Short channel coherence time and oscillator phase noise are two major impairments in millimeter-wave (mmWave) communication systems. Several studies indicate that a substantial fraction of the available bandwidth may be required as overhead to compensate for these impairments, potentially exceeding one third of the total capacity. In this paper, we study Direction-Shift Keying (DSK), a variant of Spatial Modulation (SM), which encodes information in the Direction-of-Arrival (DoA) rather than in the signal amplitude or phase. DSK is implemented over a Distributed Antenna System (DAS), enabling angular resolvability of the transmitted signals. We first derive the structure of the optimal detector for a mobile device equipped withMantennas. We then introduce and characterize the Direction Coherence Time (DCT), defined as the temporal interval over which the DoA remains approximately invariant. Our analysis shows that DCT scales withd/v(transmitter-receiver distance over velocity), whereas the conventional Channel Coherence Time (CCT) scales with λ/v, revealing a coherence-time gain proportional tod/λ, which can exceed several orders of magnitude in mmWave systems. Furthermore, we show that the proposed detector inherently cancels receiver phase noise, eliminating the need for explicit phase-noise tracking. Simulation results validate the analytical findings and demonstrate the robustness of DSK in mobile mmWave environments in the presence of phase noise.

Frequency multipliers are increasingly utilized for signal up-conversion in modern wireless communication systems, particularly in millimeter-wave (mmWave) and sub-terahertz (sub-THz) bands, owning to their simplicity and ease of integration. However, their inherent nonlinearity causes distortions, fundamentally altering the temporal and spectral characteristics of transmitted signals. This distortion transforms well-defined baseband pulses (e.g., sinc, raised cosine) into complex, hardware-dependent waveforms, where the matched-filter depends both on the multiplication order and the specific hardware implementation. Notably, the spectral occupancy of the transmitted signal expands after frequency multiplication. Without accurate knowledge of the multiplier-induced distortions at the receiver, applying a mismatched filter can cause severe inter-symbol interference and loss of critical frequency components, signal-to-noise ratio degradation thereby degrading detection performance. In this paper, we propose a blind, adaptive matched-filter estimation approach leveraging a Long Short-Term Memory (LSTM) neural network. Our method directly estimates the matched filter from sampled segments of the noisy modulated received signal without requiring pilot symbols. The proposed model adapts to dynamic pulse shapes and amplitudes by implicitly learning the spectral transformations introduced by hardware-induced nonlinearities. Simulation results demonstrate high accuracy of the matched filter estimation, with a mean-square error precision of four decimal places.

The Open Radio Access Network (O-RAN) paradigm fosters multi-vendor interoperability, allowing modules from different vendors to cooperatively handle network functions, such as temporary data processing or sensor data collection for network operations optimization. However, this integration agility introduces the risk of selecting suboptimal or adversarial modules, leading to moral hazard. Traditional Moral Hazard testing approaches typically rely on a benchmarking data set in addition to historical performance score. However, they deemed impractical, as vendor-supplied modules may not reveal their outputs before deployment, and the network may lack direct access to reference results for validation. This challenge is further compounded by the dynamic nature of network elements and AI-driven models, whose performance can degrade over time due to malicious tampering, obsolescence, or device deterioration, making historical quality assessments ineffective. In this paper, we address the challenge of identifying legitimate vendor-supplied modules among adversarial ones, with respect to a given network functionality/operation, in the absence of benchmarks. We propose a benchmark-free test framework that detects and eliminates adversarial modules using a methodology inspired by the WereWolf game, combined with zero-knowledge proof techniques. Monte Carlo simulations demonstrate that our approach effectively removes adversarial entities while preserving the privacy of legitimate modules.

There is a growing interest in codebook-based beam-steering for millimeter-wave (mmWave) systems due to its potential for low complexity and rapid beam search. A key focus of recent research has been the design of codebooks that strike a trade-off between achievable gain and codebook size, which directly impacts beam search time. Statistical approaches have shown promise by leveraging the likelihood that certain beam directions (equivalently, sets of phase-shifter configurations) are more probable than others. Such approaches are shown to be valid for static, non-rotating transmission stations such as base stations. However, for the case of user terminals that are constantly changing orientation, the possible phase-shifter configurations become equally probable, rendering statistical methods less relevant. On the other hand, user terminals come with a large number of possible steering vector configurations, which can span up to six orders of magnitude. Therefore, efficient solutions to reduce the codebook size (set of possible steering vectors) without compromising array gain are needed. We address this challenge by proposing a novel and practical codebook refinement technique, aiming to reduce the code book size while maintaining array gain within$\gamma\ \mathbf{dB}$of the maximum achievable gain at any random orientation of the user terminal. We project that a steering vector at a given angle could effectively cover adjacent angles with a small gain loss compared to the maximum achievable gain. We demonstrate experimentally that it is possible to reduce the codebook size from 102416to just a few configurations (e.g., less than ten), covering all angles while maintaining the gain within$\gamma=3\ \mathbf{dB}$of the maximum achievable gain.

With the emergence of the Open Radio Access Network (ORAN) concept and related standardization efforts, future radio access networks are anticipated to feature elements from diverse vendors. Although the ORAN elements can authenticate as legitimate, the system may fail to meet service requirements if some network components do not adhere to their respective agreements, i.e., moral hazard. This issue raises concerns about the network's end-to-end performance, complicating fault attribution and conflict resolution. Therefore, there is a need for an automated zero-trust framework capable of continuously detecting instances of moral hazard. The complexity is exacerbated by the dynamic nature of network elements or artificial intelligence (AI) model performance, which may degrade over time intentionally (e.g., malicious tampering) or unintentionally (e.g., model obsolescence or device performance decline), limiting the effectiveness of offline testing. To address this, we develop a mechanism based on subjective logic principles, incorporating a logic-based argumentation framework that explicitly accommodates argument schemes, argument accrual, and burden of proof. Building upon this framework, we apply contract theory to incentivize compliant devices to participate truthfully in the ORAN ecosystem, thereby enhancing system performance. The simulation results show improved system efficiency and reduced operational costs.

The Sub-6GHz multi-path channel model suggests that the angle of arrivals (AoAs) and angle of departures (AoDs) of dominant rays follow a uniform distribution. Moreover, AoA/AoD varies interdependently from one coherence time/space to another. Several of the recent works on millimeter wave (mmWave) transmissions suggest otherwise, where some presume that it is possible to predict the AoAs/AoDs from nearby users (correlation over space) while others presume that beamforming coherence distance/time is higher than the channel coherence distance/time. The results in existing works, however, are often based on abstract models (two rays model), simulation results (typically rays tracing simulator), and, in many cases, the presence of a Line-of-Sight (LoS) link. In an effort to support or refute such a conjecture, we have carried out a real-world experiment in indoor office environments with high Non-LoS (NLoS) probability. We use statistical Bayesian learning to infer a statistical model on AoAs and extract insightful information.

The wireless industry is moving towards developing smart cellular architectures that dynamically adjust the use of the network elements according to the service demand, and automating their operations in order to minimize both capital expenditure (CAPEX) and operation expenditure (OPEX). This involves developing efficient and unsupervised radio access network (RAN) planning, which has a direct impact on the system performance and CAPEX. This intelligent cellular planning aims at providing the base stations (BSs) configurations (e.g., coverage, user associations and antenna radiation pattern) that minimize the number of deployed BSs and meet the requirements in terms of coverage and capacity. The cellular planning optimization problem has been shown to be complex and non-scalable. Moreover, most of the existing cellular planning techniques result in an over or under provisioning architecture. Motivated by the above, we propose in this paper a novel and efficient unsupervised planning process. We make use of statistical machine learning (SML) to solve the problem at hand. The core idea of SML is that the planning parameters are treated as random variables. The parameters that maximize the corresponding joint probability distribution, conditioned on observations of users' positions, are learned or inferred using Gibbs sampling theory and Bayes' theory. To apply this theory to the planning problem, we make significant efforts to properly formulate the problem to be able to incorporate the constraints into the inference process and extract the planning parameters from the inferred model. Through several numerical examples, we compare the performance of the proposed approach to clustering-based and optimization-based existing planning approaches, and demonstrate the efficacy of our approach. We also demonstrate how our approach can leverage existing cellular infrastructures into the new design.

In recent years, providing connectivity to fast-moving vehicles on highways has been the focus of the wireless research community. In this paper, in the context of V2X, we propose using unmanned aerial vehicles (UAVs) to serve vehicles on a highway, where a UAV is dispatched in disaster situations (such as floods or earthquakes) to serve these vehicles, or to provide better coverage when vehicles are out of reach of road side units. We consider free flow scenario where vehicles moving between two road-side units and where the infrastructure is partially or totally unavailable. Our goal is to guarantee a certain Quality of Service (QoS) for each vehicle on the highway by jointly optimizing the UAV trajectory and the radio resource allocation. We show that during the UAV flight time, the UAV adapts its velocity to the velocities of the vehicles in the served cluster, to maximize the minimum average rate for each vehicle. Our findings are verified through Monte-Carlo simulation where we demonstrate the effectiveness of our proposed design under different UAVs types.

Next-generation cellular systems are anticipated to support 100 times higher data rates (ultra-high rate) compared with the fourth generation (4G) of cellular systems. It is, therefore, necessary to develop novel spectrally efficient uplink/downlink techniques. Multiple techniques have been proposed, including the so-called non-orthogonal multiple access (NOMA) technique. However, the spectral efficiency gains achieved by NOMA over OMA techniques have been shown to be modest. Recently, we proposed a spectrally efficient technique for the downlink channel, which involves exploiting similarities among users' short bit blocks, where we showed that spectral efficiency gains of up to three times that of OMA schemes can be achieved. However, the technique cannot be extended to the uplink scenario because users are not aware of each other's bit block. To this end, we propose in this paper a spectrally efficient scheme for the uplink channel, where we exploit the similarity between the short bit blocks of the uplink and downlink sequences corresponding to one user. The downlink bit sequences are those received by a user from the base station (BS). It is assumed that the BS keeps track of the bit sequences transmitted on the downlink channel to different users. The uplink and downlink bit sequences, which are assumed to be uncorrelated, are divided into bit blocks of short lengths, and then, the similarity between those blocks is extracted. Once each user determines its similarity index (i.e., the number of similar bit blocks) between its own bit sequence and its respective downlink bit sequence, this information is communicated with the BS, which will, in turn, select the user with the largest similarity index to transmit during that resource block. The same process repeats every resource block where the user with the maximum similarity index is always selected. We propose a simple overhead exchange algorithm that facilitates the exchange of the information on the similarity indexes between the users and the BS, where we assume that this exchange of information is done through a control channel. The performance of the proposed scheme and the overhead exchange algorithm is investigated analytically and by Monte Carlo simulations. Among the parameters that we incorporate into the analysis are the user density, the length of bit blocks used to check the similarity index, and the channel correlation. We show that spectral efficiency gains of approximately two times that of OMA schemes can be achieved.

Non-orthogonal multiple access (NOMA) has been proposed as an alternative to orthogonal multiple access (OMA) in an effort to enhance the spectral efficiency of 5G cellular systems. However, the NOMA throughput gain relative to that of OMA has been shown to be modest. In this paper, we propose a novel NOMA scheme that exploits the partial overlap (i.e., similarity) among users bit sequences at the base station (BS). Specifically, users bit sequences are divided into blocks of short lengths, i.e., short bit sequences. Then, one user is selected and served during a given transmission time interval (TTI). Users whose bit sequences partially overlap with the bit sequence of the served user are also (partially) served during the same TTI. At the receiving end, the receiver corresponding to the served user recovers its entire bit sequence, whereas the partially served users recover their corresponding overlapping bit blocks and ignore the rest of the sequence. The performance of the proposed scheme is analyzed in terms of the overall throughput. We show that a throughput gain of up to three times that of existing OMA schemes can be achieved. Moreover, we show that the average rate per user decreases slightly as the number of users increases, whereas it linearly decreases with the number of users in existing NOMA schemes. We stress here that the proposed scheme completely differs from existing NOMA schemes as the latter schemes are based on power allocation at the BS where successive interference cancellation is normally used. The implication of this is that the proposed scheme provides substantial throughput gains without causing interference among users and without adopting a specific power allocation at the BS.

Cooperative relaying is often deployed to enhance the communication reliability (i.e., diversity order) and consequently the end-to-end achievable rate. However, this raises several security concerns when the relays are untrusted, since they may have access to the relayed message. In this paper, we study the achievable secrecy diversity order of cooperative networks with untrusted relays. In particular, we consider a network with an N-antenna transmitter (Alice), K single-antenna relays, and a single-antenna destination (Bob). We consider the general scenario, where there is no relation between N and K, and therefore, K can be larger than N. Alice and Bob are assumed to be far away from each other, and all communication is done through the relays, i.e., there is no direct link. Providing secure communication while enhancing the diversity order has been shown to be very challenging. In fact, it has been shown in the literature that the maximum achievable secrecy diversity order for the adopted system model is one (while using artificial noise jamming). In this paper, we adopt a nonlinear interference alignment scheme that we have proposed recently to transmit the signals from Alice to Bob. We analyze the proposed scheme in terms of the achievable secrecy rate and secrecy diversity order. Assuming Gaussian inputs, we derive an explicit expression for the achievable secrecy rate and show analytically that a secrecy diversity order of up to min(N, K) - 1 can be achieved using the proposed technique. We provide several numerical examples to validate the obtained analytical results and demonstrate the superiority of the proposed technique to its counterparts that exist in the literature.

The notion of non-orthogonal multiple access (NOMA) for 5G essentially relies on the availability of the channel state information at the transmitter (CSIT). Such knowledge is used to judiciously allocate power among users to make their signals separable at their respective receivers while employing successive interference cancellation (SIC). Feeding back the CSI from the users to the BS (transmitter) is obviously bandwidth consuming. Reducing such an overhead is of great importance and has been of interest in recent years. Furthermore, existing NOMA techniques become inapplicable when the CSI is unavailable at the BS. In this case, the BS has only the option of allocating power among users blindly, including equal power splitting, which has been shown to yield poor performance in terms of outage probability and error probability. This motivates us to develop a NOMA scheme that does not require CSI knowledge at the BS. We make use of a nonlinear interference alignment technique that we have proposed recently, namely, interference dissolution, to develop the proposed NOMA scheme, which allows the BS to communicate with two users simultaneously while keeping signals perfectly separable at their respective receivers. We develop the proposed scheme for multiple-input single-output and single-input single-output downlink channels. We analyze the proposed technique analytically in terms of the achievable degrees-of-freedom and achievable rate per user. We show that the proposed NOMA scheme outperforms existing NOMA techniques in terms of the outage probability and error probability.

Power-domain non-orthogonal multiple access (NOMA) for 5G essentially relies on the availability of the channel state information (CSI) at the transmitter. Feeding back the CSI from the users to the transmitter is clearly bandwidth consuming. In addition, when the CSI is unavailable at the transmitter (CSIT), NOMA techniques become inapplicable, and in such scenario, allocating power among users blindly, including equal power splitting, has been shown to yield poor probability of error performance. To this end, we develop a NOMA technique that does not require CSI knowledge at the transmitter, i.e., with unknown CSIT. The proposed technique allows the transmitter to communicate with multiple users simultaneously while keeping signals perfectly separable at their respective receivers. We apply the proposed technique to a two-user multiple-input single-output (MISO) two-user downlink channel with unknown CSI where the available degree of freedom (DoF) is one. We show that it is possible to allocate 1/2 DoF to each user, implying that the received signals can be perfectly separated at the receiver, i.e., without interference. We analyze the performance of the proposed scheme in terms of the achievable DoF per user and the symbol error rate (SER). We present numerical examples to validate the efficacy of the proposed scheme as a NOMA technique for 5G systems, and compare its performance in terms of the SER to that of existing schemes and demonstrate its superiority.

Real interference alignment is efficient in breaking-up a one-dimensional space over time-invariant channels into fractional dimensions. As such, multiple symbols can be simultaneously transmitted with fractional degrees-of-freedom (DoF). Of particular interest is when the one dimensional space is partitioned into two fractional dimensions. In such scenario, the interfering signals are confined to one sub-space and the intended signal is confined to the other sub-space. Existing real interference alignment schemes yield poor achievable rate at finite signal-to-noise ratio (SNR), which is of interest from a practical point of view. In this paper, we propose a radically novel nonlinear interference alignment technique, which we refer to as Interference Dissolution (ID). ID allows to break-up a one dimensional space into two fractional dimensions while achieving near-capacity performance for the entire SNR range. This is achieved by aligning signals by signals, as opposed to aligning signals by the channel. We introduce ID by considering a timeinvariant, point-to-point multiple-input single-output (MISO) channel. This channel has a one-dimensional space and offers one DoF. We show that, by breaking-up the one dimensional space into two sub-spaces, ID achieves a rate of two symbols per channel use while providing \ DoF for each symbol. We also propose a decoder and prove its optimality. We compare numerically the performance of ID in terms of the achievable rate performance to that of existing schemes and demonstrate ID's superiority.

In this paper, we study the achievable secure degrees-of-freedom (sdof) for the multiple-input singleoutput (MISO) wiretap channel with an unknown eavesdropper. It is assumed that the eavesdropper's (Eve's) channel state information (CSI) is unknown to the transmitter (Alice) and legitimate receiver (Bob). Recent studies have shown that the achievable sdof in the sense of strong secrecy is zero when Eve's number of antennas is equal to or more than Bob's number of antennas, which is the scenario considered in this paper. To this end, we propose a novel precoding technique and a coding strategy that together achieve full sdof in the sense of strong secrecy without knowing Eve's CSI and without using artificial noise. The proposed precoding method uses the CSI of the Alice-Bob channel in a nonlinear fashion, which makes the transmitted symbols undecodable at Eve. The proposed coding scheme is based on the channel resolvability concept and ensures strong secrecy. Achieving full sdof with an unknown Eve's CSI is significant, because it is contrary to what is believed about the achievable sdof for the MISO wiretap channel in the sense of strong secrecy. We also show that the proposed scheme achieves near Alice-Bob's channel capacity in the sense of strong secrecy with a probability approaching one at finite signal-to-noise ratio.

In full duplex relaying, the direct link and the decode and forward processing delay are not always negligible. The signal transmitted by the source thus interferes, at the destination, with the delayed signal retransmitted by the relay. This paper presents a novel full duplex transmission scheme based on distributed Alamouti encoding (denoted by FDAE) that eliminates the interference problem and combines efficiently each transmitted signal and its delayed copy at the destination for decode and forward relaying. The performances of FDAE are compared to the full duplex system with interference at the destination (denoted by FDI) and to the conventional half duplex relaying. The simulation results show the harmful effect of the interference problem on the end-to-end achievable data rate and on the bit error rate. They also show that our proposed scheme provides a highest end-to-end achievable data rate and lower bit error rate than FDI due to its ability to take advantage of full duplexing while eliminating interference.

In this paper, we consider a secondary broadcast network where a multi-antenna transmitter broadcasts the same data toward a large number of secondary receivers (SRs) in the presence of a primary communication. Thanks to its multi-antenna capabilities, the secondary transmitter (ST) uses an orthogonal beamforming technique to broadcast its data while controlling the interference perceived by the primary receiver. We develop and investigate three broadcast transmission schemes. The first one is simple and operates in underlay mode where the ST broadcasts its data simultaneously as the primary transmission. The second scheme operates in overlay mode where ST helps the primary transmission by means of cooperative diversity transmission. SRs exploit a post-transmission interference cancellation techniques to cancel the interference caused by the primary transmission. The third scheme operates also in overlay mode and the secondary network exploits also the cooperative diversity technique. The metric used to evaluate the performance of secondary broadcast network is the rate of served SRs. We compare the performances of the three schemes by simulations. Also, analytical expressions of the outage probability for the first and second schemes are provided. Simulations along with analytical results proved that our two overlay proposed schemes ensure low secondary outage probability.