking purposes. The simulation results show that the proposed precoder selection method consistently outperforms the conventional approach under $\lambda$-based RIS optimization.

Interference Modulation: A Novel Technique for Low-Rate and Power Efficient Multiple Access

The majority of spatial signal processing techniques focus on increasing the total system capacity and providing high data rates for intended user(s). Unlike the existing studies, this paper introduces a novel interference modulation method that exploits the correlation between wireless channels to enable low-data-rate transmission towards additional users with a minimal power allocation. The proposed method changes the interference power at specific channels to modulate a low-rate on-off keying signal. This is achieved by appropriately setting the radiation pattern of front-end components of a transmitter, i.e., analog beamforming weights or metasurface configuration. The paper investigates theoretical performance limits and analyzes the efficiency in terms of sum rate. Bit error rate simulation results are closely matched with theoretical findings. The initial findings indicate that the proposed technique can be instrumental in providing reduced capability communication using minimal power consumption in 6G networks.

Theoretical and Experimental Assessment of Large Beam Codebook at mmWave Devices: How Much is Enough?

Modern millimeter wave (mmWave) transceivers come with a large number of antennas, each of which can support thousands of phase shifter configurations. This capability enables beam sweeping with fine angular resolution, but results in large codebook sizes that can span more than six orders of magnitude. On the other hand, the mobility of user terminals and their randomly changing orientations require constantly adjusting the beam direction. A key focus of recent research has been on the design of beam sweeping codebooks that balance a trade-off between the achievable gain and the beam search time, governed by the codebook size. In this paper, we investigate the extent to which a large codebook can be reduced to fewer steering vectors while covering the entire angular space and maintaining performance close to the maximum array gain. We derive a closed-form expression for the angular coverage range of a steering vector, subject to maintaining a gain loss within \(\gamma\) dB (e.g., 2\, dB) with respect to the maximum gain achieved by an infinitely large codebook. We demonstrate, both theoretically and experimentally, that a large beam-steering codebooks (such as the \(1024^{16}\) set considered in our experiment) can be reduced to just a few steering vectors. This framework serves as a proof that only a few steering vectors are sufficient to achieve near-maximum gain, challenging the common belief that a large codebook with fine angular resolution is essential to fully reap the benefits of an antenna array.

On Outage Analysis of OTFS Based LEO-Satellite Systems With HAPS Relaying

This paper presents an Orthogonal Time Frequency Space (OTFS) waveform application along with a high altitude platform station (HAPS) relaying for remedying severe Doppler effects in non-terrestrial networks (NTNs). Taking practical challenges into consideration, HAPS is exploited as a decode and forward relay node to mitigate the high path loss between a satellite and a base station (BS). In addition, a maximum ratio transmission scheme with multiple antennas at the LEO-satellite is utilized to maximize Signal-to-Noise Ratio (SNR). A shadowed Rician fading model is employed for the channel realization between the LEO-satellite and the HAPS while Nakagami-m is used between the HAPS and the BS. We derive the closed-form expression of the outage probability (OP) for the end-to-end system. The theoretical and simulation results demonstrate that the OP can significantly decrease when the OTFS order and the number of transmit antennas increase.

RIS Meets O-RAN: A Practical Demonstration of Multi-user RIS Optimization through RIC

Open Radio Access Network (O-RAN) along with artificial intelligence, machine learning, cloud and edge networking, and virtualization are important enablers for designing flexible and software-driven programmable wireless networks. In addition, Reconfigurable Intelligent Surfaces (RIS) represent an innovative technology to direct incoming radio signals toward desired locations by software-controlled passive reflecting antenna elements. Despite their distinctive potential, there has been limited exploration of integrating RIS with the O-RAN framework, an area that holds promise for enhancing next-generation wireless systems. This paper addresses this gap by designing and developing the RIS optimization xApps within an O-RAN-based real-time 5G environment. We perform extensive measurement experiments using an end-to-end 5G testbed including the RIS prototype in a multi-user scenario. The results demonstrate that the RIS can be utilized either to boost the performance of the selected user or to provide the fairness among the users or to balance the tradeoff between the performance and fairness.