Reconfigurable intelligent surfaces (RIS) have emerged as a transformative technology for next-generation wireless networks, offering unprecedented control over radio propagation environments. However, their passive nature and ease of deployment introduces security vulnerabilities that remain largely unexplored. This paper investigates a spoofing attack where a malicious RIS strategically manipulates its reflection coefficients to impersonate a legitimate RIS, thereby deceiving the base station (BS) and gaining unauthorized network access. To counter this threat, we propose a novel authentication framework that formulates the detection problem as a data-driven binary classification task, leveraging conditional generative adversarial networks (cGAN). The framework employs a U-Net-based generator to synthesize realistic attack scenarios during training, while the discriminator serves as a lightweight authenticator enabling robust authentication without requiring apriori knowledge of attacker strategies. Through extensive simulations across diverse attack scenarios, including co-located and correlated configurations, we demonstrate that the trained discriminator achieves 96.4% detection accuracy against malicious RIS attackers positioned near the BS (co-located) and maintains 86.2% accuracy under correlated attack conditions.

According to the recent 3GPP decisions on 6G air interface, orthogonal frequency-division multiplexing (OFDM)-based waveforms are the primary candidates for future integrated sensing and communication (ISAC) systems. In this paper, we consider a monostatic sensing scenario in which OFDM is used for the downlink and its reflected echo signal is used for sensing. OFDM and discrete Fourier transform-spread OFDM (DFT-s-OFDM) are the options for uplink transmission. When OFDM is used in the uplink, the power difference between this signal and the echo signal leads to a power-domain non-orthogonal multiple access (PD-NOMA) scenario. In contrast, adopting DFT-s-OFDM as uplink signal enables a waveform-domain NOMA(WD-NOMA). Affine frequency-division multiplexing (AFDM) and orthogonal time frequency space (OTFS) have been proven to be DFT-s-OFDM based waveforms. This work focuses on such a WD-NOMA system, where AFDM or OTFS is used as uplink waveform and OFDM is employed for downlink transmission and sensing. We show that the OFDM signal exhibits additive white Gaussian noise (AWGN)-like behavior in the affine domain, allowing it to be modeled as white noise in uplink symbol detection. To enable accurate data detection performance, an AFDM frame design and a noise power estimation (NPE) method are developed. Furthermore, a two-dimensional orthogonal matching pursuit (2D-OMP) algorithm is applied for sensing by iteratively identifying delay-Doppler components of each target. Simulation results demonstrate that the WD-NOMA ISAC system, employing either AFDM or OTFS, outperforms the PD-NOMA ISAC system that uses only the OFDM waveform in terms of bit error rate (BER) performance. Furthermore, the proposed NPE method yields additional improvements in BER.

For high-resolution sensing in integrated sensing and communication (ISAC) systems, the deployment of extra-large antenna arrays (XLAAs) is essential. This, however, renders the traditional point target (PT) model inaccurate. Instead, targets must be considered as having a spatial extent over range and angle, necessitating their modeling as extended targets (ET) for accurate sensing, especially within the near-field propagation region. This shift to ET modeling often entails a significant increase in energy consumption, and reduced sum-rate and increased latency for the communication users compared to the simpler PT model. To address this critical trade-off, this paper proposes an antenna selection strategy for XLAA-based ISAC. By selectively activating antenna elements, the proposed ISAC design aims to maintain effective far-field PT operating conditions, thereby enhancing energy efficiency and communication sum-rate. The optimization ensures the communication quality-of-service by enforcing signal-to-interference-plus-noise power ratio constraints for the communication users, while inherently managing the sensing performance evaluated via the Cramer-Rao bound. This strategy provides a controllable operating point, balancing the ET model’s high sensing accuracy, which comes with higher signal processing time and lower communication sum-rate, against the PT model’s lower sensing accuracy but lower processing time and higher sum-rate. Numerical results validate the proposed approach, demonstrating substantial improvements in energy efficiency and sum-rate over pure ET modeling, achieved at a quantifiable cost in sensing accuracy.

Integrated sensing and communication (ISAC) in monostatic in-band full-duplex (IBFD) systems encounters significant challenges due to self-interference (SI) at the radar receiver during concurrent communication and radar operations. This paper proposes a novel waveform-domain self-interference cancellation (SIC) technique that leverages the unique properties of orthogonal frequency division multiplexing (OFDM) and affine frequency division multiplexing (AFDM) signals. The proposed approach designs the integrated dual-functionality frame to utilize OFDM for communication and AFDM for radar sensing, both generated using the same modulator block. Then, we establish the conditions under which a wide sense stationary (WSS) process in the time domain appears as WSS in the affine domain and demonstrate that the interfering OFDM signal behaves as an additive white Gaussian noise (AWGN) in this domain. Exploiting this property, the received signal is projected into the affine domain, where the SI appears as AWGN, enabling its subtraction with minimal residual interference. To further mitigate the residual SI, an iterative low-complexity windowing scheme is applied, selectively locking onto the radar signal to reduce the processed signal space. A subsequent time domain spreading step is applied after converting the SIC-processed signal into the post-coded time domain, wherein the SI diminishes separately across the delay and Doppler axes. The proposed method demonstrates superior performance in terms of detection probability, target’s range and velocity root mean square error (RMSE), while maintaining high spectral efficiency and minimal computational complexity.

Cell-free massive multiple-input multiple-output (CF-mMIMO) is a key enabler for sixth-generation (6G) wireless systems, offering enhanced spectral efficiency and ubiquitous coverage. In such systems, the association of user equipments (UEs) to access points (APs) is a critical challenge, as it directly impacts scalability, interference suppression, and overall system performance. Conventional user association (UA) methods optimize communication throughput but overlook emerging 6G requirements from sensing and integrated sensing and communication (ISAC) applications. To address this, we propose a scalable user association (SUA) scheme for CF-mMIMO networks that explicitly considers heterogeneous UE service needs, including communication, sensing, and ISAC. The proposed SUA scheme integrates AP masking, link prioritization, and optimization-driven AP selection to balance system load and enhance service quality. Simulation results demonstrate that the proposed approach significantly reduces interference and computational runtime, while improving symbol error rate for communication UEs and probability of detection for sensing UEs.

Emerging technologies such as dynamic time division duplexing (D-TDD) in 5G and full-duplex (FD), both considered for 6G, promise higher spectral efficiency and lower latency. D-TDD flexibly allocates uplink and downlink resources to match traffic, while FD enables simultaneous transmission and reception on the same band, boosting capacity. These gains, however, introduce new interference: cross-link interference (CLI) in D-TDD and self-interference (SI) in FD, both of which threaten network robustness. Extra-large multiple-input multiple-output (XL-MIMO) with its near-field (NF) visibility-region (VR) concept offers a promising solution. The core idea in this work is to exploit VRs jointly in space and temporal domain to build a comprehensive interference-management framework. By modeling VR characteristics across spatial and temporal domains, we develop strategies that selectively activate antennas and suppress dominant interferers. We propose a VR-aware antenna-selection method that evaluates overlap and delay structure to minimize CLI and SI without sacrificing desired signal power. Simulation results validate the approach, showing substantial interference reduction and improved reliability and efficiency in XL-MIMO-based cellular systems.

The rapid evolution of mobile technologies presents a formidable security challenge, as traditional cryptographic methods struggle to keep pace. Integrating physical layer security (PLS) solutions with cutting-edge technologies such as in-band full-duplex (IBFD) and reconfigurable intelligent surfaces (RISs) holds promise for addressing these challenges effectively. This study introduces a novel RIS-driven protected zone (PZ) formation approach that employs artificial noise (AN) to safeguard legitimate users without requiringa prioriknowledge of eavesdropper locations, channels, or numbers. The proposed methodology partitions the RIS into two distinct segments: while the former segment enhances the achievable data rate for legitimate signal, the latter segment concurrently amplifies AN to jam illegitimate users within the PZ.We present formulations and solutions for maximizing secrecy capacity (SC) and minimizing power consumption through optimized transmit power allocation factors, RIS segmentation, and beams’ directions, all subject to stringent quality-of-service (QoS) constraints. Closed-form expressions are derived to facilitate efficient implementation and performance optimization. Simulation results validate closed-form solutions and demonstrate that the proposed scheme can significantly enhance SC compared to benchmarks where RIS and AN are used separately, with the proposed scheme achieving approximately 81% greater capacity than the “RIS-Only” approach and a substantial advantage over the “AN-Only” approach, which results in no secrecy. Additionally, this work includes an analysis of energy efficiency, emphasizing the critical importance of optimizing power consumption in practical applications. This dual focus on improving security while effectively managing energy resources underscores the scheme’s practical relevance and efficiency.

This paper investigates the sensing potential of affine frequency division multiplexing (AFDM) in high-mobility integrated sensing and communication (ISAC) from the perspective of radar waveforms. We introduce an innovative parameter selection criterion that establishes a precise mathematical equivalence between AFDM subcarriers and Nyquist-sampled frequency-modulated continuous-wave (FMCW). This connection not only provides a clear physical insight into AFDM's sensing mechanism but also enables a direct mapping from the DAFT index to delay-Doppler (DD) parameters of wireless channels. Building on this, we develop a novel input-output model in a DD-parameterized DAFT (DD-DAFT) domain for AFDM, which explicitly reveals the inherent DD coupling effect arising from the chirp-channel interaction. Subsequently, we design two matched-filtering sensing algorithms. The first is performed in the time-frequency domain with low complexity, while the second is operated in the DD-DAFT domain to precisely resolve the DD coupling. Simulations show that our algorithms achieve effective pilot-free sensing and demonstrate a fundamental trade-off between sensing performance, communication overhead, and computational complexity. The proposed AFDM outperforms classical AFDM and other variants in most scenarios.

The rapid proliferation of mobile technologies introduces substantial security vulnerabilities, with conventional cryptographic approaches increasingly inadequate. Physical layer security (PLS) approaches, especially when paired with advanced methods like full-duplex (FD) communication and reconfigurable intelligent surfaces (RISs), offer substantial potential for enhanced security. This work proposes a novel RIS-aided inband FD (IBFD) framework that employs artificial noise (AN) to establish a protected zone (PZ) around the legitimate user, operating independently of any a priori knowledge regarding the number, positions, or channels of potential eavesdroppers. To achieve this, the RIS is functionally partitioned into two distinct segments: one enhances the legitimate user's data rate, while the other simultaneously intensifies AN to jam any unauthorized users within the PZ. We formulate a secrecy capacity (SC) maximization problem that optimizes both the legitimate user's transmission power and the RIS configuration, while meeting quality-of-service (QoS) requirements. Simulation results indicate the superior efficacy of the proposed technique in enhancing SC compared to benchmarks that employ RIS and AN independently. In particular, the proposed approach achieves an approximate SC improvement of 80% and 49% over the “RISonly” and “AN-only” approaches, respectively, underscoring its significant potential to enable robust PLS in next-generation communication networks.

This paper proposes a novel multi-party key generation method that jointly utilizes channel state information (CSI) and blockchain technology to enhance security in distributed systems. The proposed method starts by extracting CSI from wireless channels, leveraging the channels’ inherent randomness and reciprocity to generate secure key fragments shared among legitimate parties. Then, the key generation process involves several stages, including quantization, reconciliation, and privacy amplification, ensuring that the resulting keys are secure and synchronized across participants. Blockchain technology is then leveraged to securely commit these keys, ensuring that the key agreements are recorded in a decentralized, tamper-resistant ledger. The proposed method effectively combines the physical-layer properties of CSI with the decentralized nature of blockchain, providing robust protection against eavesdropping and tampering attacks. Theoretical analyses and simulation results demonstrate the effectiveness of the proposed method in terms of key mismatch probability and secrecy capacity. Additionally, the randomness of the generated keys by the proposed method is validated using the National Institute of Standards and Technology randomness tests.

Physical layer security (PLS) has garnered increasing attention as a complementary solution to conventional crypto-graphic techniques for addressing the diversity of use cases, deployment scenarios, and device capabilities in today’s wireless networks. Integrating artificial intelligence (AI) into PLS offers a promising solution to various multi-dimensional, heterogeneous, and complex challenges stemming from the growing complexity of networks. However, the opaque nature of AI has raised concerns regarding its trustworthiness and interpretability. This paper addresses these concerns by emphasizing the crucial role of explainability in AI-based PLS in several use cases of next-generation networks. A particular focus is placed on physical layer authentication through an illustrative case study, aiming to enhance AI-empowered PLS’s practicality and trustworthiness. The paper concludes with a discussion of some critical future research directions.

Sub-band full duplex (SBFD) operation, which enables simultaneous uplink (UL) and downlink (DL) transmissions over adjacent subbands, has been introduced as a promising duplexing technique for 6G and beyond. However, SBFD introduces cross-link interference (CLI), particularly between neighboring base stations (gNB-to-gNB), which can severely degrade uplink performance. Uniform UL resource muting algorithms have been proposed in the literature to make accurate CLI measurements for the effectiveness of gNB-to-gNB interference mitigation mechanisms. In this paper, we propose an adaptive and non-uniform UL resource muting scheme that dynamically adjusts the number and position of muted resource elements (REs) based on the estimated large-scale interference power distribution. Furthermore, we introduce a frequency-shaped adjacent channel leakage ratio (ACLR) model to reflect realistic leakage behavior in SBFD networks. Simulation results show that non-uniform muting pattern (NuMP) outperforms uniform muting pattern (UMP) in terms of estimation performance, while also requiring fewer muted resource elements, as demonstrated by lower normalized mean square error (NMSE) values and reduced muting overhead.

Mobility management remains a cornerstone of network evolution, yet ever-tighter latency and reliability targets, heterogeneous deployments, and AI-driven network intelligence demand continual refinement of handover mechanisms. Tracking and understanding recent developments in mobility management is essential to support the integrated, intelligent, and ubiquitous connectivity envisioned for 6G networks. This paper delivers a 3GPP-centric review of progressive mobility enhancements from Rel-15 through Rel-20 and offers insight into the emerging roadmap for 5G-Advanced and early 6G networks. After summarizing baseline measurement procedures and event-triggered reporting, we analyze three principal handover paradigms—Baseline Handover, Conditional Handover, and the recent Lower-Layer Triggered Mobility—highlighting their respective trade-offs in signaling overhead, interruption time, and robustness. We then examine how AI/ML techniques are positioned within 3GPP to predict optimal handover parameters, adapt to dynamic radio conditions, and reduce failure rates. The paper synthesizes Rel-20 hot topics, including mobility enhancements and AI/ML-based mobility use cases, and distills key contributions from 6G standardization meetings. By aligning ongoing 3GPP efforts with performance goals, this work highlights key challenges and outlines directions for future standardization beyond Rel-20.

In this paper, we propose a practical device-free localization and tracking system for mobile objects located in enclosed spaces. The localization is performed by exploiting the RF fingerprints of the object in real time. We investigate three approaches including minimum distance (MD), k-nearest neighbors (KNN), and convolutional neural network (CNN) to obtain centimeter-level localization and tracking. We develop an experimental setup in the laboratory for the proof-of-concept of the proposed methods. This study opens new research directions in the domain of device-free localization and tracking, and offers a scalable and efficient solution for future industrial needs.

In this study, we propose two novel approaches to mitigate cross-link interference (CLI) in a network-controlled repeater (NCR)-assisted integrated sensing and communication (ISAC) network. These approaches include base station (BS) sensing signal transmission (BSST) and an NCR sensing signal transmission (NSST). We implement a power constraint algorithm at the BS to optimize the system performance while ensuring communication reliability and meeting sensing service requirements. Additionally, we investigate the user mobility under the CLI scenarios with different NCR deployments. Specifically, we analyze the NCR connectivity to single and multiple BSs in order to evaluate the received signal reference power and signal-to-interference-plus-noise ratio-based handover (HO) strategies, focusing on radio link failure (RLF), and handover probability. The results show that deploying an NCR-assisted single BS achieves sum rate gains of up to 58.3% and increases in the probability of target detection by 60% compared to networks without assistance. Furthermore, a reduction of RLF by 49.1% is observed in the ISAC networks. These results highlight the effectiveness of NCRs in mitigating CLI and improving the system performance under diverse mobility conditions

The advent of 6G-enabled real-time applications, such as remote surgery and autonomous driving, has sparked significant interest in a novel and integrated metric known as the age of information (AoI). This metric is particularly valuable because it effectively reflects the trade-offs between reliability, latency, and frequent updates. In this paper, we propose an intelligent framework for hybrid automated repeat request (HARQ) enabled rate splitting multiple access (RSMA) networks, aiming to optimize resource utilization while maintaining a balance between timeliness and reliability. Particularly, the source intelligently adapts power allocation and re-transmissions for common and private streams of RSMA carrying data packets of different priorities, considering the current state of AoI and feedback signals. Firstly, an analytical framework is established by deriving closed-form approximations for the individual average block error rates (BLER) of both common and private streams. Subsequently, an AoI minimization problem is formulated using the derived BLER. Following that, the problem is modeled as a Markov decision process (MDP), allowing us to develop an optimal policy for minimizing the system’s average AoI. Moreover, we also devise a near-optimal solution utilizing the Lyapunov drift function, accounting for the MDP’s complexity. Extensive simulations demonstrate that the proposed approach improves the AoI performance of the RSMA scheme and outperforms the conventional approaches.

Wireless sensing has become integral to futuristic intelligent transportation systems encompassing Internet of Things (IoT) and vehicle-to-everything (V2X) networks. In the context of vehicle-to-infrastructure (V2I) scenarios, employing a monostatic pulsed radar on a roadside unit (RSU) to transmit digital linear frequency-modulated (LFM) pulses presents notable progress in obtaining high-resolution and precise sensing information. However, processing of these signals entails the use of expensive high-rate analog-to-digital converters (ADCs). Moreover, reducing the sampling frequency below the Nyquist rate introduces aliasing, which negatively impacts sensing accuracy. To address these challenges, this article investigates hyperbolic frequency-modulated (HFM) pulsed signals for accurate range and the Doppler information of multiple targets at sub-Nyquist sampling rates. Particularly, the inherent nonlinearity of HFM pulses is used to generate distinct aliases when the sampling is done below the Nyquist rate, enabling precise range information through receiver cross-correlation. Performance analysis and simulation results are provided to demonstrate the superiority of sub-Nyquist HFM pulse compression radar over its linear counterpart in terms of range-Doppler estimation, peak-to-sidelobe ratio (PSLR), integrated-sidelobe ratio (ISLR), and probability of detection.

Joint sensing and communication (JSAC) has become increasingly popular in recent years due to spectrum scarcity, hardware limitations, power constraints, and the emergence of applications that require both communication and sensing capabilities. As such, the coexistence of both functionalities remains a challenge for current systems. Therefore, this article proposes a novel orthogonal time-frequency space (OTFS)-chirp waveform. The proposed waveform exploits the sparsity of linear chirps in delay-Doppler domain to multiplex OTFS and chirp in orthogonal manner. This enables simultaneous high-data rate communication and low-complexity accurate sensing simultaneously. Furthermore, we propose a multiuser JSAC scheme where multiple orthogonal chirps (OCs) are assigned to different users within the same OTFS-Chirp waveform. On top of that, a novel chirp-based channel estimation technique is proposed for OTFS systems. The proposed method leverages the sparsity of chirp in both delay-Doppler and Fresnel domains. This approach alleviates the pilot guard overhead and reduces the peak-to-average power ratio (PAPR) of the transmitted signal. The effectiveness of the proposed JSAC waveform is verified by the conducted numerical results that agree with the developed analysis and validate that the proposed waveform design can achieve accurate low-complexity radar parameter estimation while preserving high-data rates.

Unmanned aerial vehicles (UAVs) serve as flexible aerial platforms, enriching air-ground communication networks in various ways. To support massive connectivity within limited time-frequency blocks, non-orthogonal multiple access (NOMA) is proposed to be integrated into UAV networks. However, a common issue associated with almost all NOMA schemes is the susceptibility to inter-user interference (IUI). Therefore, in this paper, we propose a multi-UAV cooperative system aided by NOMA with index modulation (IM), termed MCU-NOMA-IM, to improve the performance of air-ground networks by mitigating IUI and also avoiding the successive interference cancellation (SIC) decoding method that is prone to error floors. With MCU-NOMA-IM, the information bits pertaining to multiple UAVs are mapped into multiple dimensions, including the modulated symbols, subcarrier indices, and energy allocation patterns. To fully investigate the performance of MCU-NOMA-IM on air-ground networks, we consider scenarios in the presence of three and four UAVs and derive upper-bounds for the bit error rates (BERs). In addition, we propose a multi-clustered-UAV cooperative system aided by NOMA with IM (MCCU-NOMA-IM), which groups closely located UAVs into several clusters to reduce the requirement for time resources. Simulation results demonstrate that both MCU-NOMA-IM and MCCU-NOMA-IM greatly outperform cooperative NOMA and non-cooperative NOMA-IM schemes, especially for distant UAVs when the signal-to-noise ratio is sufficiently high. Also, we show that the derived BER upper bounds are asymptotically tight.

In this paper, we propose a unified transceiver framework based on single-carrier interleaved frequency division multiplexing (SC-IFDM) to address key challenges in fifth-generation (5G) and sixth-generation (6G) networks, including spectral efficiency, backward compatibility, structural flexibility, and support for joint sensing and communication (JSAC). Rather than introducing a new parametrizable waveform, we demonstrate that SC-IFDM can serve as a reconfigurable processing backbone capable of generating a wide class of discrete Fourier transform (DFT)-based waveforms through simple phase adjustments and index-specific data placement. This includes orthogonal frequency division multiplexing (OFDM), orthogonal chirp division multiplexing (OCDM), orthogonal time-frequency space (OTFS), affine frequency division multiplexing (AFDM), and frequency modulated continuous wave (FMCW). The framework ensures seamless waveform adaptation and orthogonal coexistence by exploiting sparsity in the DFT domain and maintaining compatibility with legacy systems. We present rigorous architectural analysis, resource allocation strategies, and coexistence mechanisms within shared time-frequency resources. Simulation results validate the proposed scheme, demonstrating its ability to support diverse waveform requirements with improved performance, scalability, and flexibility compared to conventional multi-waveform approaches.

The upcoming sixth generation (6G) wireless networks are designed to support advanced applications that the current air interface based on orthogonal frequency division multiplexing (OFDM) cannot accommodate, necessitating innovations in waveform design. Orthogonal time frequency space (OTFS) has emerged as a promising alternative, offering enhanced performance particularly in high-mobility channel environments. However, deploying fundamentally different waveforms over the same frequencies fails to exploit the mutual relationships between them. In this paper, a forward-compatible yet backward-compatible coexistence framework is proposed, where various OFDM waveform options are incorporated while seamlessly integrating OTFS within the same network. The proposed coexistence paradigm involves utilizing a specially designed spreading matrix in the delay-Doppler (DD) domain to process OTFS data. The matrix is tailored to establish orthogonality between OTFS and OFDM waveforms, effectively reducing cross-interference when both coexist within the same time-frequency (TF) resources. Our results demonstrate up to a 6 dB improvement in bit error rate (BER) performance for the OTFS waveform compared to other coexistence schemes. The proposed approach also shows greater interference resilience and approaches the upper bounds of achievable rates. By utilizing the full bandwidth and time duration, it enhances range and velocity resolutions, leading to improved sensing performance. These findings are supported by mathematical analysis and extensive simulations for uplink scenarios.

As wireless technology advances toward the sixth generation (6G) communication systems, ambient backscatter communication (AmBC) has emerged as a key enabler for low-cost internet of things (IoT) networks. This paper introduces a novel joint localization and communication (JLAC) technique based on orthogonal time sequency multiplexing (OTSM), specifically designed for passive backscatter devices (BDs). The proposed design enhances spectral efficiency by supporting broadband direct link communication, reduces synchronization requirements by leveraging the spreading characteristics of OTSM carriers, and ensures reliable BC even in the presence of strong direct link interference (DLI) without the need for successive interference cancellation (SIC). The approach utilizes pilot carriers that are protected by a guard in the delay-sequency (DS) domain to achieve diversity gains along the delay domain while ensuring zero interference from either the data or the direct link. The scheme also exploits the pilot signal for localization, using received signal strength (RSSI) from BDs to localize the transmitter. Furthermore, the scheme minimizes the energy consumption at the BDs by reducing the switching rate (SR) by a factor ofM. Extensive analysis and simulations demonstrate the proposed OTSM-based JLAC system’s robustness to DLI, synchronization mismatches, power efficiency, and low complexity characteristics.

RSMA is a multiple access method designated to counteract the effects of the multi-user interference (MUI) present in multi-antenna systems. In this study, rate-splitting multiple access (RSMA)’s ability to manage interference is integrated with the flexibility of orthogonal frequency division multiplexing (OFDM) waveform incorporating multi-numerology concept. This fusion aims to confront the issue of inter-carrier interference (ICI) which compromises the orthogonality of OFDM subcarriers. Sum-rate maximization problem is formulated aiming to determine the optimal power and subcarrier allocation for downlink communication in a system with two users. We utilize a transformation grounded in the weighted minimum mean-square error (WMMSE) approach to address the non-convex problem. We show that the marriage of rate-splitting (RS) with OFDM provides complementary strengths to cope with peculiar characteristic of wireless medium and its performance-limiting challenges including ICI, inter-symbol interference (ISI), inter-numerology interference (INI), and MUI. The sum-rate and fairness performance of the proposed multi-numerology OFDM-RSMA approach is numerically evaluated against traditional orthogonal frequency division multiple access (OFDMA) and OFDM-non-orthogonal multiple access (NOMA).

This paper presents a novel transceiver design for multi-numerology systems, enabling efficient spatial multiplexing in downlink communication. Multi-antenna and multi-numerology technologies are vital for modern wireless networks, yet a unified transceiver design that seamlessly integrates both has been absent from the literature. Our proposed design fills this gap, incorporating a tailored precoding scheme. OFDM symbols from different numerologies are grouped into a single encapsulation OFDM symbol for processing. This design facilitates the complete elimination of all interference types through linear precoding. We thoroughly investigate precoding design for both shortening and multiplexing, proposing a new approach that combines waterfilling with filtering of the designed channel gains. Finally, simulation results demonstrate the effectiveness and performance of the proposed transceiver in practical scenarios.

In this study, we propose an orthogonal frequency division multiplexing (OFDM) based scheme to achieve interference-free backscatter communications (BC) in a symbiotic radio system. In this scheme, the backscatter device shifts the primary signal, i.e., the OFDM symbols transmitted from a base station, in the frequency domain to transmit its information. Symbiotically, the base station (BS) empties specific subcarriers within the band so that the received signals from the backscatter device and the primary signal are always orthogonal to each other. To address the channel estimation challenge for the signals arriving from the backscatter device, we consider a non-coherent detector for obtaining the information from the backscatter signal at the receiver. We derive the bit-error rate performance of the detector theoretically. Through the comprehensive simulations, we show that the proposed approach achieves a lower bit-error rate up to 10−4at 30 dB with BC by eliminating direct link interference.

In this paper, we propose a slot-based protocol that does not rely on global-time synchronization to achieve a self- healing mesh network. With the proposed protocol, each node synchronizes with its neighbors locally by adjusting its time to transmit based on the reception instant of a decoded beacon signal. Also, it determines its slots without any coordinator to avoid collisions. Finally, to communicate the messages over the mesh network, it identifies the forwarding nodes on the shortest path without knowing the entire communication graph. We show that the proposed protocol can effectively resolve collisions over time while enabling nodes to synchronize with each other in a distributed manner. We numerically analyze the performance of the proposed protocol for different configurations under a realistic channel model considering asymmetrical links. We also implement the proposed method in practice with Long-Range (LoRa) devices. We demonstrate that the nodes adapt themselves to changes in the network and deliver a message from a sensing node to a reference node via multi-hop routing.

This paper expands sensing capabilities by providing a Joint Imaging and Communication (JIC) system, leveraging millimeter-wave (mm-Wave) technology and sparse antenna array. To address the challenges associated with the high cost and power consumption of dense antenna arrays, we use a sparse antenna array (SAA) to avoid such a problem at the expense of image resolution. The enhancement of acquired image resolution is achieved through the incorporation of multiple low-resolution image components corresponding to distinct transmission-reception combinations. In order to achieve a high level of fairness between communication and imaging performance we formulate a non-convex optimization problem, and then propose an algorithm for finding an approximate solution in a fully digital beamforming case. Numerical results on achievable capacity and image resolution are presented to validate the proposed approach and provide insights into system performance.

Low-Earth orbit (LEO) non-terrestrial networks (NTNs) have become increasingly popular due to their ability to provide high-bandwidth communication in otherwise unserved regions. However, this comes at the cost of high satellite mobility, necessitating efficient handover (HO) strategies. Till now the focus has been on the S-band, however Ka-band is expected to be deployed for high-bandwidth applications necessitating HO studies for higher frequency bands. To address this, we evaluate the performance of the conventional received power-based HO, as well as alternatives such as elevation angle and distance-based triggers for Ka-band LEO networks, and compare them with S-band frequencies. Moreover, a dynamic threshold approach is also evaluated in terms of the number of HOs, unnecessary handovers (UHOs), radio link failures (RLFs), and distributions of downlink carrier-to-noise-plus-interference ratio (CNIR) and mean time-of-stay of a user in a cell. The obtained results indicate the efficacy of power-based mechanisms for the S-band while showing that the alternative methods provide a much better balance at the Ka-band in terms of the overhead and the overall communication link quality.

Rate splitting multiple access (RSMA) has a variety of advantages, including higher throughput, enhanced capacity, and network efficiency, which makes it suitable for beyond fifth generation (5G) networks. Since the combining and splitting operations are performed on the transmitter side, one of the challenging aspects of RSMA is how a retransmission can be accomplished. In this article, an efficient hybrid automatic repeat request (HARQ) design for RSMA networks is presented in which three novel retransmission strategies are developed. More specifically, the main idea is choosing among RSMA, nonorthogonal multiple access (NOMA), and space division multiple access (SDMA) during the HARQ retransmission round, respectively, to do the retransmission. Therefore, a new link adaptation approach is proposed. The effectiveness of the proposed design is analyzed in terms of the average number of retransmissions, energy efficiency (EE), and achievable sum rate. Simulation results confirm the superiority of the proposed protocol in terms of packet error rate, EE, and sum-rate improvement up to 70%, 81%, and 76%, respectively, as compared to the conventional RSMA.

Long-Range (LoRa) technology holds tremendous potential for regulating and coordinating communication among Internet-of-Things (IoT) devices due to its low power consumption and cost-effectiveness. However, LoRa faces significant obstacles such as reduction in coverage area, a high packet drop ratio (PDR), and an increased likelihood of collisions, all of which result in substandard data rates. In this paper, we present a novel approach that employs a relaying node capable of allocating resources dynamically based on signal parameters. In particular, the geometric placement of the relay node is determined by a genetic algorithm that maximizes signal-to-noise ratio (SNR) and signal-to-interference ratio (SIR) success probabilities. Using equal-area based (EAB) spreading factor (SF) distance allocation scheme, the coverage area is sliced into distinct regions in order to derive the success probabilities for different communication stages. Furthermore, we present a frequency channel shuffling algorithm to prevent collisions between end devices (EDs) without increasing the complexity of the relaying nodes. Through extensive simulations, we demonstrate that our proposed scheme effectively expands the coverage area, conserves transmission resources, and enhances the system’s throughput. Specifically, our approach extends the range by up to 40%, increases the throughput by up to 50% compared to conventional methods, and achieves a 40% increase in success probability. To validate the practicality of our approach, we implement our algorithm in an active LoRa network utilizing an ESP32 LoRa SX1276 module, showcasing its compatibility in real-world scenarios.

When using ultra-wideband signaling on massive multiple-input multiple-output (mMIMO) systems, the electromagnetic wave incurs an extra delay (across the array elements) comparable to or larger than the symbol duration, which translates into a shift in beam direction known as the beam squint effect. The beam squinting problem degrades the array gain and reduces the system capacity. This paper proposes a novel transceiver design based on lens antenna subarray and analog subband filters to compensate for the beam squinting effect. Specifically, the proposed design chunks the wideband signal from the phase shifters into groups of narrowband signals and controls their squints through an exhaustive search-based switching/precoding mechanism under the lenses. Furthermore, a simplified, thresholded search-based precoding algorithm is proposed, which demonstrates good performance while significantly minimizing complexity. The proposed system is analyzed in terms of beam gain, complexity, power consumption, and capacity. The numerical results demonstrate significant performance enhancement for the proposed system design as compared to the conventional mMIMO system with an uncompensated beam squinting problem.

The recently popularized ISAC paradigm attempts carry out both communication and sensing functionalities uses the same time-frequency resources to combat the scarcity of these resources. However, high-resolution range and velocity radars require wideband long-duration transmission, which implies complex, costly receivers to sample at a high-frequency rate. In this paper, we propose an orthogonal time-frequency space (OTFS)-based ISAC system which enables achieving highly accurate range-velocity profiles without the need for large bandwidth transmissions or long-duration frames. This approach relaxes the constraints on bandwidth and time while still providing precise sensing information. The proposed scheme exploits a single OTFS carrier with rectangular pulse shaping as a pilot to estimate both simultaneous accruing delay and Doppler, thereby determining range and velocity, respectively. By leveraging the sidelobes of the physical pulse shape of the pilot signal, we propose an algorithm that allows the detection of the range and the velocity of radar targets beyond the resolution limitation set by the time duration and the bandwidth of the transmitted signal. The conducted simulation results along with the real experimental results demonstrate that the proposed design can achieve accurate low-complexity radar parameter estimation.

Physical Layer Authentication (PLA) is a topic of considerable interest in ensuring strong security for upcoming wireless networks. However, existing PLA methods face challenges in maintaining performance in dynamic environments. To overcome this, we propose a novel tracking-based PLA approach, utilizing properties of the beamspace multiple-input multiple-output (MIMO) channel in narrowband millimeter-wave (mmWave) networks. Specifically, In particular, the proposed technique involves extracting a distance signature vector from the positions of the principal components within the beamspace MIMO channel representation. These components are then sorted in descending order based on their indices. To address mobility concerns in dynamic settings, a tracking filter is introduced. This filter allows the authentication system to continuously track and update the stored signature, enhancing overall authentication performance. Additionally, the proposed technique is extended to ultra-wideband signaling. In this extension, the richness of the derived signature is further improved by exploiting the beam squint effect, contributing to a more robust authentication process. Simulation results demonstrate that our approach overcomes the limitations of previous methods, resulting in improved authentication performance measured by detection and false alarm rates.

5th Generation (5G) systems are designed with a more flexible structure compared to previous generations with an increasing variety of applications and services. Thus, new flexibility dimensions are observed in 5G technologies. Furthermore, emergence of these flexibility dimensions is triggered a need for advanced management paradigms for 5G and beyond. It is expected that application richness, flexibility dimensions, and the related management paradigms will show an increase with 6th Generation (6G) systems. It is possible that different flexibilities related to the waveform design can be introduced in 6G while a uniform method is used in 5G and previous generations. One of these flexibilities can be the ability to make selection through a waveform set for a new capability to meet different application and user requirements with the waveform selection. In this paper, waveform selection approaches are proposed based on machine learning (ML) with single-stage and multi-stage networks for the waveform management in the same coverage area under the assumption that multiple waveforms can be used in 6G. Hence, the problem of deciding on the best waveform for a coverage area considering different requirements and environmental conditions is studied. To provide environmental awareness, a new synthetic dataset is formed with an example simulation setup. Moreover, a feature control algorithm is proposed to limit side effects of the waveform selection approaches.

Identifying spectrum opportunities is a crucial element of efficient spectrum utilization for future wireless networks. Spectrum sensing offers a convenient means for revealing such opportunities. Studies showed that usage of the spectrum has a high correlation over multi-dimensions, including time and frequency. However, multi-dimensional spectrum sensing requires high-cost processes. Applying compressive sensing allows for subNyquist sampling. This reduces associated training, feedback, and computation overheads of a spectrum sensing method. However, the accuracy of the signal sparsity assumption and knowledge of the precise sparsity level are necessary for the applicability of compressive sensing. It is common practice to assume a level of known sparsity. On the other hand, in reality, this presumption is incorrect. This paper proposes a method for estimating the multidimensional sparsity for spectrum sensing. By extrapolating it from its counterpart with respect to a compact discrete Fourier basis, the proposed method calculates the sparsity level over a dictionary. A machine learning estimation method achieves this inference. Extensive simulations validate a high-quality sparsity estimation. To validate this observation, real-world measurements are used, where one of the biggest Turkish telecom operators has private uplink bands in the frequency range between 852-856 MHz.

This paper presents a geometrical 3-D channel model for stationary inter-high altitude platform (HAP) systems operating at millimeter wave (mmWave) frequency bands for the future 6G non-terrestrial networks (NTNs). The motivation of this study is to satisfy such a scenario where a high data rate between two HAPs is desired. In order to do this, the possible reasons for path loss, namely the free space and atmospheric path losses that are severely observed because of the short wavelength of the mmWave signals, are characterized according to 3GPP standards and ITU recommendations. Unlike most of the air-to-air unmanned aerial vehicle (UAV) channel modeling studies where a 2-D channel model is adopted, this study adopts a 3-D approach to characterize the wireless channel between two HAPs to fill the gap in the literature and reflect the actual characteristics of the air-to-air UAV networks. Moreover, this paper introduces the usage of the multiple input multiple output (MIMO) beam-forming technology in the UAV networks to compensate for the path loss effects in mmWave bands. Numerical results show the validation of the proposed 3-D channel model in point-to-point HAP networks at frequencies varying from 28 to 60 GHz.

This paper proposes a novel time-frequency warped waveform for short symbols, massive machine-type communication (mMTC), and internet of things (IoT) applications. The waveform is composed of asymmetric raised cosine (RC) pulses to increase the signal containment in time and frequency domains. The waveform has low power tails in the time domain, hence better performance in the presence of delay spread and time offsets. The time-axis warping unitary transform is applied to control the waveform occupancy in time-frequency space and to compensate for the usage of high roll-off factor pulses at the symbol edges. The paper explains a step-by-step analysis for determining the roll-off factors profile and the warping functions. Gains are presented over the conventional Zero-tail Discrete Fourier Transform-spread-Orthogonal Frequency Division Multiplexing (ZT-DFT-s-OFDM), and Cyclic prefix (CP) DFT-s-OFDM schemes in the simulations section.

Visible light communication (VLC) is a promising technology for next-generation indoor wireless broadband communication systems. Physical layer security (PLS) is one proposed method to ensure data security for VLC in public areas. However, most PLS studies in the literature neglect the reflections in the VLC channel and do not consider inter-symbol interference (ISI). This paper investigates the ISI effects on the secrecy rate in multiple-input single-output VLC systems where the reflections are not neglected for the cases of perfect and imperfect knowledge of the eavesdropper’s channel state information. We aim to compensate for the ISI effects by designing zero-forcing (ZF) and artificial noise (AN) beamformers. In addition, we formulate optimization problems to maximize the secrecy rate resulting in non-convex and NP-hard problems. Thus, we utilize the particle swarm optimization algorithm for solutions and also convert non-convex optimization problems into easily solvable linear problems. Furthermore, robust ZF and AN beamformers for the worst-case scenario are considered for the cases of ISI and no ISI. The results reveal that ISI severely degrades the secrecy rate; however, well-designed beamformers can reverse the ISI effects.

In this paper, we propose a composite multiple-mode orthogonal frequency division multiplexing with index modulation (C-MM-OFDM-IM) scheme to increase the spectral efficiency (SE) of OFDM-IM systems by extending the indexing to the energy and constellation domains. In C-MM-OFDM-IM, the information bits are mapped to not only the subcarrier activation patterns (SAPs) and modulation symbols, but also the energy allocation patterns (EAPs) and constellation activation patterns (CAPs). To cope with the practical situations, we propose a variant IM scheme named C-MM-OFDM-IM-II to build a new mapping rule between information bits and the increased CAPs, capable of further increasing the SE of C-MM-OFDM-IM. Upper-bounded bit error rate (BER) and lower-bounded achievable rate are both derived in closed-form to evaluate the performance of C-MM-OFDM-IM(-II). Moreover, we further propose two enhanced schemes, named generalized C-MM-OFDM-IM(-II) and C-MM-OFDM with in-phase/quadrature IM(-II), where the former jointly considers all SAPs, EAPs, CAPs and modulated symbols, while the latter expands the index implementation to the in-phase and quadrature constellation domains. Simulation results show that C-MM-OFDM-IM(-II) outperforms the conventional OFDM-IM related schemes, especially in the high signal-to-noise ratio (SNR) region, and verify the accuracy of the theoretical analysis for the upper-bounded BER and achievable rate.

In this paper, a novel frame design is proposed which realizes integrated sensing and communication (ISAC) while developing synergy among non-terrestrial (NTN) and terrestrial networks. Conventional time division duplexing (TDD) based systems suffer from high latency in sensing and communication performance which further aggravates with the increasing distance between transmitter and receiver as in the case of NTN. Therefore, to overcome the issue of latency, a spectrum efficient frame design is proposed that exploits the waiting period of a pulsed radar to perform interference free communication and sensing. The communication transmitter and radar transceiver embedded in high altitude platforms (HAPs) uses pulsed radar for sensing. Due to high altitudes, the target echo is reached at the HAPS after a long delay. This delay time is exploited to embed fixed and opportunistic communication in the proposed ISAC frame design. The numerical analysis explains spectrum efficiency of the proposed frame design compared to TDD mode of JRC systems, with reliable communication and accurate target detection.

In this paper, a novel method for joint sensing and communication (JSAC) is proposed by exploiting the scattering properties of a rough surface present in the environment in the terahertz (THz) frequency range. At higher frequencies, the transmitted signals are more likely to be obstructed by a blockage owing to their shorter wavelength. Therefore establishing an alternate connection between the communicating nodes is highly desired. In case when the direct line-of-sight (LOS) link is unavailable between transmitter (Tx) and receiver (Rx), the proposed framework provides a true non-line-of-sight (NLOS) connection via a rough surface. The transmitted signal interacts with the rough surface present in the environment. The scattering pattern of the reflected signal from the rough surface is exploited to realize a JSAC system. Specifically, the high-powered specular component reflected by an intermediate rough surface is used for communication whereas, a moderate-powered diffused reflected component is exploited for target sensing. Finally, simulation results are provided to analyze communication and sensing performance along specular and diffused components reflected from a rough surface.

Joint sensing and communication (JSAC) systems are becoming attractive technologies since they can map the radio environment while performing communication using the same frequency bands. This is achieved by radar signal processing of the received signal that is composed of a known waveform. However, varying the waveform used for JSAC will create a trade-off between throughput and computational complexity. In this paper, we propose a joint orthogonal time-frequency space (OTFS)-frequency modulated continuous wave (FMCW) waveform design to perform JSAC to achieve high data rates due to OTFS and low-complex simple radar receiver thanks to FMCW. This is done by exploiting the simultaneous locality property of the FMCW in both time-frequency and delay-Doppler domains to orthogonally superimpose OTFS and FMCW, and use them for communication and sensing, respectively. Then, we provide an analysis of the computational complexity of the proposed design. The conducted simulation results demonstrate that the proposed waveform design can achieve accurate low-complexity radar parameters estimation while preserving high data rates.

In multicarrier wideband millimeter-wave (mmWave) communications, as the size of antenna array increases, as in massive multiple-input multiple-output (MIMO), an additional propagation delay of the electromagnetic wave at each antenna element is introduced comparable to (or greater than) the symbol duration, resulting in producing a displacement in beam direction at each subcarrier frequency or as it calls beam squinting. With multi-beam transmission in massive MIMO systems, due to beam squinting effect, an additional inter-beam interference (IBI) can be introduced to the system which significantly decreases the overall system capacity. Therefore, in this paper, IBI under beam squint effect is modeled for different subcarrier frequencies and beam angles in a multi-beam mmWave massive MIMO system. In addition, the impact of this IBI model on the system capacity is evaluated. The analysis results show that beam squinting causes a significant increase in IBI level, even when transmitting with orthogonal beams. Moreover, the results provide the optimal number of beams for a given antenna array size to maximize the system’s capacity considering beam squinting phenomena.

High-quality radio frequency (RF) components are imperative for efficient wireless communication. However, these components can degrade over time and need to be identified so that either they can be replaced or their effects can be compensated. The identification of these components can be done through observation and analysis of constellation diagrams. However, in the presence of multiple distortions, it is very challenging to isolate and identify the RF components responsible for the degradation. This paper highlights the difficulties of distorted RF components’ identification and their importance. Furthermore, a deep multi-task learning algorithm is proposed to identify the distorted components in the challenging scenario. Extensive simulations show that the proposed algorithm can automatically detect multiple distorted RF components with high accuracy in different scenarios.

A traditional array (TA) multiple-input multiple-output (MIMO) architecture in mmWave with hybrid beamforming suffers from high power consumption and hardware overhead. Therefore, a lens antenna subarray (LAS)-MIMO architecture has been recently proposed as a promising technology for a power-efficient system and reducing hardware cost and complexity. Additionally, the LAS-MIMO can offer spectral efficiency (SE) performance close to TA-MIMO and higher than single-lens antenna array (SLA)-MIMO. In this paper, we propose a hybrid precoding algorithm for the LAS-MIMO in mmWave to efficiently control the LAS design. The precoding problem is formulated as a sparse reconstruction problem due to the sparse behavior of mmWave channel. The proposed algorithm is an iterative process developed jointly using artificial bee colony (ABC) optimization with orthogonal matching pursuit (OMP) algorithms. In each iteration, the algorithm first selects the switches for each lens randomly using ABC and then uses OMP to approximate optimal unconstrained precoders. This process continues until achieving maximum SE. The simulation results show that LAS has around a 30% increase in SE compared to SLA while providing a significant gain in energy efficiency (EE) for single radio-frequency (RF) chain and multi RF chain scenarios.

This article proposes a pre-equalization method to remove inter-numerology interference (INI) that occurs in multi-numerology OFDM frame structures of fifth-generation New Radio (5G-NR) and beyond, on the transmitter side. In the literature, guard bands, filters, and interference cancellation methods are used to reduce the INI. In this work, we mathematically model how the INI is generated and show how it can be removed completely for multi-numerology systems by deploying a pre-equalization matrix on the transmitter side. With this pre-equalization method, the need for guard bands and filters is eliminated and spectral efficiency is improved.

Next-generation wireless networks require massive connectivity and ubiquitous coverage, for which non-terrestrial networks (NTNs) are a promising enabler. However, NTNs, especially non-geostationary satellites bring about challenges such as increased handovers (HOs) due to the moving coverage area of the satellite on the ground. Accordingly, in this work, we compare the conventional measurement-based HO triggering mechanism with other alternatives such as distance, elevation angle, and timer-based methods in terms of the numbers of HOs, ping-pong HOs, and radio link failures. The system-level simulations, carried out in accordance with the 3GPP model, show that the measurement-based approach can outperform the other alternatives provided that appropriate values of hysteresis/offset margins and time-to-trigger parameters are used. Moreover, future directions regarding this work are also provided at the end.

We propose an efficient radio resource scheduling (RRS) approach based on the existing dynamic resource block structure (D-RBS). The proposed RRS is more responsive to variations in traffic demand. More specifically, small-sized resource blocks (RB)s are allocated to user equipments (UE)s to handle the changes in the traffic needs and link failures. The proposed approach enables low latency communication without the use of punctured mini-slot based scheduling methods. Thus, the performance of enhanced mobile broadband (eMBB) UEs or cells is not degraded while prioritizing ultra-reliable low latency communication (URLLC) UEs. The available RBs are distributed using traditional scheduling algorithms such as round robin (RR), proportional fair (PF), and best channel quality indicator (BCQI). Also, the proposed scheme allows the dynamic switching of RR and BCQI scheduling based on specific thresholds, such as signal-to-noise ratio (SNR) values. System-level simulations (SLS)s are performed to evaluate the performance of the proposed approach against the conventional static resource block structure (S-RBS) approach. The simulation results demonstrate that the developed approach provides robust data rate, system throughput, spectral efficiency (SE), and achievable rate per UE for various fifth generation (5G) services.

Channel emulators are usually used to evaluate preliminary performances of the newly developed wireless algorithms in the laboratory without resorting to the on-site measurements which are generally complex and costly. In this study, a simple but effective channel emulator that features a benchtop-sized (small-sized) reverberation chamber (RVC), radio frequency (RF) cable, and power controller is proposed for emulating a Rician propagation environment with a flexibly controllable k-factor. The developed emulator has the ability to precisely introduce the Rician propagation effect (with the desired k-factor) to the input RF signal. The performance of the proposed emulator was evaluated through measurement and its accuracy was validated by conducting a Kolmogorov–Smirnov (KS) goodness-of-fit (GoF) test. The emulator is suitable for both algorithm/prototype testing and educational purpose in wireless laboratories.

Massive multiple-input multiple-output (mMIMO) systems implementing wideband signaling have been found to suffer from beam squinting problem. In multicarrier systems, beam squint causes spreading of the beam to multiple undesired directions, thereby degrading system capacity. This paper proposes user scheduling and precoding techniques that controls and exploit the beam squinting phenomenon to serve multiple users and improve the overall system capacity. The proposed techniques are based on the lens antenna subarray (LAS) mMIMO system. The proposed system design is explained and numerically evaluated in terms of beam gain and capacity with different number of users and RF chains. The simulation results exhibit significant performance enhancement in terms of beam gain and capacity, corroborating the idea of exploiting the beam squinting phenomenon to serve multiple spatially separated groups of users.

Spreading codes are the core of the spread spectrum transmission. In this paper, a novel channel-dependent code allocation procedure for enhancing security in multi-carrier code division multiple access (MC-CDMA) system is proposed and investigated over frequency-selective fading. The objective of the proposed technique is to assign the codes to every subcarrier of active/legitimate receivers (Rxs) based on their channel frequency response (CFR). By that, we ensure security for legitimate Rxs against eavesdropping while preserving mutual confidentiality between the legitimate Rxs themselves. To do so, two assigning modes; fixed assigning mode (FAM) and adaptive assigning mode (AAM), are exploited. The effect of the channel estimation error and the number of legitimate Rxs on the bit error rate (BER) performance is studied. The presented simulations show that AAM provides better security with a complexity trade-off compared to FAM. While the latter is more robust against the imperfection of channel estimation.

Wireless technologies have always been the cornerstone of industrial progress. However, as industrial technologies have improved and advanced services have emerged, the demands of industry have meant that wireless technologies have had to adapt. When throughput was the only major concern in previous generations, orthogonal frequency division multiplexing (OFDM) provided an excellent solution for frequency-selective channels. However, the current era of technologies also requires extensive mobility support, resulting in doubly selective channels. As a robust waveform in doubly dispersive channels, orthogonal time-frequency space (OTFS) has been proposed in the literature recently. However, like other multicarrier schemes, OTFS suffers from high a peak-to-average power ratio (PAPR). High PAPR can lead to inter-modulation distortion due to the non-linearity, resulting in severe degradation of detection performance. Therefore, we present a novel PAPR reduction method that exploits the unique OTFS frame structure. Simulation results show that this method can reduce PAPR by up to 2.4 dB, with minimal loss of detection performance compared to conventional OTFS transmission.

Orthogonal frequency division multiplexing (OFDM) is such a vital waveform scheme that is utilized in fifth-generation (5G) communication systems as well as the previous one. Since the usage scenarios of 5G are quite wide, the security of those systems is currently an open and critical issue. In this paper, a promising paradigm is proposed for enhancing physical layer (PHY) security in OFDM systems. Two independent secret keys are extracted by legitimate users quantizing the channel measurements. Those key sequences are exchanged via a novel artificial noise (AN) injection method which does not result in a key mismatch. Bit error rate (BER) versus signal-to-noise ratio (SNR) performance of the adversary is still low even if the malicious node has better channel than the legitimate user. After agreement upon the same key, both legitimate parties directly employ key sequence and inter-carrier interference matrix caused by the local oscillators to produce a secrecy matrix. This matrix enables secure communication by inserting it into the transmission design.

Wireless networks beyond 5G are expected to support a wide range of applications and use cases, and single-carrier (SC) based wireless technologies have been considered in the literature as a suitable solution for high-frequency bands and latency-critical applications. However, SC systems experience severe performance degradation under multipath wireless channels. In a realistic scenario, wireless channels can cause fractional delays that introduce devastating self-interference into the system. Therefore, in this paper, we present an extended channel model that considers pulse shaping and fractional delay. Moreover, we use the proposed model to analyze the performance of the SC transmission scheme with a root-raised-cosine (RRC) pulse shape over a fractional delay channel. In this context, we propose a flexible system design with the aid of the exhaustive search method to control the effect of self-interference on SC in the presence of a fractional delay wireless channel. Lastly, we provide bit error rate results (BER) to validate the accuracy of the proposed compensator for SC systems in practical scenarios.

Radio-frequency (RF) front-end forms a critical part of any radio system, defining its cost as well as communication performance. However, these components frequently exhibit non-ideal behavior, referred to as impairments, due to the imperfections in the manufacturing/design process. Most of the designers rely on simplified closed-form models to estimate these impairments. On the other hand, these models do not holistically or accurately capture the effects of real-world RF front-end components. Recently, machine learning-based algorithms have been proposed to estimate these impairments. However, these algorithms are not capable of estimating multiple RF impairments jointly, which leads to limited estimation accuracy. In this paper, the joint estimation of multiple RF impairments by exploiting the relationship between them is proposed. To do this, a deep multi-task learning-based algorithm is designed. Extensive simulation results reveal that the performance of the proposed joint RF impairments estimation algorithm is superior to the conventional individual estimations in terms of mean-square error. Moreover, the proposed algorithm removes the need of training multiple models for estimating the different impairments.

In cognitive radio systems, predicting spectrum occupancies is a convenient alternative way to continuous spectrum sensing. It can provide information on spectrum usage and so empty spectrum bands can be used by secondary users. The usage of the spectrum bands is highly correlated over both time and frequency. Recently, machine learning algorithms are used to predict spectrum occupancy by exploiting such correlations. However, this approach primarily assumes a supervised learning setting. Despite its outstanding performance, this setting requires the availability of sufficiently large datasets (of labeled data) and is not adaptive to environment changes. In this paper, different from the existing literature, a deep reinforcement learning (RL) algorithm is used to alleviate those shortcomings. In this algorithm, we define the reward functions of the deep RL setting and its state and action spaces such that it is applicable to work dynamically, in an online fashion, in real world settings. Extensive experiments validate the capability of the proposed algorithm in predicting spectrum occupancies as examined over real world spectrum measurements. These are carried out in the 832-862 megahertz frequency bands, which are used by the leading Turkish telecom providers as private uplink bands. This is a significant step towards realizing a standalone spectrum occupancy prediction operation without any control from the operator and minimizing memory requirements while alleviating the need for the labeled dataset.

With revolutionary new services and applications, integrated sensing and communication has been essential for recent and future wireless communication systems. For the communication systems, the cyclic prefix - orthogonal frequency division multiplexing (CP-OFDM) is a widely used waveform in various wireless standards due to its high spectral efficiency and resilience to static multi-path channel conditions. On the other hand, the frequency modulated continuous-wave (FMCW) is a popular waveform in radar-sensing applications, especially for autonomous vehicles. Although communication signals over the air are utilized for sensing applications, such as passive radars, however, these systems have limited sensing capabilities. Also, several coexistence schemes are introduced for these different systems, communication and radar-sensing that separately allocate time, frequency and space resources. Unlike these approaches, a novel waveform design by overlapping on the same time and frequency resources is proposed to provide orthogonal coexistence for joint radar and communication (JRC) systems. For the proposed design, the channel estimation and bit-error rate (BER) performances are compared with the conventional CP-OFDM systems, and it is demonstrated that the same performance can be obtained in the proposed coexistence. Therefore, this waveform design due to the overlapping achieves a better spectral efficiency compared to separate resource sharing approaches.

Obtaining accurate channel state estimates at reasonable training overheads remains a big challenge for the applicability of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM). Recently, the exploitation of channel sparsity has led to sub-Nyquist channel sampling thereby reducing the channel training overhead. Still, there is a growing belief in channel sparsity appearance in many dimensions; time, frequency, angle, and space. Accordingly, this paper proposes an algorithm for channel estimation where sparsity in multidimensions is simultaneously exploited. Also, the applicability of sparse coding relies on the validity of a signal sparsity assumption and knowing the exact sparsity level. However, this assumption is not valid in practice, especially when applying learned dictionaries as sparsifying transforms. The problem is more strongly pronounced with multidimensional sparsity. In this paper, we also propose an algorithm for estimating the composite sparsity lying in multiple domains defined by learned dictionaries. Simulations validate a substantial channel estimation quality attained by the proposed algorithm as compared to the existing algorithms. The simulations also validate a high quality of sparsity estimation leading to performances close to the impractical case of assuming known sparsity.

This work aims to address the timing synchronization issue which limits the applicability of coordinated multipoint schemes, specifically joint transmission, in practical wireless networks. Following a brief description of the issue itself, and its repercussions on the network performance, the various conditions/solutions that mitigate this problem are recapped. Following this, we provide the background of the proposed approach to be used for mitigating the timing synchronization issues, namely, common cyclic prefix (CP) technique. Then, a clustering algorithm is proposed aimed at balancing the cell load with timing synchronization as a constraint. In load balancing stage, the first priority is given to users with higher received power and lower number of base stations in the candidate set. The results obtained via simulations indicate that heterogeneous network (HetNet) deployments suffer from timing synchronization when smaller CP duration is used, and this performance degradation can be resolved quite effectively using the common CP configuration.

Cooperative communication has been widely used to provide spatial diversity benefits for low-end user equipments, especially in ad hoc and wireless sensor networks. However, the lack of strong authentication mechanisms in these networks leaves them prone to eavesdropping relays. In this paper, we propose a secure orthogonal frequency division multiplexing (OFDM) transmission scheme, where the destination node transmits a jamming signal over the cyclic prefix (CP) duration of the received signal. Simulation results verify that as long as at least a part of the jamming signal falls to the actual data portion of the eavesdropping relay, it spreads through all the data symbols due to the fast Fourier transformation (FFT) operation, resulting in degraded interception at the eavesdropper.

Design of simple transceiver architectures is inevitable in order to provide low computational complexity, low power consumption and affordable cost in beyond 5G (B5G) wireless systems, but it results in hardware impairments that significantly degrade the performance reliability of transmission. In this paper, among these hardware impairments, we discuss in-phase and quadrature (IQ) imbalance in orthogonal time frequency space (OTFS), which is a recent waveform considered as a potential candidate for B5G systems to relax the vulnerability against time-variant wireless channels. To mitigate the effect of IQ imbalance for OTFS, we propose an energy and spectral efficient IQ imbalance compensation scheme with the aid of index modulation (IM), which provides an attractive flexibility in the system design. In contrast to conventional solutions used in classical wireless technologies, such as iterative and pilot-based techniques, the proposed scheme avoids additional energy consumption and significant spectral efficient loss during the estimation and compensation of the IQ imbalance effect. The obtained bit error rate (BER) results validate the accuracy of the proposed compensator for different OTFS system configurations considering perfect/imperfect channel state information in practical scenarios.

In this work, novel physical layer security (PLS) schemes are proposed for orthogonal frequency-division multiplexing (OFDM) to secure both data and pilots in multiple-input multiple-output (MIMO) systems. The majority of previous studies focus on only securing the data without considering the security of the pilots used for channel estimation. However, the leakage of channel state information (CSI) from a legitimate node to an eavesdropper allows the latter to acquire knowledge about the channel of the legitimate nodes. To this end, we propose adaptive and flexible PLS algorithms which can 1) secure data, 2) secure pilots, and 3) jointly secure both data and pilots. Particularly, minimum-phase all-pass channel decomposition is exploited, where the proposed algorithms use the all-pass component to provide security without harming the performance of the legitimate user. In the analysis for data security, we evaluate the secrecy under correlated and uncorrelated eavesdropping channels via closed-form bit error rate (BER) formulas. For pilot security, we analyze the estimated channel’s normalized mean squared error (NMSE) performance. The simulation results and theoretical analysis demonstrate that the proposed algorithms can effectively enhance the communication secrecy of the overall system.

The intelligent reflecting surface (IRS) is emphasized as a controlled scattering cluster. To this end, scatterers and traveling paths of multipath components are classified to build a new channel model. Unlike the conventional modeling, where the channels between system units are modeled independently, the new model considers the channel as a whole and decomposes it based on the traveling paths. The model shows clearly how IRS, in the beam-space context, converts the channel from a problem into a design element. After investigating IRS as a scattering cluster, based on a proposed segmentation scheme, the beamforming problem is considered with a focus on first-order reflections. Passive beamforming at IRS is shown to have two tiers; at the scatterer and antenna levels. A segment-activation scheme is proposed to maximize the received signal power, where the number of transmitting antenna elements to be used is given as a function of IRS positioning and beamforming at the receiver. The results show that while using more transmitting antenna elements to get narrower beams is possible, using fewer elements can give better performance, especially for larger IRS at close distances. The developed model also proves useful in addressing emerging issues in massive MIMO communication, namely, stationarity and spherical wavefronts.

Reconfigurable intelligent surface (RIS) has recently drawn significant attention in wireless communication technologies. However, identifying, modeling, and estimating the RIS channel in multiple-input multiple-output (MIMO) systems are considered challenging in recent studies. In this paper, a disassembled channel estimation framework for the RIS-MIMO system is proposed based on the eigenvalue decomposition (EVD) concept to separate the cascaded channel links and estimate each link separately. This estimation is based on modeling the RIS-MIMO channel as a keyhole MIMO system model. Numerical results show that the proposed estimation method has a low estimation time overhead while providing less estimation error.

Cognitive radio-based non-orthogonal multiple access (CR-NOMA) is considered to be one of the promising multiple accessing technique candidates for 5G and beyond networks. These networks are facing a lot of challenges to achieve high spectral efficiency, low latency, and massive connectivity. Interference management and efficient power allocation are highly interesting among the researchers to investigate in CR-NOMA networks. This paper studies the power allocation of underlay CR-NOMA network using game theory approach by conducting the pricing technique to achieve efficient power allocation and minimum interference. In particular, the game is formulated, and its solution is achieved by exploring the suboptimal solution represented by the Pareto-efficiency of the Nash equilibrium point. The simulation results show the superiority of the proposed scheme in achieving higher spectral efficiency, fairness index, and sum utilities of secondary users compared to existing schemes.

Cognitive radio-based non-orthogonal multiple access (CR-NOMA) is considered to be one of the promising multiple accessing technique candidates for 5G and beyond networks. These networks are facing a lot of challenges to achieve high spectral efficiency, low latency, and massive connectivity. Interference management and efficient power allocation are highly interesting among the researchers to investigate in CR-NOMA networks. This paper studies the power allocation of underlay CR-NOMA networks using multi-input multi-outputs (MIMO) techniques to increase the achievements of getting higher spectral efficiency as well as spatial diversity among multiple users to be served. In particular, power allocation based on uniform and adaptive power allocation, and near-optimal for high and low signal to noise ratio are derived. Finally, the simulation results show the superiority of the proposed scheme in achieving higher spectral efficiency, fairness, and average capacity of secondary users compared to the conventional scheme.

For existing IEEE 802.11ax and futurist Wi-Fi standards, one of the major challenges is fair coexistence with LTE-Unlicensed/5G-New Radio (LTE-U/5G-NR) and other internet of things (IoT) paradigms. An algorithm is developed for multiple Wi-Fi small cell networks, coexisting with the LTE-U network over the unlicensed band for smart spectrum sharing. An optimal detector is designed based on second-order statistics (SOS) of OFDM signals and using singular value decomposition (SVD) method. Furthermore, theoretical expressions are derived for the detection and the false alarm probabilities. For spectrum access and sharing, flexible carrier sensing adaptive transmission (CSAT) framework and algorithm are designed. Lastly, the simulation results show the distinction of the proposed approach over the conventional detectors.

In sparse coding-based channel estimation, atom selection is based on jointly minimizing the sparsity and the error of the representation of the noisy measurement. However, this selection is not necessarily optimal in terms of minimizing the channel estimation error. This calls for better ways of atom selection. Accordingly, we propose an algorithm for improved atom selection in sparse coding for frequency division duplex (FDD) massive multiple-input-multiple-output (MIMO) downlink channel estimation. The proposed algorithm performs iterative atom selection based on two residuals. First is the received signal residual used to guide on a small selection pool of candidate atoms. Second is the residual of an initial channel estimate which is used to pick the best atom within the selection pool. Simulation results show the advantage of the proposed algorithm over standard sparse coding-based channel estimation. Moreover, the proposed algorithm eliminates the need for cell-specific trained dictionaries without sacrificing the performance. Furthermore, the proposed sparse coding can be applied in the process of dictionary learning to train for improved dictionaries achieving further performance enhancement.

The novel orthogonal frequency division multiplexing with subcarrier number modulation (OFDM-SNM) transmission scheme offers high spectral and energy efficiency compared to the conventional OFDM; this is due to the extra information bits loaded over the active subcarriers. However, the OFDM-SNM scheme has a high and comparable peak-to-average power ratio (PAPR) performance to the classical OFDM. Besides the high PAPR in OFDM-SNM, out-of-band emission (OOBE) often happens between the adjacent blocks. To address the above-mentioned problems, we introduce an enhanced version of the classical OFDM-SNM, where the active subcarriers' positions are cleverly placed to reduce the PAPR and OOBE values. Power spectral density (PSD) and complementary cumulative distribution function (CCDF) of PAPR are used as performance metrics to assess the PAPR and OOBE performances of the proposed scheme. The obtained simulation results exhibit improved PAPR and OOBE performances of the proposed scheme along with almost similar bit error rate (BER) performance as compared to the classical OFDM.

Joint radar and communication (JRC) is a fast emerging research field to cope up with the ever-growing applications dependent on both sensing and communication. However, frequent issues are faced for JRC systems including interference mitigation, transmission design and signal analysis. This paper focuses on blind signal separation (BSS) of spectral coexistence JRC signals for blindly extracting sensing information from the communication signal for spectrum awareness, also this BSS is used for interference mitigation by using a modified fast independent component analysis (Fast-ICA) algorithm. Furthermore, a new non-linear function is introduced for Fast-ICA which tends to have better performance of separation with low time computational complexity. The numerical analysis shows the effectiveness and practicality of the system by using modified Fast-ICA algorithm in separating JRC signals successfully compared to other separation methods.

In this paper, a novel frame design for integrated communication and sensing is proposed. The proposed frame structure consists of Barker radar sequence and binary phase shift keying (BPSK) modulated data bits. The temporal position of the radar sequence is determined by a subset of incoming information bits. Therefore, in addition to target sensing; the radar sequence also carries data bits in the form of position modulation. Moreover, during the reception process channel estimation is also performed using the radar sequence thereby leveraging the function of pilots. The simulation results verify that the dynamic location of radar sequence does not effect the sensing performance; however, sensing is sensitive to the length of radar sequence. Moreover, the proposed scheme results in reduced bit error rate (BER) when compared to radar-communication frame without any position modulation.

The cognitive users (CUs) in the cooperative communication may serve as relay nodes for conveying the signal received from the primary users (PUs) to their destinations, provided that both the PUs and the CUs minimum rate requirements are satisfied. The PUs are motivated to cooperate by the incentive of achieving a higher PU rate with reduced power requirement, while concurrently allowing an access to CUs to share their spectral band. The existing cooperative schemes do not improve the simultaneous transmission rate of both PUs and CUs. In this paper, an incremental pragmatic distribution algorithm (IPDA) is proposed, which provides efficient spectral access with an improved simultaneous transmission performance of both CUs and PUs. The obtained results by employing the proposed algorithm show that our scheme offers relatively better performance of PUs and CUs with low overhead than the conventional distributed cooperative communication schemes.

Orthogonal time frequency space (OTFS) technique is a recent two-dimensional (2-D) modulation aiming to exploit both time and frequency selectivity of doubly dispersive wireless channel, which significantly affects the reliability of conventional wireless communication systems. In OTFS transmission, delay-Doppler domain is utilized for conveying the data symbols. Besides channel characteristics, the performance of wireless communications systems is severely limited due to the impairments at the RF front-end. One of these impairments is the in-phase and quadrature (IQ) imbalance that occurs due to inevitable imperfections existing between in-phase and quadrature branches at either transmitter (Tx) or receiver (Rx) architecture. The aim of this paper is to reveal and investigate the physical effect of IQ impairment in delay-Doppler domain, which is unknown in the literature. Hence, we provide theoretical models to explicitly understand the impact of IQ imbalance at different stages of OTFS-based communication systems including Tx, Rx, and jointly Tx-Rx. Importantly, we show that although the performance of OTFS transmission depends on both delay and Doppler axes, IQ imbalance leads to an interference originating only from the mirror Doppler axes, which we name mirror Doppler interference (MDI), along with power degradation. Moreover, we assess the performance of IQ imbalanced OTFS under various communication scenarios considering ideal and practical pulse shapes with maximum likelihood (ML) and minimum mean square error (MMSE) detectors, respectively.

Cognitive radio non-orthogonal multiple access (CRNOMA) networks promise improved spectrum utilization and capacity in 5G networks. In this work, we aim to investigate efficient power allocation for the secondary users (SUs) in underlay CR-NOMA networks using a game-theoretic approach. We present a novel power allocation to CR-NOMA network from a game-theoretic perspective. First, we specify the utility function of the primary users (PUs) and SUs, and formulate the game as a non-cooperative game. Then, the existence and uniqueness of the Nash equilibrium (NE) are investigated. Finally, the sum utilities of SUs is maximized by optimal power allocation at the NE point. Simulation results provided that the proposed scheme outperforms the conventional method, providing up to 37.5% increase in sum utilities of the SUs.

Receive Spatial Modulation (RSM) uses the index of the receive antenna to convey additional information bits, which reduces the receiver complexity and improves spectral efficiency. Additionally, it provides inherent physical layer security using the Zero-forcing (ZF) precoding technique. However, the channel becomes vulnerable to eavesdropper (Eve) if the channel impulse response is assumed to be time-invariant or stationary through coherent block intervals. In this paper, a physical layer secure scheme is proposed based on phase index RSM to combat eavesdroppers that use k-nearest neighbors (KNN) supervised pattern recognition. The average bit error rate (BER) performance shows the ability of the proposed scheme to provide a suitable level of security while degrading the average BER performance of Eve.

The reconfigurable intelligent surface (RIS) technology has attracted interest due to its promising coverage and spectral efficiency features. However, some challenges need to be addressed to realize this technology in practice. One of the main challenges is the configuration of reflecting coefficients without the need for beam training overhead or massive channel estimation. Earlier works used estimated channel information with deep learning algorithms to design RIS reflection matrices. Although these works can reduce the beam training overhead, still they overlook existing correlations in the previously sampled channels. In this paper, different from existing works, we propose to exploit the correlation in the previously sampled channels to estimate RIS interaction more reliably. We use a deep multilayer perceptron for this purpose. Simulation results reveal performance improvements achieved by the proposed algorithm.

5G New Radio (NR) introduces new flexibility that different numerologies can be selected to meet the requirements of a wide variety of services. For this new structure, blind numerology identification can increase system efficiency. Therefore, we propose a blind identification method for mixed numerologies. An autocorrelation method is applied in the time domain by correlating the cyclic prefix (CP) signal of the candidate numerology in the received composite signal for numerology type identification. Then, the location of each numerology in the frequency domain is identified by the variance difference in the power spectral density (PSD) of the subbands, on which different numerologies are occupied. The simulation results are obtained under additive white Gaussian noise (AWGN) and frequency-selective channels. The obtained results show that the proposed method has a robust identification accuracy and a satisfactory BER performance as compared to the non-blind identification approach in the conventional mixed-numerology system.

In this paper, a novel, yet efficient, multi-user scheduling scheme based on mode selection and power allocation is presented for 5G and beyond networks. The proposed scheme schedules the users in co-existence (CE) and non coexistence (NCE) modes to maximize the connectivity under signal separability and reliability constraints. In addition, two multi-user scheduling mechanisms; check requirements before scheduling (CRBS) and check requirements after scheduling (CRAS), are proposed for practical scenarios to study the impact of quality of service (QoS) on multi-user scheduling in terms of users' reliability requirements. Analytical results show that CRBS outperforms CRAS and orthogonal multiple access (OMA) schemes in terms of connectivity and system throughput with a complexity trade-off.

Abstract In 5G and beyond communication systems, distinct numerologies can coexist to serve diverse requirements for users and applications. However, the inter‐numerology interference (INI) is a main challenge that significantly impacts the system performance. Therefore, the performance under INI has become an essential evaluation metric for the suitability of the different transmission schemes in the future communication systems. This paper analyzes the impact of INI on the performance of orthogonal frequency division multiplexing with index modulation (OFDM‐IM) systems. Specifically, an analytical expression of the INI level in OFDM‐IM systems is presented as a function of the subcarrier activation ratio (SAR) and subcarrier activation probability (SAP). Furthermore, aiming at reducing the INI level, an adaptive subcarrier mapping scheme (SMS) is proposed based on the conventional combinatorial mapping scheme. Moreover, analysis and evaluation of SAR and SAP are performed regarding the requirements of 5G and beyond services. It is proved that the INI level in OFDM‐IM systems is highly dependent not only on the number of active subcarriers but also on their position in an OFDM block.

Index modulation (IM) provides a novel way for the transmission of additional data bits via the indices of the available transmit entities compared with classical communication schemes. This study examines the flexible utilization of existing IM techniques in a comprehensive manner to satisfy the challenging and diverse requirements of 5G and beyond services. After spatial modulation (SM), which transmits information bits through antenna indices, application of IM to orthogonal frequency-division multiplexing (OFDM) subcarriers has opened the door for the extension of IM into different dimensions, such as radio frequency (RF) mirrors, time slots, codes, and dispersion matrices. Recent studies have introduced the concept of multidimensional IM by various combinations of 1-D IM techniques to provide higher spectral efficiency (SE) and better bit error rate (BER) performance at the expense of higher transmitter (Tx) and receiver (Rx) complexity. Despite the ongoing research on the design of new IM techniques and their implementation challenges, proper use of the available IM techniques to address different requirements of 5G and beyond networks is an open research area in the literature. For this reason, we first provide the dimensional-based categorization of available IM domains and review the existing IM types regarding this categorization. Then, we develop a framework that investigates the efficient utilization of these techniques and establishes a link between the IM schemes and 5G services, namely, enhanced mobile broadband (eMBB), massive machine-type communications (mMTCs), and ultrareliable low-latency communication (URLLC). In addition, this work defines key performance indicators (KPIs) to quantify the advantages and disadvantages of IM techniques in time, frequency, space, and code dimensions. Finally, future recommendations are given regarding the design of flexible IM-based communication systems for 5G and beyond wireless networks.

Orthogonal frequency division multiplexing with subcarrier number modulation (OFDM-SNM) has been recently proposed to improve the spectral efficiency (SE) of the traditional OFDM system. In this paper, we propose a joint-mapping OFDM-SNM (JM-OFDM-SNM) scheme to transmit the signal vector with a constant length of information bits by jointly considering the subcarrier activation patterns and constellation symbols. A low-complexity detection scheme based on log-likelihood ratio criterion is proposed to relieve the high computational complexity of the maximum-likelihood detection at the cost of a negligible performance loss. Upper-bounded bit error rate (BER) and lower-bounded achievable rate are both derived in closed-form to evaluate the performance of JM-OFDM-SNM. To suit different application scenarios, we further propose two enhanced schemes, named adaptive JM-OFDM-SNM (AJM-OFDM-SNM) and JM-OFDM with in-phase/quadrature SNM (JM-OFDM-IQ-SNM), where the former adjusts the constellation orders for different numbers of active subcarriers, and the latter extends the indexing to in-phase and quadrature domains. Simulation results corroborate the tightness of the derived BER expression in the high signal-to-noise ratio region and show that (A)JM-OFDM-SNM improves the performance of OFDM-SNM, while both AJM-OFDM-SNM and JM-OFDM-IQ-SNM schemes perform better than JM-OFDM-SNM at the same SE.

Most physical-layer authentication techniques use channel information to prevent spoofing attacks. In such techniques, one must estimate the channel information for each authentication procedure. However, when the number of pilots decreases, authentication accuracy also decreases due to low channel estimation quality. This paper proposes a novel signal relation-based authentication method that relies on the detection of received signal symbols and does not require the estimation of channel information in the testing stage. It is noteworthy that the authentication performance of the proposed scheme remains in a good level. We develop two different solutions for the detection of received signal symbols, namely, minimum mean-square error and long short-term memory. Extensive simulation results show the main insights of the proposed signal relation-based authentication method compared to conventional channel-based authentication method.

Ensuring secure communication for internet of things (IoT) has drawn much attention because of the limitation in the use of conventional cryptographic techniques owing to the unique features of IoT devices such as low complexity, lightweight computing, and power constraints. Physical layer security (PLS) has the potential to provide security solutions that are suitable for such applications. In this article, an efficient PLS approach is proposed for providing secure communication against external and internal eavesdroppers in a downlink multi-carrier IoT communication system. The system consists of a transmitter with a single active antenna (and a single radio frequency chain) that is trying to communicate with two single-antenna IoT devices in the presence of a passive eavesdropper. In the proposed algorithm, frequency selective channel based pre-coder matrices and dual-transmission approach are jointly employed to provide simple and secure communication without complex computational processing at the IoT devices. Simulation results showed that the proposed algorithm can provide security against internal and external eavesdroppers and is suitable for IoT devices.

A new modulation scheme called orthogonal frequency division multiplexing with subcarrier gap modulation (OFDM-SGM) is proposed. The proposed scheme embeds extra information bits by exploiting the gap between the active subcarriers in each subblock. The proposed scheme differs from the OFDM-index modulation (OFDM-IM), in which information bits are transmitted using the index of active subcarriers. This OFDM-SGM technique provides superior spectral and energy efficiencies compared to the OFDM-IM, particularly when using binary phase-shift keying (BPSK)-like low constellation schemes, that suit the Internet of Things (IoT) applications that have low complexity. The theoretical error performance of the proposed scheme is presented, and the consistency between the theoretically derived error performance and the simulated one is also provided.

Cognitive radio (CR)-based internet of things systems can be considered as an efficient solution for futuristic smart technologies. However, CRs are naturally vulnerable to two major security threats; primary user emulation (PUE) and jamming attacks. Machine learning has been recently applied to the detection of these attacks. Still, the need for feature extraction required by machine learning techniques restrains the full exploitation of raw data. To alleviate this need, this paper proposes one-dimensional deep learning as a framework for identifying such attacks. Simulations show the ability of the proposed algorithm to detect these attacks with high performance.

The identification of spectrum opportunities is a pivotal requirement for efficient spectrum utilization in cognitive radio systems. Spectrum prediction offers a convenient means for revealing such opportunities based on the previously obtained occupancies. As spectrum occupancy states are correlated over time, spectrum prediction is often cast as a predictable time-series process using classical or deep learning-based models. However, this variety of methods exploits time-domain correlation and overlooks the existing correlation over frequency. In this paper, differently from previous works, we investigate a more realistic scenario by exploiting correlation over time and frequency through a 2D-long short-term memory (LSTM) model. Extensive experimental results show a performance improvement over conventional spectrum prediction methods in terms of accuracy and computational complexity. These observations are validated over the real-world spectrum measurements, assuming a frequency range between 832-862 MHz where most of the telecom operators in Turkey have private uplink bands.

In this study, a novel transmission scheme is proposed to serve radar-sensing and communication objectives at the same time and allocated bandwidth. The proposed transmitted frame non-orthogonally superimposes two different waveforms, which are frequency modulated continuous-wave (FMCW) for radar-sensing and orthogonal frequency division multiplexing (OFDM) for communication. Also, the receiver scheme that performs channel estimation via radar-sensing functionality without degrading data rate of communication operation is introduced. As numerically evaluated, the proposed system achieves good sensing accuracy even if the signal-to-noise ratio (SNR) is low, and communication performance is only 0.6 dB less at the target bit-error rate (BER) of 1% compared to the assumption of perfect channel state information (CSI) without any pilot overhead over OFDM subcarriers.

In this paper, a hybrid power domain non-orthogonal multiple accessing (NOMA) scheme by the superposition of orthogonal frequency division multiple accessing (OFDM) and index modulated OFDM (OFDM-IM) technologies is presented and named IM-NOMA. It is shown via both computer-based simulations and mathematical analysis that IM-NOMA outperforms the classical OFDM-NOMA in terms of bit error rate (BER) under a total power constraint and achievable sum rate. The system performance of IM-NOMA not only depends on the power difference between the overlapping users but also on features of the OFDM-IM signal. Hence, this scheme is robust against possible catastrophic error performance in case similar power is assigned to the users.

Recent research considers the application of a lens antenna array in order to provide efficient beam selection in beamspace massive MIMO. Achieving the advantages of this beam selection paradigm requires efficient channel estimation in the beamspace. Along this line, beamspace sparsity is an efficient regularizer to this problem. In this paper, we propose using a dictionary trained over a set of example beam selection matrices, as a beam selection tool. In this context, a learned dictionary can more effectively guarantee the sparsity of the representation at the specified sparsity level, owing to the dictionary learning process. This means that it gives a better sparse representation, and, consequently, a better channel estimation quality. Simulations validate that using a trained dictionary improves the quality of channel estimation, as tested over two channel models with different operating scenarios.

Next generation of wireless communication systems is expected to support a wide set of applications and use cases. Among these, applications with ultra-reliable and low-latency communications (URLLC) are at utmost importance due to stringent requirements. In this work, single carrier (SC) transmission is considered as a promising solution to meet demands of systems with URLLC. Firstly, SC system parameters affecting reliability and latency are comprehensively explained. Additionally, these parameters are optimized in time and frequency domain to achieve URLLC. Later, adaptive roll-off factor usage within a SC block is proposed to provide more efficient resource utilization. Trade-offs between reliability, latency and system efficiency are shown via computer based simulations. SC transmission inherently offers flexible structure to optimize the trade-offs through proper parameter selection.

Massive MIMO enabled ultra-dense heterogeneous networks (UDHNs) have been considered as the indispensable and emerging approach to meet the demand on growing data traffic for next generation networks. Although deployment of large number of antennas causes high circuit power consumption in massive MIMO UDHNs, there is always a tradeoff between energy efficiency (EE) and spectral efficiency (SE). Therefore, an energy efficient and spectral efficient user-cell association will become crucial and challenging in massive MIMO UDHNs. In this paper, we address a user-cell association problem for EE and SE tradeoff. To this end, we formulate a convex multi-objective optimization problem (MOP) and convert it into a single-objective optimization problem (SOP) where a priority is assigned for EE and SE with a weighting factor which means the problem can be adjusted whether priority is on EE or SE. The problem aims to maximize the weighted sum of the EE and SE. As a solution, Lagrange duality analysis is performed and a distributed game theoretical user-cell association (GTUCA) algorithm considering the fairness among users is developed. The results confirm that the proposed algorithm outperforms the baseline algorithm, namely maximum rate-based cell selection in terms of EE and SE, when the weighting factor is set properly.

Recent works have tried to incorporate unmanned aerial vehicle (UAV) base stations in conventional networks, however, the inter-cell interference mitigation techniques for such networks have not been studied comprehensively. In this paper, we consider a new heterogeneous cellular network, where terrestrial base stations (TBSs) and low altitude platforms (LAPs) collaborate to construct a hybrid network. We believe that it can serve as the stepping stone to a full-fledged coordinated multi-point implementation for 5G and beyond networks. The proposed network is simple, open to improvement and also makes use of available TBS. It promises to increase minimum signal-to-interference ratio (SIR) value of users and also overall throughput by using fractional frequency reuse. The hovering LAP is used for edge users that have lower SIR than TBSs threshold. Furthermore, we simulated a few scenarios, analyzed the effect of radius and UAV altitude, found optimum values for both.

Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper proposes an algorithm for sub-Nyquist wide-band spectrum sensing addressing this shortcoming. The proposed algorithm divides the spectrum into narrow, contagious frequency subbands and learns a subband dictionary for each subband. A subband dictionary is well-suited for the representation of signals in its corresponding subband. A compressed version of the received signal is sparsely coded over each subband dictionary. We show that the convergence patterns over a specific dictionary can be used for identifying the occupancy of its underlying subband. Therefore, the convergence patterns obtained by the gradient operator are used as distinctive classifying features. Then, a machine learning-based classifier is trained over these features and used to make the decision about spectrum occupancy. As the interest is only to characterize sparse coding convergence patterns, we alleviate the need for a specific or an estimated sparsity level. Besides, using subband dictionaries at different frequencies omits the need for a frequency-splitting filterbank. The proposed algorithm achieves significant performance improvements in terms of the probability-of-detection and false-alarm-rate measures. This result is validated through simulations with various operating scenarios.

Ultra-reliable low latency communication (URLLC) is undoubtedly the toughest service class in 5G-NR from the network service provider's perspective. Different methodologies have been utilized to meet the reliability and latency requirements of URLLC including proposition of various diversity techniques. This paper envisages a hybrid network using terrestrial and flying base stations to provide ubiquitous and reliable service to URLLC users. We propose utilizing the macro-diversity in the hybrid environment by exploiting the significant differences in path loss and shadowing characteristics of flying base stations (FBSs) as compared to the terrestrial base stations (TBSs). Preliminary results are presented to this effect and recommendations are made to their inclusion in the networks for supporting URLLC users in the future.

Next generation of mobile networks is the key area of research with increasing demand for new applications and use cases. In order to satisfy the applications with high data rate, high reliability, and low latency, multicarrier transmission through index modulation (IM) has been considered as a promising candidate owing to its flexible structures. In general, existing IM schemes are only evaluated for ideal communication scenarios. In this work, error performance of three frequency domain IM schemes are investigated and compared in the presence of carrier frequency offset (CFO) and in-phase/quadrature (IQ) imbalance. Orthogonal frequency division multiplexing with IM (OFDM-IM), OFDM with generalized IM (OFDM-GIM), and OFDM with subcarrier number modulation (OFDM-SNM) are assessed. It is shown via computer based simulations that although OFDM-GIM and OFDM-SNM provide higher spectral efficiency compared with OFDM-IM, they are more sensitive against RF impairments. Among them, OFDM-IM provides the best error performance under CFO and IQ imbalance.

Flexibility is one of the essential requirements for future cellular communications technologies. Providing customized communications solutions for each user and service type cannot be possible without the flexibility in 5G and beyond. Different optimizations need to be done for the flexibility related structures of 5G and beyond systems. In this paper, a novel machine learning (ML) based selection mechanism for the configurable waveform parameters is designed from the flexibility perspective. Moreover, a simulation based dataset generation methodology is proposed for ML systems. Results of computer simulations are presented using the generated dataset.

In this paper, beam expansion and optimization approach is proposed as a solution to alleviate blockage impact at millimeter wave (mm-wave) frequency bands. Directional communication in mm-wave bands provides opportunities to combat with high-level propagation loss. However, initiating communication over a certain direction makes the link vulnerable against blockage impact. In this study, an investigation on antenna directionality is conducted through indoor measurements and statistical analysis to elaborate directional link performance under blockage effect. Measurements are conducted at 60 GHz frequency band by using 15° half power beamwidth (HPBW) antennas at transmitter (TX) and receiver (RX). Beam expansion approach is evaluated by power azimuth spectrum (PAS) analysis. The proposed approach is also statistically analyzed using mm-wave channel simulator. It is shown that the beam optimization approach provides up to 13 dB gain (2 dB in average) on the received signal strength (RSS).

Sparse coding over a redundant dictionary has recently been used as a framework for downlink channel estimation in frequency division duplex massive multiple-input multiple-output antenna systems. This usage allows for efficiently reducing the inherently high training and feedback overheads. We present an algorithm for downlink channel estimation via selective sparse coding over multiple cluster dictionaries. A channel training set is divided into clusters based on the angle of the arrival/departure of the majority physical subpaths corresponding to each channel tap. Then, a compact dictionary is trained in each cluster. Channel estimation is done by first identifying the channel cluster and then using its dictionary for reconstruction. This selective sparse coding allows for adaptive regularization via sparse model selection, thereby offering additional regularization to the ill-posed channel estimation problem. We empirically validate the selectivity of the cluster dictionaries. Simulation results show the advantage of the proposed algorithm in achieving better estimation quality at lower computational cost, as compared the case of using standard sparse coding.

In this paper, we introduce a secure multiple access scheme, which exploits the multipath structure of the channel to create a multi-user interference environment. The generated interference enables legitimate users to share time and frequency resources over spatially secure communication links. Utilizing directional modulation, we ensure secrecy for legitimate users against eavesdropping while preserving mutual confidentiality between the legitimate users themselves. Moreover, we introduce a complementary scheme for covering the non-selective channel case. The scheme uses directional modulation in coordinated multi-point transmission to provide location-specific secure communication to legitimate users. We characterize the achievable performance using a newly defined metric called vulnerable region. We provide analysis for the achievable secrecy rate, secrecy outage probability, and channel correlation effect on the secrecy performance for the proposed scheme. Furthermore, the effect of the channel spatial diversity, channel estimation error, and the number of legitimate users on the secrecy performance is studied.

Automatic-repeat-request (ARQ) as a MAC layer mechanism and artificial noise (AN) as a physical layer mechanism along with the help of maximal ratio combining (MRC), are jointly designed to achieve secrecy. Basically, a special AN, which does not require null-space in the channel, is designed based on the quality of service requirements and the channel condition between the legitimate parties and injected to the data packet. If the same packet is requested by the legitimate receiver (Bob), an AN canceling signal is properly designed and added to the next packet. Then, an AN-free packet is obtained by using MRC process at Bob, while deteriorating the eavesdropper's performance. Furthermore, two simple closed-form expressions of the achievable secure throughput are derived. The first one is given in a closed-form for the case of ARQ scheme without AN, while the second one is given in an upper-bound form for the case of ARQ with AN. Moreover, this paper addresses two critical security-associated problems: 1) the joint design of secrecy, reliability, throughput, delay and the tradeoff among them, and 2) the increase in the peak-to-average power ratio (PAPR) due to the added AN. Finally, the proposed design is extended to OFDM to demonstrate its capability in not only enhancing the secrecy due to the frequency selectivity of the channel, but also in reducing the PAPR and out-of-band emission of OFDM-based waveforms, while maintaining secrecy.

Nonorthogonal multiple access (NOMA) is a promising technique which outperforms the traditional multiple access schemes in many aspects. It uses superposition coding (SC) to share the available resources among the users and adopts successive interference cancelation (SIC) for multiuser detection (MUD). Detection is performed in power domain where fairness can be supported through appropriate power allocation. Since power domain NOMA utilizes SC at the transmitter and SIC at the receiver, users cannot achieve equal rates and experience higher interference. In this paper, a novel NOMA scheme is proposed for multinumerology orthogonal frequency division multiplexing system, that is, different subcarrier spacings. The scheme uses the nature of mixed numerology systems to reduce the constraints associated with the MUD operation. This scheme not only enhances the fairness among the users but improves the bit error rate performance as well. Although the proposed scheme is less spectrally efficient than conventional NOMA schemes, it is still more spectrally efficient than orthogonal multiple access schemes.

In this paper, we propose algorithms for enhancing physical layer security and spectral efficiency of Orthogonal Frequency Division Multiplexing (OFDM) with Index Modulation (IM) systems. Particularly, different activation ratios and/or Constellation Modulation orders are selected adaptively for each subblock based on the channel quality of the legitimate receiver. More specifically, three approaches named as (1) OFDM with Adaptive Index Modulation and Fixed Constellation Modulation (OFDM‐AIM‐FCM), (2) OFDM with Adaptive Index Modulation and Adaptive Constellation Modulation (OFDM‐AIM‐ACM), and (3) OFDM with Variable Index Modulation and Variable Constellation Modulation (OFDM‐VIM‐VCM) are proposed for enhancing physical layer security and spectral efficiency. Simulation results are presented to investigate the effectiveness of the proposed algorithms.

In this paper, a practical power efficient technique is proposed for an untrusted decode-and-forward (DAF) based cooperative communication system to provide secure communication between the source and the destination. More specifically, a DAF relay, called switchable DAF (sDAF), is designed in such a way that it can be switched to amplify-and-forward (AAF) in certain predefined situations. The algorithm is based on destination-assisted jamming and comprised of two phases. The first phase securely shares the random manipulating sequence (RMS) through an untrusted relay, while the second phase uses this RMS for secure communication through untrusted relay. This algorithm not only provides secrecy, but also enhances the power efficiency as compared to other destination-assisted jamming techniques.

An effective and hardware-friendly physical layer security design, composed of a channel-based frequency pre-coder and a post-coder for OFDM-based systems, is proposed. The design is achieved by decomposing the diagonal matrix of the channel frequency amplitude of the legitimate receiver in order to obtain two unitary orthonormal matrices. The first matrix is used as a pre-coder just before the IFFT process at the transmitter, while the second matrix is used as a post-coder just after the FFT process at the receiver. Besides security, the presented design is interestingly found out to work as a shuffler or inter-leaver, which does not only provide secrecy, but also enhances the performance against burst errors. Moreover, a new channel calibration technique is developed to overcome the effect of channel reciprocity mismatch on the proposed scheme. The provided simulations and USRP hardware testbed implementation results validate the effectiveness of the proposed design in achieving practical and reliable secrecy with just minor modifications on the OFDM structure.

The next generation communication systems are evolving towards an increased flexibility in different aspects. Enhanced flexibility is the key in order to address diverse requirements. This paper presents the significance of adaptive guards considering a windowed-OFDM system which supports a variety of services operating asynchronously under the same network. The windowing approach requires a guard duration to suppress the out-ofband emissions (OOBE), and the guard band is required to handle the adjacent channel interference (ACI) along with the windowing. The guards in both time and frequency domains are optimized with respect to the use case and power offset between the users. To fully exploit and further increase the potential of adaptive guards, an interference-based scheduling algorithm is proposed as well. The results show that the precise design that facilitates such flexibility reduce the guards significantly and boost the spectral efficiency.

This work presents a simple, spectral and power efficient scheme for providing secure OFDM communication system using channel shortening. The basic concept is to utilize a channel shortening technique, whose design is based on the channel of the legitimate user (Bob), in such a way that the length of the effective channel is made equal to or less than the cyclic prefix (CP) at Bob only, while the length of the effective channel at the illegitimate receiver (Eve) is greater than CP. Thus, this causes inter-symbol-interference (ISI), loss of orthogonality, and overall performance degradation at Eve. The simulation results show that the presented technique can provide a significant BER performance gap between Bob and Eve, and can provide Quality of Service (QoS) based security. The design is shown to be robust against channel imperfections and can provide spectral and power efficiency beside enhancing security.

Using minimum, even insufficient guards are proposed to achieve the spectral efficiency and latency requirements of cellular communication systems beyond 5G. This leads to interference in both time and frequency domains. In this paper, a partial-non-orthogonal multiple accessing scenario in which the desired user is experiencing both intersymbol interference (ISI) due to insufficient cyclic prefix (CP) and adjacent channel interference (ACI) caused by asynchronous transmitters using non-orthogonal numerologies in adjacent bands is investigated. ISI and ACI depend on the power offset between desired and interfering users, the instantaneous channel impulse responses of interfering users and transmitter and receiver window functions. Therefore, joint and adaptive utilization of CP requires real-time calculation of ISI and ACI. Analytical expressions for expected ISI and ACI at each subcarrier of the desired user are derived to minimize their combination. Accordingly, an adaptive algorithm consisting of windowing each subcarrier at the receiver with window length that minimizes the combined interference at that subcarrier by optimally exchanging ISI and ACI is proposed. Interference reduction performances of current, outdated and average optimal window length raised cosine receiver windows are assessed and compared to fixed and no receiver windowing. Windowing reduces interference even when CP is shorter than the channel if window length is determined using the proposed design guidelines.

In vivo wireless body area networks and their associated technologies are shaping the future of healthcare by providing continuous health monitoring and noninvasive surgical capabilities, in addition to remote diagnostic and treatment of diseases. To fully exploit the potential of such devices, it is necessary to characterize the communication channel, which will help to build reliable and high-performance communication systems. This paper presents an in vivo wireless communication channel characterization for male torso both numerically and experimentally (on a human cadaver) considering various organs at 915 MHz and 2.4 GHz. A statistical path loss (PL) model is introduced, and the anatomical region-specific parameters are provided. It is found that the mean PL in decibel scale exhibits a linear decaying characteristic rather than an exponential decaying profile inside the body, and the power decay rate is approximately twice at 2.4 GHz as compared to 915 MHz. Moreover, the variance of shadowing increases significantly as the in vivo antenna is placed deeper inside the body since the main scatterers are present in the vicinity of the antenna. Multipath propagation characteristics are also investigated to facilitate proper waveform designs in the future wireless healthcare systems, and a root-mean-square delay spread of 2.76 ns is observed at 5 cm depth. Results show that the in vivo channel exhibit different characteristics than the classical communication channels, and location dependence is very critical for accurate, reliable, and energy-efficient link budget calculations.

While the wireless communication systems provide the means of connectivity nearly everywhere and all the time, communication security requires more attention. Even though current efforts provide solutions to specific problems under given circumstances, these methods are neither adaptive nor flexible enough to provide security under the dynamic conditions which make the security breaches an important concern. In this paper, a cognitive security (CS) concept for wireless communication systems in the physical layer is proposed with the aim of providing a comprehensive solution to wireless security problems. The proposed method will enable the comprehensive security to ensure a robust and reliable communication in the existence of adversaries by providing adaptive security solutions in the communication systems by exploiting the physical layer security from different perspective. The adaptiveness relies on the fact that radio adapts its propagation characteristics to satisfy secure communication based on specific conditions which are given as user density, application specific adaptation, and location within CS concept. Thus, instead of providing any type of new security mechanism, it is proposed that radio can take the necessary precautions based on these conditions before the attacks occur. Various access scenarios are investigated to enable the CS while considering these conditions.

Health care applications of wireless communication have been finding places dramatically. One of these applications is communication of implantable medical devices (IMD)s. It is expected that the number of IMDs will increase greatly in the near future. As a result, significant congestion will be experienced in medical implant communication service (MICS) band, leading to interference problems. In this study, we propose reliable listen-before-talk (LBT) mechanism at low signal-to-noise ratios (SNR)s for medical implant communication systems in order to mitigate the interference effects. In our method, we have just brought out power difference between mean peak and mean lowest power spectral values and it provides reliable and simple monitoring of MICS channels' occupation fastly. Our proposed method has superior performance when threshold power level is considered according to the federal communication commission (FCC) Part 95 regulatory standard.

This work introduces a physical-layer secure multiple-users communication scheme. Our scheme employs the multi-path nature of the wireless channel to provide a different secure communication link for each of the legitimate users. We show that the proposed scheme highly degrades the eavesdroppers channel even for the worst case scenarios. We also provide the secrecy capacity and secrecy outage probability for the proposed scheme. We analyze the effect of the number of users, channel paths, and antenna elements on the secrecy performance of the scheme.

In this work, the total spectrum sensing duration required for cognitive radios in multiband environments is studied to minimize the reactive handoff latency. Two spectrum sensing strategies, namely window-based and sample-based sensing, are evaluated to estimate channel workload and idle time probability. Channel workload is the percentage of time the band is used by other wireless networks. Idle time probability is defined as the probability of usable durations for the cognitive radio communications. The mean square error performance of the estimations is provided for both sensing strategies in the case of energy detection based sensing and realistic interarrival time distribution of packets. It is shown that, sample-based strategy requires half of the total multiband spectrum sensing duration compared to its window-based counterpart, if the hardware switching delay is under a specific threshold.

Performance of OFDM is known to be very sensitive to frequency synchronization errors. By exploiting this feature, a novel technique is proposed to provide secure communication against eavesdropping. The technique is based on introducing self inter-carrier interference to pre-compensate the carrier offset only for the legitimate user. This pre-compensation process depends on both the channel and the local carrier offset of the legitimate user, hence provides another degree of freedom for secrecy. Since an eavesdropper experiences an uncorrelated channel, his performance is expected to be degraded. Also our approach converts the simple one-tap frequency domain channel equalization to a very complex receiver operation for the eavesdropper. Moreover, the power aspects of this technique are discussed. By setting a threshold in the pre-compensation stage, we provide an acceptable trade-off between the transmitted power and the error performance.

In this work, we investigate the security performance obtained by employing a practical precoded orthogonal space time block coding method (POSTBC) in MISO wireless networks. In particular, space time codewords are precoded with an optimum matrix that minimizes the error rate at only the legitimate user (Bob). The acquired results depict that there exists a security gap region in the resulting BER performance as a consequence of using POSTBC. Moreover, we enhance the performance more by developing a new hybrid and green security method called precoding along with partial pre-equalizing (PCPPE). In this method, the transmitted symbols are precoded by a new precoder composed of both the original precoder and a new designed unitary matrix that maps Bob's channel amplitudes or phases estimated over the transmitting antennas into 2D orthonormal matrix. Additionally, three issues associated with the proposed security method have been tackled. Including: the slight increase in the transmit power, the appropriate selection process of the optimal precoding matrix, and the effect of imperfect channel estimation and reciprocity. The comparative simulation results prove that PCPPE method provides a secure link among the legitimate parties without sacrificing Bob's reliability although an eavesdropper is assumed to be fully aware of the used method and the original selected precoding matrix indicator (PMI).

In this work, Automatic-Repeat-Request (ARQ) and Maximal Ratio Combination (MRC), have been jointly exploited to enhance the confidentiality of wireless services requested by a legitimate user (Bob) against an eavesdropper (Eve). The obtained security performance is analyzed using Packet Error Rate (PER), where the exact PER gap between Bob and Eve is determined. PER is proposed as a new practical security metric in cross layers (Physical/MAC) security design since it reflects the influence of upper layers mechanisms, and it can be linked with Quality of Service (QoS) requirements for various digital services such as voice and video. Exact PER formulas for both Eve and Bob in i.i.d Rayleigh fading channel are derived. The simulation and theoretical results show that the employment of ARQ mechanism and MRC on a signal level basis before demodulation can significantly enhance data security for certain services at specific SNRs. However, to increase and ensure the security of a specific service at any SNR, adaptive modulation is proposed to be used along with the aforementioned scheme. Analytical and simulation studies demonstrate orders of magnitude difference in PER performance between eavesdroppers and intended receivers.

Orthogonal frequency division multiplexing (OFDM) inherently suffers from two major drawbacks: high out-of-band (OOB) power leakage and high peak-to-average power ratio (PAPR). This paper proposes a novel approach called suppressing alignment for the joint reduction of the OOB power leakage and PAPR. The proposed approach exploits the temporal degrees of freedom provided by the cyclic prefix (CP), a necessary redundancy in OFDM systems, to generate a suppressing signal, that when added to the OFDM symbol, results in marked reduction in both the OOB power leakage and PAPR. Additionally, and in order to not cause any interference to the information data carried by the OFDM symbol, the proposed approach utilizes the wireless channel to perfectly align the suppressing signal with the CP duration at the OFDM receiver. Essentially, maintaining a bit error rate (BER) performance similar to legacy OFDM without requiring any change in the receiver structure.

In this work, we introduce a novel approach, called suppressing alignment, to reduce the out-of-band (OOB) interference of orthogonal frequency division multiplexing (OFDM) systems. Suppressing alignment exploits the unavoidable redundancy provided by the cyclic prefix (CP) and the wireless communications channel to generate an OOB interference suppressing signal at the OFDM transmitter. However, after passing through the wireless channel, the suppressing signal is aligned with the CP duration at the OFDM receiver, essentially causing no interference to the data portion of the OFDM symbol. The proposed approach reduces the OOB interference by tens of decibels and does not require any change in the receiver structure of legacy OFDM.

It is a great pleasure welcoming all of you to the IEEE International Wireless Communications and Mobile Computing Conference (IEEE IWCMC 2015) in the beautiful Dubrovnik, Croatia! We are indeed delighted that this year's IEEE IWCMC lived up to its goal under the conference theme “Communications for the 21stCentury,” and continues its tradition of providing the premier forum for presentation of research results and experience reporting on the cutting edge research in the general areas of wireless communications and mobile computing. This year, we received more than 700 submissions from 42 countries. Each paper received at least three peer technical reviews, comprised of more than 450 TPC members from academia, government laboratories, and industries. After carefully examining all review reports, the IEEE IWCMC 2015 TPC finally selected about 36% high-quality papers for presentation at the conference and publication in the IEEE IWCMC 2015 proceedings. The conference program starts on Monday August 24thwith a full day of Tutorials that are free of charge to all our attendees. Then, each day starts with a keynote speaker chosen from renowned world-class leaders in the area-Dr. Giuseppe Bianchi from University of Roma Tor Vergata, Italy, Dr. Mario Gerla from UCLA, and Dr. Slim Alouini from KAUST, highlighting the latest research trends in the wireless communications, mobile computing, and networks. This year, the technical sessions reflect the continued and growing interests in a wide range of spectrum, including wireless communications and networks, cross-layer design and optimization, mobile computing, wireless sensor networks, network security, and use of wireless technologies in social emergency applications. There are two special sessions composed of invited papers from renowned experts from around the world. Outstanding papers will be selected for four Special Issues in well known international journals. Our objective in the future is to reduce the acceptance rate further.

Raising concerns about the security of wireless communication led researchers develop new concepts to keep information secret from eavesdroppers. Among them, physical layer security relies on the features of the wireless channels. Most of the work in physical layer security does focus on data transmission. On the other hand the focus of this work is to use manipulation of pilot tones to enhance communication security and to reduce eavesdroppers' ability to estimate the wireless channel. Particularly, we are introducing two novel algorithms, which manipulate pilot tones according to legitimate channels' phase and amplitude characteristics. Both algorithms decrease the channel estimation quality of the eavesdropper considerably, while the amplitude based algorithm provides high quality reception at the legitimate receiver. We provide resulting pilot error rates due to proposed algorithms. In addition, we show the effect of threshold selection to channel estimation quality both at the legitimate receiver and eavesdropper.

In vivo wireless medical devices have a critical role in healthcare technologies due to their continuous health monitoring and noninvasive surgery capabilities. In order to fully exploit the potential of such devices, it is necessary to characterize the in vivo wireless communication channel which will help to build reliable and high-performance communication systems. This paper presents preliminary results of experimental characterization for this fascinating communications medium on a human cadaver and compares the results with numerical studies.

Directional Modulation is a recently developed multi-antenna technique for secure transmission. It allows to transmit signals in desired directions while distorting the signal in the other directions. To secure the transmission in a scenario where eavesdropper is in the same direction as legitimate user, a coordinated multipoint scheme is proposed to have a location- specific secure communication that works even when a rich scattering environment is not available. Simulations are presented to verify the proposed scheme using 3 base stations.

In this paper, we introduce a windowing technique, which provides optimal time-frequency containment and maximal adjacent channel interference (ACI) rejection for orthogonal frequency-division multiplexing (OFDM)-based systems. Instead of using a single pulse shape function for all subcarriers, multiple functions are considered in order to maximize the time-frequency containment of the OFDM waveform. The main strategy is to concentrate the spectrum of windowing functions into a given bandwidth while achieving maximum suppression in the out-of-band region. This is achieved by employing prolate-based windowing functions which give optimal spectral concentration for time-limited pulse shapes. The windowing functions are designed per-subcarrier basis in order to exploit available concentration band for each subcarrier. In addition, the proposed concept is considered for the receive filtering in the presence of ACI. It is shown that the optimal spectral concentration property also maximizes ACI rejection for OFDM receivers.

Reconfigurable antennas (RA) offer an emerging technology that allows wireless devices to alter their antenna states determined by different radiation patterns to maximize received signal strength. In this paper, we consider multiuser orthogonal frequency-division multiple access cognitive heterogeneous networks (HetNets) and we study the potential benefits of employing RA in terms of improving the overall network capacity. In cognitive HetNets, a secondary network is allowed to share the spectrum with the primary network under the condition that the interference level experienced by the primary network is below a predetermined threshold. To satisfy this interference constraint, a secondary user (SU) employs a power control mechanism, which typically limits its transmission power and thus reduces substantially its performance. Moreover, the large number of users expected for next-generation networks brings dense interference to the secondary network and, as such, even efficient interference mitigation and resource allocation techniques can fail in maintaining an acceptable performance level for the network. In this work, we consider utilizing RA technology at SUs to act as an additional resource in terms of selecting antenna radiation patterns that improve received signal strength among SUs. This also limits the mutual interference between the secondary and primary networks. We propose a game theoretical framework for jointly selecting the subcarriers as well as the RA antenna state at each SU that maximizes the overall capacity of the network while meeting the interference target in the primary network. Using potential games that guarantee the existence of a Nash equilibrium, our results show that, by selecting the best RA state and subcarriers for each SU, the capacity of the secondary network increases substantially compared to a scenario with conventional omni-directional antennas.

The increasing number of mobile devices and the demand for large throughput requiring applications has hampered access to the limited frequency spectrum. The goal of this work is to introduce a new degree of freedom to the reuse of occupied resources by intentionally creating co-existence between different types of signals. First, the co-existence of orthogonal frequency division multiple access and single carrier-frequency division multiple access signals is introduced and analyzed for a conventional successive interference cancellation (c-SIC) processing. Then, the average bit-error-rate is derived for the proposed co-existence approach as a baseline. The results of the analysis lead to the design of an improved adaptive multi-user detection (MUD) approach, which outperforms the c-SIC receiver. The proposed MUD approach performs iterative likelihood testing and a signal-to-interference plus noise ratio based processing to improve the decoding performance. Additionally, three different power control schemes are proposed for heterogeneous networks to improve the gain further and observe the performance in the system-level. Our results show that the proposed combination of methods works well in dense mobile communication environments.

Reconfigurable antennas (RA) have been viewed as a hardware-efficient alternative solution to multiple-input multiple-output systems whereby network users can vary the antenna radiation patterns using a single antenna element to maximize the received signal strength. In this paper, we study the potential benefits of employing RA in multiuser orthogonal frequency division multiple access cognitive heterogeneous networks (Het-Nets) in terms of the overall network capacity. In cognitive HetNets, a secondary (unlicensed) network is allowed to share the spectrum with the primary (licensed) network under the condition that the interference level at the primary network is below a predetermined value. To account for this interference constraint, the secondary user (SU) can limit their transmission power and thus reducing substantially its performance. Moreover, the large number of users expected for next generation network brings dense interference to the secondary network and thus even efficient interference mitigation and resource allocation techniques can fail in maintaining the required performance level. Therefore, in this paper, we consider utilizing an RA at the SUs that acts as an additional resource which can be optimized by selecting the best state that maximizes the signal strength among the SUs and limits the mutual interference between the secondary and primary network. In particular, we propose a game theoretical framework for selecting the subcarriers based on best allocation techniques as well as the random antenna state selection that maximizes the overall capacity of the network while obeying the interference level in the primary network. We use potential games which guarantee the Nash equilibrium existence. Our results show that by selecting the optimal RA state and the subcarriers for each user, the capacity of the secondary network increases substitutionally with limited hardware complexity.

Macrocell-assisted small cell concepts, such as "Phantom cell concept" and "soft cell concept", have been proposed previously for interference management, flexible cell planning, and energy saving in dense small cell deployments. These concepts require macrocell involvement to improve links between small cell and user. Since target implementation areas of the concepts are crowded urban areas (e.g. downtown New York City) to satisfy the data need, more realistic simulations are needed to be implemented compared to conventional evaluations. In this paper, as a new approach to urban area LTE simulations, Manhattan grid layout is presented and implemented for mobility performance of Macrocell-assisted small Cell concept. The results show that the macrocell involvement to improve mobility performance gives a great advantage compared to using the conventional mobility solution for dense small cell deployments.

Cognitive heterogeneous networks (HetNets) have been recently introduced as a promising solution to meet the user demand for higher data rate. Due to the physical coexistence of microcells, femtocells and the lack of available spectrum, there is a need for techniques that allows users to share the same spectrum while maintaining required performance level for each user by adopting interference mitigation techniques. In this paper, we focus on resource allocation algorithm for orthogonal frequency-division multiple access (OFDMA) cognitive networks using game theory. In particular, we consider supermodular game theory, where given the problem meets specific requirement, the game has two significant features; it has at least one pure Nash Equilibrium (NE) and its best responses are monotonically increasing. Our objective is that each femtocell user selects a specific number of subcarriers determined by its needs. In comparison where at each iteration of the game, the femtocell user search all the subcarriers to maximize its payoff, our algorithm is based on selecting the subcarriers randomly and checks only those subcarriers that achieve higher payoff. Our results show that our algorithm reaches NE and can provide lower feedback compared to the sweeping-all subcarriers.

In an uncoordinated network, the link-level performance of a wireless receiver might degrade significantly due to the interference from other transmitters that share the same spectrum. As a solution, in this study, the concept of partially overlapping tones (POT) is introduced. In POT, interference energy observed at a victim receiver is mitigated by partially overlapping the individual subcarriers via an intentional carrier frequency offset between the links. It is argued that the self-interference arising due to the use of POT can be more easily addressed than the dominant other-user interference, potentially yielding higher spectral efficiencies with POT. Using a spatial Poisson point process based framework, a tractable bit error rate analysis is provided to demonstrate potential benefits emerging from POT in system-level scenarios.

Interference cancellation is expected to have significant importance for next-generation wireless communication systems due to various co-channel deployment scenarios and dense frequency reuse. In this study, an interference cancellation receiver that exploits the unique characteristics of single-carrier frequency-division multiple access based systems is proposed. The proposed receiver suppresses the co-channel dominant interference by employing a soft window to the frequency-domain samples where the desired and interfering signals overlap. In order to improve the performance, demodulation and regeneration stages are repeated multiple times by initially accommodating a group of reliable symbols before the iterations. The simulation results indicate that proposed methods work particularly well for low overlap ratios compared to interference coordination and no cancellation methods.

In a wireless communication medium, the transmitted signal reaches to the receiver antenna after passing through multipath channel. The difference in path delays and mobility cause the transmitted signal spread both in time and frequency, resulting in inter-symbol (or adjacent block) and inter-carrier (or adjacent channel) interference, respectively. The pulse shaping and matching filters used in the transceivers also impact the level of dispersion in both time and frequency. In this study, the composite effects of wireless medium and the used filters are investigated on the equalization of multicarrier systems. For this purpose, considering a symbol-spaced tap model for the equalization, the number of effective taps in both time and frequency domains is obtained via Akaike information criterion (AIC) for different signal-to-noise ratios (SNRs). Subsequently, a method which characterizes the equalization complexity of the receiver as a function of the transmit pulse shape, communication medium, the receive filter response, and SNR is proposed.

In this paper, we propose a multi-user aware frame structure for doubly dispersive channels in order to increase both spectral efficiency and frequency spread immunity of orthogonal frequency division multiple accessing (OFDMA) based systems. Unlike the conventional OFDMA based system where the fixed cyclic prefix duration and subcarrier spacing are utilized within the frame structure considering the worst case communication channel, in the proposed approach, multiple cyclic prefix durations and subcarrier spacings are employed. In order to build the proposed frame structure, the statistics of the mobility and the range of the users are mapped to inter-carrier-interference and maximum excess delay to obtain multiple subcarrier spacings and cyclic prefix durations. As a result, better frequency spread immunity and spectral efficiency are achieved by exploiting the doubly dispersive channel characteristics of the users.

Interference cancellation will become more important in future wireless communication systems due to various co-channel deployment scenarios and denser frequency reuse. In this study, an interference cancellation receiver is proposed which can be used for single-carrier frequency-division multiple access based systems. In the proposed receiver, impact of dominant interference (DI) is mitigated by an iterative blanking algorithm. If the DI is detected on the desired band, overlapping DI spectrum is blanked, followed by demodulation and regeneration of the desired signal. Afterward, the blanked overlapping samples are replaced by the corresponding samples of the regenerated signal. In order to improve the performance, demodulation and regeneration stages can be repeated multiple times. Performance of the proposed approach is compared with those of interference coordination and no cancellation through link-level and system-level simulations.

The recently proposed edge windowing technique provides a new degree of freedom between spectral efficient sidelobe suppression and controllable inter-symbol-interference (ISI) for orthogonal frequency division multiplexing (OFDM) based systems. By combining the introduced degree of freedom of edge windowing and the dependency of the channel dispersive characteristics to the distance between transmitter and receiver, ISI can be eliminated. Therefore, scheduling strategies becomes critically important for edge windowing in multiple accessing environment. In this paper, edge windowing technique is investigated along with different scheduling strategies; random scheduling, ranging based scheduling, and root mean square (RMS) delay spread based scheduling. Considering these scheduling strategies with the channel and edge windowing parameters, the performance metrics of sidelobe suppression, average error vector magnitude (EVM) on each subcarrier, and the worst case statistical characteristics of EVM are evaluated.

In a typical macrocell network, all macrocell mobile stations (mMSs) are synchronized to the macrocell base station (mBS) during the uplink. The mMSs that are closer to the mBS transmit their signals at a later time instant so that signals of all the all mMSs arrive at the mBS at the same time. However, signals of the mMSs reach at the femtocell base stations (fBSs) with different delays, which may cause interference problems for femtocell users. For orthogonal frequency division multiple access (OFDMA) based networks, interference due to delays larger than the cyclic prefix of the desired signal will appear as inter-carrier interference (ICI) and inter-symbol-interference (ISI). In this paper, statistics of the ICI power received from the mMSs at the fBSs is derived considering different locations of the fBSs in the macrocell network. The concept of zero-ICI region is introduced and its implications for coexisting macrocell/femtocell networks are presented. Theoretical findings are verified via simulation results.

Inefficient spectrum usage is a crucial issue in wireless communications and methods for dynamic spectrum access are proposed based on spectrum sensing methodology of the cognitive radio systems. Beside the detection and estimation methods, spectrum sensing procedures can also benefit from the modeling and prediction of the wireless spectrum usage. Markovian, regressive and other approaches are introduced for time or frequency domain channel modeling however, the research on the spectrum allocation methods indicates that location information has also an important influence on the spectrum occupancy characterization. In this paper, linear autoregressive prediction approach for binary time series is employed to investigate channel occupancy prediction performance based on spectrum measurements conducted in four different locations synchronously. Through the modeling procedure, dependency in frequency domain is also taken into consideration by modeling the adjacent frequency bands together. The model order is selected based on mean residual magnitudes and Akaike information criterion, mode order parameters are tabulated, and comparative prediction analysis considering the observation time is given for each location. The performance of the proposed linear modeling method is also compared with continuous-time Markov chain modeling in one of the locations.

In split spectrum macrocell-femtocell networks, certain portion of the available spectrum resources are dedicated to each tier in order to avoid interference problems among the tiers. In such a setting, effective partitioning of the spectrum resources carries critical importance for maximizing the total capacity and satisfying quality of service (QoS) requirements of the users within each tier. This paper proposes spectrum splitting methods for a macrocell-femtocell network considering factors other than the capacity maximization. First, a capacity maximizing spectrum splitting solution is derived based on certain simplifying assumptions. Then, a modified QoS-oriented fairness metric is introduced which captures important characteristics of tiered network structures that are not captured by the Jain's fairness index. Finally, a spectrum splitting strategy that simultaneously considers capacity maximization, fairness constraints, and QoS constraints is proposed. Example numerical results show that while only considering total capacity maximization may yield unfair spectrum splitting, a more balanced spectrum allocation can be achieved by also considering fairness and QoS constraints.

Access configuration of femtocell networks carries critical importance due to the resulting interference scenarios. Especially in closed-access femtocell networks, there might be significant interference between the femtocell and the macrocell users. In this paper, we evaluate the capacity of closed access femtocell networks employing various dynamic spectrum reuse techniques. When there is a macrocell user in the vicinity of a femtocell, the femtocell may dynamically decide not to reuse the spectrum of the macrocell user to avoid interference. We discuss and evaluate the following three decision criteria for this purpose: maximum sum capacity, minimum macrocell loss, and minimum effective interference. Computer simulations in realistic settings are provided to demonstrate possible gains with the proposed methods.

Adaptive modulation is an important method for effective usage of channel capacity in Orthogonal Frequency Division Multiplexing (OFDM) systems. Modulation identification algorithms unnecessitate the need of transferring the modulation information to the receiver, thereby these algorithms are very effective methods to increase the channel capacity. However, in practice, separate two sets of pilot symbols are used to identify the modulation type and to estimate the channel impulse response. In this paper, we propose one set of pilot symbols to get information about the channel and the modulation type, jointly. These pilots are named as “adaptive pilots” because they are related with the modulation type. Monte Carlo simulations are performed to observe the performance of the proposed adaptive pilot method and to compare with previously presented algorithm given in [1]. Simulation results indicate that the proposed adaptive pilots successfully help to identify correctly the modulation type without affecting the performance of the channel estimation.

Coexistence of narrowband (NB) and multicarrier technologies will be a major concern in next generation wireless communication systems due to the co-channel interference (CCI) problem. In this paper, an efficient CCI cancellation method is proposed that may be utilized for an improved coexistence. The method treats both co-channel signals as desired signals and enhances them in an iterative manner. Through computer simulations, it is demonstrated that it yields significant gains in the symbol error rate (SER) performance of both the NB and multicarrier systems. Its computational complexity is compared with the complexity of the joint demodulation technique and it is shown to be much lower.

Cognitive radio is an enabling technology for efficient utilization of radio spectrum. In this paper, an orthogonal frequency division multiple access (OFDMA) based cognitive (opportunistic) network is considered, which co-exists with a macrocell network through utilizing its unused subcarriers. We particularly consider the uplink opportunity detection problem by the opportunistic network, where accurate synchronization to the macrocell network is crucial for minimizing the interference received from the macrocell users. After demonstrating the impact of synchronization on the inter-carrier-interference (ICI) observed at the opportunistic network, an improved blind first-user synchronization technique is proposed, and its statistics are analyzed. Through computer simulations it is shown that the proposed technique yields less interference and better opportunities for the opportunistic network.

Direct conversion receivers are attractive for low cost systems as they avoid intermediate frequency (IF) filters. However, the direct conversion from radio frequencies (RF) to complex inphase (I) and quadrature (Q) baseband signals in one mixing step introduces additional front-end distortions. These IQ distortions lead to a degradation in the system performance. The problem becomes more significant in orthogonal frequency division multiple access (OFDMA) systems where multiple user signals with different IQ impairments are combined in the uplink (UL) signal. In this paper, detection methods for OFDMA-UL signals corrupted by IQ distortions are investigated. The received signal as a function of transmitted signals, IQ parameters, and communication channels is mathematically formulated. We designed a novel pilot pattern that is used by two proposed estimation and compensation methods of IQ impairments to the signal. Proposed methods were shown to significantly improve the system performance.

Cognitive Radio (CR) systems with spectrum awareness feature is a promising approach to use spectrum effectively. However, accurate modeling of spectrum utilization is crucial for the development and performance evaluation of such systems. Hence, in this paper, a wideband multidimensional spectrum occupancy measurement campaign is conducted to study the evolution of RF spectrum over time, frequency, and space dimensions simultaneously. The measurements are performed over three consecutive days considering 700-3000 MHz frequency band at four different locations concurrently. The measurement results show low utilization of the 700-3000 MHz frequency band with different utilization percentage at each location. Furthermore, the measurements confirm that the spectrum occupancy highly depends on the time, frequency, and location. As a result, multidimensional spectrum measurement and analysis are vital for accurate spectrum utilization modeling and performance evaluation of CR systems.

Location awareness is a prominent feature of cognitive radio (CR) systems. In order to support goal driven and autonomous location aware applications using CR systems, range accuracy adaptation is an essential task. Therefore, in this paper, performance analysis of optimal maximum likelihood (ML) time of arrival (TOA) range accuracy adaptation technique is conducted to study performance limits of location aware systems. The performance of ML-TOA range accuracy adaptation method is evaluated in dynamic spectrum access environments through computer simulations. The results show that range accuracy adaptation can be achieved by ML-TOA method with a relative error for each desired range accuracy.

In this paper, we explore a method for interference suppression in EGPRS (also commonly known as EDGE) systems, wherein 8PSK is used as the modulation for the desired signal and the interferer is modulated using GMSK. Previous methods for single antenna interference cancellation (SAIC) have concentrated on the case when both the desired and interfering signals are GMSK modulated, or have relied on highly complex methods such as joint demodulation. We derive a simple method that exploits the redundancy inherent in the interferer signal to suppress it. The interference suppression method causes a well- modeled nonlinear distortion to the 8PSK signal. This non-linear distortion is handled using a modified equalizer that deals with a time-varying input symbol constellation applied to a matrix channel. Simulation results using the method show great promise.

Separating user signals in the uplink (UL) of an orthogonal frequency division multiple access (OFDMA) system without access to the subcarrier assignment scheme (SAS) is a challenging task, but it can have a number of useful applications. In this paper, a semi-blind user separation algorithm is proposed, which assumes time synchronization and availability of information on the type of SAS used. The proposed algorithm estimates the carrier frequency offsets and time delays of each frequency allocation block by exploiting the cross-correlations over pilot subcarriers. A clustering method to group the blocks is employed, where each group belongs to a different user. Mathematical model of the proposed algorithm is presented, and possible user separation applications in OFDMA-based femtocells are discussed. Feasibility of the algorithm is proved through practical simulations.

In this paper, fundamental limits on time delay estimation are studied for cognitive radio systems, which facilitate opportunistic use of spectral resources. First, a generic Cramer-Rao lower bound (CRLB) expression is obtained in the case of unknown channel coefficients and carrier-frequency offsets (CFOs) for cognitive radio systems with dispersed spectrum utilization. Then, various modulation schemes are considered, and the effects of unknown channel coefficients and CFOs on the accuracy of time delay estimation are quantified. Finally, numerical studies are performed in order to verify the theoretical analysis.

Error vector magnitude (EVM) is one of the widely accepted figure of merits used to evaluate the quality of communication systems. In the literature, EVM has been related to signal-to-noise ratio (SNR) for data-aided receivers, where preamble sequences or pilots are used to measure the EVM, or under the assumption of high SNR values. In this paper, this relation is examined for nondata-aided receivers and is shown to perform poorly, especially for low SNR values or high modulation orders. The EVM for nondata-aided receivers is then evaluated and its value is related to the SNR for quadrature amplitude modulation (QAM) and pulse amplitude modulation (PAM) signals over additive white Gaussian noise (AWGN) channels and Rayleigh fading channels, and for systems with IQ imbalances. The results show that derived equations can be used to reliably estimate SNR values using EVM measurements that are made based on detected data symbols. Thus, presented work can be quite useful for measurement devices such as vector signal analyzers (VSA), where EVM measurements are readily available.

Accurate detection of spectrum opportunities within the frequency band of an orthogonal frequency division multiple access (OFDMA) system carries critical importance for OFDMAbased cognitive radios. In this paper, we analyze the opportunity detection performances of energy detection and ESPRIT (estimation of signal parameters by rotational invariance techniques) algorithms in the presence of timing misalignments in uplink (UL) OFDMA. For the energy detector, the statistics of subcarrier power are derived considering timing misalignments, and they are verified through computer simulations. Using these statistics, which take inter-carrier-interference (ICI) effects into account, receiver operating characteristics (ROCs) of the energy detector receiver are obtained. It is shown that energy detection has a considerably better performance than ESPRIT, especially when the subcarrier assignment changes frequently. Moreover, a closed form expression is derived for the UL-OFDMA synchronization point that minimizes the ICI. Finally, it is shown that employing resource allocation blocks with larger sizes in the primary network yields better opportunities for the cognitive radio.

Accurate detection of spectrum opportunities within the frequency band of an orthogonal frequency division multiple access (OFDMA) system is a critical requirement for the realization of a coexisting cognitive radio. In this paper, we analyze the opportunity detection performances of energy detection and ESPRIT algorithms in the presence of timing misalignments in uplink (UL) OFDMA. For the energy detector, the statistics of subcarrier power are derived, and the accuracy of these derivations is verified through simulations. The feasibility of opportunity detection in an asynchronous UL-OFDMA system is proven. Also, it is shown that energy detection has a considerably better performance than the ESPRIT algorithm especially when the subcarrier assignments change frequently.

In this study, the impact of mobility is investigated in low-speed environments such as femtocells and picocells for wireless networks. Given that there is interference on the uplink of a FDD system, this study solely focuses on how interference evolves with respect to mobility of terminals which move in a random fashion. Wiener-Levy process is used as a stochastic tool for characterizing the impact of mobility on the future behavior of interference. The results show that there is a trade-off between short and long interference observation (measurement) interval. On the one hand, choosing a short interval leads to a waste of processing power, since the interference level to be observed is not expected to deviate drastically from the previous observations. Choosing a long interval, on the other hand, increases the variance of the density of future interference level. In addition, results show that if there is more than one interference source in motion, the interference level observed has a tendency to increase in the future in low mobility environments. It is also shown that mean value of the interference level density to be observed in the future increases, whereas its standard deviation decreases with respect to the number of interference sources in motion.

Long term evolution (LTE) systems are expected to use single carrier frequency division multiple access (SC-FDMA) for the uplink. Being very similar to the OFDMA technology, SC-FDMA is sensitive to frequency offsets, which leads to inter-carrier interference (ICI). In this paper, we propose an interpolation algorithm based on adaptive order polynomial fitting for LTE uplink channel estimation to mitigate ICI in high Doppler spread. Simulation results show that the proposed method has better performance compared to the conventional schemes.

Methods for identification of orthogonal frequency division multiplexing (OFDM) signals and estimation of fundamental OFDM parameters are developed in this paper. Detected transmissions are classified as single-carrier or multi-carrier. In the case of multi-carrier transmission, OFDM symbol duration and cyclic prefix (CP) length are estimated blindly using characteristics of OFDM transmission. For estimation of symbol duration and CP length, cyclostationarity of OFDM signaling is explored by using a maximum likelihood (ML) estimator. The proposed algorithms can be used in cognitive radio for identifying various OFDM-based transmissions and for electronic surveillance to detect illegal or enemy signals.

OFDM multi-carrier modulation is expected to be the enabling technology for 4G wireless systems. One of the features that make OFDM the primary choice for 4G is its MIMO compatibility, because MIMO has a very significant potential of enhancing wireless systems for capacity, data rate, and coverage aspects. In this paper, the challenges of MIMO- OFDM measurements are addressed in comparison to SISO, with a special emphasis on WiMAX systems, which employ MIMO- OFDM technology. It is proposed to perform the reception and measurement of MIMO-OFDM signals using a single receiver branch rather than multiple receivers. A complete guide to perform impairment estimation for WiMAX MIMO signals with a single receiver according to the 802.16 standards is also provided.

One of the major goals of cognitive radio (CR) is to alleviate the inefficient use of the spectrum. CR can sense the spectrum steadily and gather information about the evolution of the spectrum in time. Spectrum occupancy information can be used for both learning the usage of the spectrum and predicting the future occupancy status. In this study, the use of binary time series for spectrum occupancy characterization and prediction is proposed. Both deterministic and non-deterministic occupancy schemes are examined. Numerical results and discussions are presented.

Ultrawideband impulse radio systems offer two kinds of processing gains that can be adapted based on the interference level in the system so that quality of service requirements are fulfilled. An adaptive assignment scheme for two types of multiple-access parameters in cluster-based wireless sensor networks is investigated. A mathematical framework is developed for asynchronous communications using a Gaussian approximation method to model the multiple-access interference in two cases: one with fixed frame duration, where the goal is to increase the average throughput, and the other with fixed symbol duration, where the goal is to increase the network lifetime. Extension of the analysis to multipath channels is carried out, and the validity of the Gaussian approximation is investigated using the Kullback-Leibler distance.

Location awareness is one of the essential characteristics of cognitive radios. In this paper, an innovative cognitive positioning system (CPS) that achieves accuracy adaptation in both indoor and outdoor environments is proposed as a step towards realization of location awareness in cognitive radios. The proposed CPS is composed of two modes; bandwidth determination and enhanced dynamic spectrum management (EDSM). Bandwidth determination equations are derived through Cramer-Rao Lower Bound (CRLB) for both additive white Gaussian noise (AWGN) and multipath channels. An EDSM system providing the optimum available bandwidth to the CPS is proposed. Overlay spectrum access based EDSM (O-EDSM) and hybrid overlay and underlay spectrum access based EDSM (H-EDSM) are two schemes that are introduced. A switching mechanism that manages the transition between underlay and overlay spectrum usage modes for the H-EDSM algorithm is presented. The theoretical analysis of the mechanism is carried out using Two-slope model. Simulation results, challenges and complexity options for the implementation of the CPS are outlined. Our study reveals the existence of a trade-off between the accuracy and complexity in the cognitive positioning systems.

Similar to OFDM systems, OFDMA systems also suffer from frequency mismatches between the receiver and the transmitter. However, the fact that each uplink user has a different frequency offset makes the compensation more challenging than that of OFDM systems. This letter proposes successive interference cancellation (SIC) for compensating the frequency offset in the uplink OFDMA systems. A decorrelator is used to remove the inter-carrier interference (ICI) within a user's signal and successive cancellation is applied to mitigate the multi access interference (MAI) arising due to the frequency difference among uplink users. The proposed algorithm is shown to eliminate the interference and has a manageable complexity.

Today's wireless services have come a long way since the roll out of the conventional voice-centric cellular systems. The demand for wireless access in voice and high rate data multi-media applications has been increasing. New generation wireless communication systems are aimed at accommodating this demand through better resource management and improved transmission technologies. Pushing the adaptive system design further by introducing multi-dimensional awareness, sensing, and learning from its experiences to reason, plan, and decide future actions to meet user needs brings the 'Cognitive Radio' concept into the wireless world. Even though there is no consensus on the formal definition of cognitive radio as of now, the concept has evolved recently to include various meanings in several contexts. One main aspect concerns autonomously exploiting locally unused spectrum to provide new paths to spectrum access. Other aspects include interoperability across several networks; roaming across borders while staying in compliance with local regulations; adapting the system, transmission, and reception parameters without user intervention; and having the ability to understand and follow actions and choices taken by their users, learning to become more responsive over time. The interest in increasing spectrum access and improving spectrum efficiency combined with both the introduction of software-defined radios (SDR) and the realization that machine learning can be applied to radios has created intriguing new possibilities for wireless radio research. This special issue discusses the cognitive radio, SDR, and adaptive radio concepts from several directions. There are many fundamental and practical issues that need to be studied more to ensure the success of these concepts in wireless communication markets. We are delighted that this special issue addresses some of these issues with eight papers selected through a competitive peer review process. In addition to the peer-reviewed papers, one invited paper is included. First, the invited paper discusses the practical implementation of cognitive radio including passing environmental information from the radio to the cognitive engine, using this information and performing real-time control of the radio platform by the cognitive engine. This paper provides a broad view to the readers and relates other technical papers to the larger themes of cognitive radio. A central value proposition of cognitive radio is to use limited radio spectrum resources as efficiently as possible. Opportunistic spectrum usage exploits the unused part of the spectrum to increase capacity. However, this requires spectrum awareness and new techniques for efficient utilization of densely occupied spectrum. The paper entitled 'Spectrum sensing in cognitive radio networks: The cooperation-processing tradeoff' discusses spectral awareness. Local and cooperative spectrum sensing and related issues are discussed under realistic radio channel conditions with fading. Next, in the paper entitled 'Spectrum sharing through distributed coordination in dynamic spectrum access networks,' techniques for the sharing of available spectrum are discussed. Coordination of the spectrum usage to support fair access to spectrum with minimum mutual interference is discussed. Related to these two papers, the fourth paper 'Formalizing the interference temperature model' defines the interference temperature model, and derives algorithms for computing radio frequency (RF) transmission parameters that maximize both capacity and spectral efficiency for a given RF environment. Similar to radio spectrum, radiated power is also a very important resource in wireless communications, especially for wireless sensor networks. The battery power is limited in small wireless devices, so it must be used very efficiently. One important consideration in cognitive radio is system design to adaptively use power as efficiently as possible. The fifth paper 'Efficient duty cycling through prediction and sampling in wireless sensor networks' deals with this issue through an innovative medium-access-control (MAC) layer protocol for wireless sensor networks for an adaptive interface to achieve ultra-low power operation. The next two papers address SDR implementation of cognitive radio. The paper entitled 'Automatic antenna tuning unit for software-defined and cognitive radio' discusses the implementation of an automatic antenna tuning unit system (ATU). Antennas for true SDR and cognitive radio realizations must cover a variety of frequency bands with radiation and reception parameters suited to different wireless standards. This paper covers recent progress in reconfigurable antenna technology. On the other hand, the paper entitled 'DSP implementation of a bit loading algorithm for adaptive wireless multicarrier transceivers' studies fixed-point DSP hardware implementations of an adaptive bit loading algorithm that can increase the capacity of the multicarrier systems like OFDM efficiently via implementation with reasonable computational complexity. The last two papers are related to the optimization of the radio resource and transmission parameters. The paper entitled 'Cognitive engine implementation for wireless multicarrier transceivers' presents a genetic algorithm (GA) driven cognitive engine for single carrier and multicarrier systems. The last paper entitled 'Install or invoke: The optimal trade-off between performance and cost in the design of multi-standard reconfigurable radios' finds the optimal trade-off between performance and cost, via a mathematical model of the design choices represented in a graph of progressively simpler functional modules. We thank the contributors of this special issue for their excellent contributions and for working with us to publish their work. Also, we extend our great appreciation to the reviewers who dedicated their valuable time to provide constructive comments, suggestions, and corrections. Finally, we thank the Editor-in-Chief, Professor Mohsen Guizani, and the staff at Wiley for their guidance. With such support, we believe that this special issue offers a considerable and timely contribution in the area of cognitive radio, and we hope that our readers will benefit from these papers and find them interesting.

Ultra Wideband (UWB) Systems take advantage of collecting energy from a large number of multipaths. In high data rate systems for time hopping (TH) UWB transmission, this large number of multipaths may leak into neighboring frames causing inter-frame interference (IFI). Most studies so far avoid this IFI by placing one or more constraints on chip length, frame length, minimum pulse to pulse duration, etc. In this paper, IFI will be investigated in detail for BPSK and PPM modulations in coherent transceivers. It will be shown that IFI effect is insignificant for these modulation options and for these transceiver architectures. Therefore, the constraints to avoid IFI can be removed for those systems. To the best knowledge of the authors, this type of analysis has not been conducted before and the simulation and semi-analytical analysis both result in a novel conclusion.

One of the popular modulation options that is used for ultra wideband (UWB) systems is pulse position modulation (PPM). In spite of many advantages of PPM, the cross-modulation interference (CMI) caused by multipath propagation degrades the performance of the UWB receivers when PPM modulation is used. In this paper, a technique for reducing the effect of CMI for PPM UWB signals is introduced. The proposed approach improves the performance of receivers greatly and eliminates the possibility of catastrophic errors. The proposed technique introduces variable modulation index instead of conventional fixed modulation index.

In this paper, the effects of various analog front-end impairments on the estimation of channel response for OFDM based wireless communication systems were discussed. Then, channel estimation algorithms that can take these effects into account were suggested. It was shown that the analog-front end impairments affect the performance of channel estimators greatly. However, with careful channel estimation algorithm designs, these effects can be minimized or completely compensated.

Multi-carrier modulation techniques, like OFDM, has been gaining significant interest for future wireless communication systems. In spite of all the advantages of OFDM, it has its own challenges. There are several impairments that can degrade the performance of the OFDM systems if the system and transceivers are not designed properly. IQ modulator impairements are among those that can limit the performance significantly. One of the major impacts of the IQ modulator in multiuser OFDM(A) systems (like in WiMAX) is that it introduces interference between the modulated symbols on the image carriers. In this paper, the interference effect caused by IQ modulators will be discussed. Self and multi-access interference caused by the IQ modulators will be explained for multiuser OFDM(A) systems. A joint demodulation based approach to suppress IQ modulator interference will be developed. The performance of the proposed algorithm will be obtained and the performance gains with respect to the conventional receiver will be demonstrated.

In orthogonal frequency division multiplexing (OFDM) systems, synchronization errors in the receiver cause a linear phase rotation at the output of the discrete Fourier transform (DFT) block. The correlation between the channel coefficients at different subcarriers is weakened due to this phase rotation. As a result, the performance of minimum mean-square error (MMSE) channel estimation degrades significantly. In this paper, we propose two novel algorithms to improve MMSE channel estimation under synchronization errors. Theoretical analysis and simulation results are presented to compare the performance of the proposed algorithms with that of the conventional algorithm.

Similar to OFDM systems, OFDMA systems also suffer from frequency mismatches between the receiver and the transmitter. However, the fact that each uplink user has a different frequency offset makes the compensation more challenging than that of OFDM systems. This paper proposes successive interference cancellation (SIC) for compensating the frequency offset in the uplink OFDMA systems. A decorrelator is used to remove the inter-carrier interference (ICI) within a user's signal and successive cancellation is applied to mitigate the multi access interference (MAI) arising due to the frequency difference among uplink users. The proposed algorithm is shown to eliminate the interference and has a manageable complexity.

Impulse-radio (IR) ultra-wideband (UWB) communications can be achieved with various transceiver architectures. Even though matched filtering is the optimal signal detection technique with Nyquist rate sampling, differentially coherent and non-coherent transceiver architectures may be favorable at lower rate samples. In this paper, we present a unified performance analysis approach for different IR-UWB transceiver types employing various modulation options and using the captured energy statistics at sub-Nyquist sampling rates. Energy capture versus robustness against noise is demonstrated as a trade-off for stored-reference transceivers. Theoretical results are verified via simulations

Time dispersion is one of the most important characteristics of the wireless channel. The knowledge about the time dispersion of a channel can be used for designing better systems which can adapt themselves to the changing nature of the transmission medium. In this paper, algorithms for estimating the time dispersion (frequency selectivity) of the channel, which use the frequency domain channel estimates or the frequency domain received signal, are proposed. The proposed algorithms first estimate the power delay profile (PDP) from which the two important dispersion parameters, namely root-mean-squared (RMS) delay spread and maximum excess delay of the channel, are estimated. It is shown that synchronization errors bias the performance of the estimators based on the channel correlation, and this bias is removed by obtaining the PDP using the magnitude of the channel estimates. The performances of the proposed algorithms are evaluated using computer simulations

For the practical LMMSE channel estimation of MIMO-OFDM systems, the high computational complexity of LMMSE needs to be eliminated. In this study, we develop a low-complexity, generalized low-rank LMMSE channel estimator for MIMO-OFDM systems using comb-type pilots. The estimator utilizes the relationship between the subspaces of the frequency domain channels at the pilots and non-pilots subcarriers. By using subspace tracking, it is observed that practical LMMSE channel estimation of MIMO-OFDM systems can be feasible.

In this paper, a low complexity coherent joint maximum-likelihood detection receiver is developed for cancelling multiaccess interference in impulse radio (IR) based ultrawideband (UWB) wireless communication systems. Unlike previous joint demodulation receivers, where the complexity is enormous and the other users' codes are required, the proposed approach does not need to know the time hopping (TH) codes of the other users which makes it a very attractive solution. The performance of joint demodulation receiver depends on the ability to estimate the channel coefficients of desired and interfering users. A novel and practical algorithm for estimating multiple users' channel responses is developed. The performance of the proposed algorithms are tested through computer simulations and the results are compared with the performance of the conventional single user UWB receiver. It is observed that the proposed joint demodulation receiver provides significant performance gains with respect to conventional single user receiver.

This paper presents a channel model for multiple input multiple output (MIMO) systems in the presence of three-dimensional (3-D) scattering. The model combines improved sum-of-sinusoids simulation models proposed for Rayleigh fading channels, and the two-dimensional (2-D) models proposed for MIMO systems, in a 3-D scattering environment. The distribution of 3-D scattering is assumed to be uniform in horizontal plane and Gaussian in the elevated plane. Simulation results showed that the new model satisfies the desired statistics with less Doppler spread, and hence can be used to generate independent fading channels for MIMO systems. The generated channels can be further processed to obtain correlated MIMO channels through the exploitation of correlation matrices at the transmit and receive sides. The resultant channel can then he used to simulate MIMO systems for a better system performance prediction.

Ultrawideband (UWB) is an attractive physical layer technology for wireless sensor networks due to its unique characteristics. Flexibility in adjusting the processing gain of UWB systems makes it possible to tune the data rate and transmission range to fulfill the requirements of specific applications. Conventional systems assign identical multiple access parameters to all users regardless of the signal-to-interference plus noise ratio of the received signal. An adaptive assignment scheme for multiple access parameters in cluster based wireless sensor networks is investigated. First, an orthogonal time hopping sequence construction is proposed for synchronous communications (downlink), where the number of pulses per symbol are adjusted to meet the bit error rate requirement of an application. Then, adaptation of multiple access parameters in asynchronous scenarios (uplink) is evaluated using a Gaussian approximation method to model the multiple access interference in two cases: one with fixed frame duration, where the goal is to increase the average throughput, and the other with fixed symbol duration, where the goal is to increase the network lifetime. Finally, a mathematical framework is developed for approximating the interference when the number of pulses per symbol and the frame duration vary.

Time hopping (TH) is commonly used with impulse radio (IR) based ultrawideband (UWB) systems as a multiple access scheme. In such systems, TH codes must he carefully designed to optimize the system performance. In this paper, TH code design for both synchronous and asynchronous UWB-IR systems are studied. For synchronous systems, a novel code assignment algorithm that depends on the number of users and delay spread of the channel is proposed. Then, the proposed codes are extended to quasi-synchronous scenarios. For asynchronous systems, frequency hopping (FH) codes obtained by finite field theory are applied to TH-IR, and their autocorrelation and crosscorrelation properties are investigated. A multiuser performance analysis method is proposed which makes use of code correlation characteristics.

The performance of multiple-input multiple-output (MIMO) systems improves substantially with the adaptation techniques like power allocation and antenna selection. These algorithms can he enhanced by considering characteristics of spatial correlation. In this study, the spatial correlation in MIMO systems is investigated to fully expose the parameters affecting it. The correlation analysis is performed by taking the effect of angle-of-arrival (AoA) statistics in three-dimensional (3-D) multipath scattering, mutual coupling, and near-field scatterers (NFS). The analysis shows that a valid model of the AoA statistics is the key parameter in the correlation analysis. Mutual coupling analysis for patch antennas reveals that coupling can reduce the correlation between antenna elements. On the other hand, the analysis on NFS suggest continuous correlation estimation. Fortunately, the rate of change of NFS is much slower than the MIMO channel variation. It is concluded that the performance of MIMO systems can be improved with accurate AoA models and tracking correlation changes.

Adaptive modulation is an effective method to increase the spectral efficiency of OFDM based high-speed wireless data transmission systems in time-dispersive (frequency-selective) channels. Blind modulation classification schemes play an important role in adaptive modulation systems to eliminate the need for transmitting the modulation information, thereby increasing spectral efficiency. In this paper, a maximum-likelihood (ML) modulation classifier which has the optimum performance in the presence of white noise is presented. A sub-optimum classifier, which greatly reduces the complexity, is derived from the optimum ML classifier. The performances of proposed classifiers are tested using Monte-Carlo simulations for ideal and non-ideal cases.

In mobile communication systems, downlink (forward link) system capacity is limited by the ability of mobile receivers to recover the desired signal in the presence of cochannel interference (CCI). Joint detection of the desired and cochannel signals is a useful approach to improving receiver performance, thus increasing system capacity. In this paper, we show that a practical single-antenna joint-detection receiver can provide significant gains in system capacity for the time-division multiple-access (TDMA) standard Telecommunications Industry Association/Electronic Industry Association/Interim Standard-136 (TIA/EIA/IS-136 or IS-136). For a sectorized system, joint detection provides a capacity gain of 47% in a typical urban environment. When used in conjunction with transmit beamforming, the synergy between the two approaches leads to a capacity gain of over 200%. In determining these gains, practical aspects of the IS-136 system are considered, namely, unsynchronized networks, limited receiver complexity, and adaptability. A semiblind acquisition process, which uses the training sequence of the desired user only, is employed, because the desired and interfering base stations are not synchronized. The receiver complexity is controlled by processing only one sample per symbol period, even though it is shown that multiple samples per symbol period should ideally be used. Finally, because receiver performance may be limited by its own intersymbol interference instead of CCI, an adaptive joint-detection process is used which selects between joint demodulation and single-user equalization for each slot.

A thorough investigation of mutual coupling effect on wireless communication systems is presented. Multiple antennas utilized by adaptive antenna arrays, spatial diversity structures, and multiple input-multiple output (MIMO) systems are analyzed for this purpose. In adaptive antenna arrays, mutual coupling can deteriorate the algorithms for getting the direction of arrival (DOA) and beamforming structure. In spatial diversity and MIMO systems, mutual coupling can increase or decrease the correlation between individual subchannels depending on the antenna configurations and the environment. An extensive mutual coupling model is needed to better analyze its effect on these systems. Available models either do not reflect all the parameters affecting mutual coupling or are not separable to the individual terms for a better analysis. In this paper, it is shown that mutual coupling can be expressed in terms of individual couplings due to antenna array geometry, near-field scatterers (NFS), and DOA. For MIMO and spatial diversity, DOA dependency drops since the feeding network does not have to be changed for a given DOA. By including the effect of NFS into the mutual coupling expression, the effect of mutual coupling on wireless communication systems can be better studied.

In this paper, average frequency correlation and root-mean-squared (rms) delay spread estimation for wireless communication systems are described. A practical algorithm for averaged channel frequency correlation estimation, which can be used for measuring frequency selectivity, is given. Average rms delay spread of the channel is obtained directly from the channel frequency correlation estimate without obtaining the channel power delay profile (PDP). Analytical relations between channel frequency correlation and assuming an exponentially decaying PDP derives rms delay spread value. Robustness of the proposed rms delay spread estimation method for other PDPs is evaluated. An orthogonal frequency division multiplexing (OFDM) based wireless communication system is considered for evaluating the performance of the proposed algorithm. It is observed that proposed channel frequency correlation and rms delay spread estimation algorithms work very well in various environments with different PDPs.

In this paper, reduced state sequence estimation (RSSE) for EDGE system is described. A significant issue associated with soft information generation for the RSSE receiver is discussed in detail. Several practical algorithms that calculate soft values efficiently are given. The performance of these algorithms is evaluated through computer simulation and compared with the performance of a more complex decision feedback sequence estimation (DFSE) receiver.

In this paper, we propose an adaptive joint detection receiver for co-channel interference cancellation in ANSI-136 handsets. The proposed receiver adaptively mitigates the dominant impairment present in the system: performing two-user joint demodulation in the presence of a dominant interferer and resorting to single-user equalization in a noise or inter-symbol-interference-limited system. The choice for the demodulator is based on the residual impairment power estimates obtained from single-user and joint acquisition using the training symbols of the desired user. Simulation results for a 1900 MHz ANSI-136 system indicate that the adaptive receiver performs well in various environments. By selecting the best demodulator for each slot on the basis of instantaneous channel conditions, the adaptive detector outperforms both single-user and joint detectors in fading channels.

EDGE has enabled the GSM network to offer third generation services as part of the UMTS core network. This is due to the introduction of 8PSK modulation and the recent specification of interfaces from the GERAN to the UMTS core network. This paper studies further improvements to the spectral efficiency and capacity of EDGE through the use of more sophisticated adaptive modulation schemes based on QAM, and the use of novel turbo coding schemes. Furthermore, this work considers a novel transmit diversity scheme adapted for use in dispersive channels. We provide performance results for the enhanced system showing tremendous gains. We also use theoretical predictions of outage analysis to predict the gain in performance obtained by the use of higher order modulations and transmit diversity. The gains from theoretical predictions match our simulations almost exactly.

The GSM/EDGE Radio Access Network (GERAN) is presently being evolved as a full complement to the 3G UMTS network. One part of this evolution is the introduction of efficient support of real-time packet data and alignment to the UNITS Core Network. Another part will introduce performance-enhancing features aimed at improving spectral efficiency, peak and average user-throughput and capacity. One such enhancement being considered is the use of Higher Level Modulations to enhance the user peak rate in the GERAN, in much the same way as the data rate for GPRS was enhanced with the 8PSK modulation in EDGE. By introducing new coding schemes based on QAM the maximum bit rate per time slot could be increased up to 88.8 kbit/s. This paper explains the GERAN concept and investigates possible system level gains, from both spectrum efficiency and perceived user quality perspective, with Higher Level Modulation in GERAN.

EDGE has enabled GSM networks to offer third generation services as part of the UMTS core network. This has been possible through two steps: the introduction of 8PSK modulation and the specification of interfaces from the GERAN (GSM/EDGE radio access network) to the UMTS core network. This paper studies further improvements to spectral efficiency and capacity for EDGE through the use of more sophisticated adaptive modulation schemes, and the use of newer coding schemes (see Nanda, S. et al., IEEE Commun. Mag., p.54-64, 2000; Ikeda, T. et al., IEEE Trans. Vehic. Tech., vol.49, p.404-12, 2000). It is possible to use theoretical predictions of outage analysis to predict the gain in performance due to the use of higher order modulations.

Joint demodulation techniques have been shown to be effective in mitigating co-channel interference for mobile handsets with only a single receiver antenna. As in the case of single user demodulation, a joint demodulation receiver needs to calculate the soft information values corresponding to the desired signal to optimize decoder performance. In this paper, practical soft information generation algorithms for use with joint demodulation of co-channel signals are described. The proposed algorithms are evaluated using the transmission parameters of a time-division multiple-access (TDMA) system known as American National Standards Institute-136 (ANSI-136).

Coherent joint detection of cochannel signals is an effective method for improving quality and system capacity for narrow-band TDMA systems in the presence of interference. Accurate estimation of signal parameters is thus required in order to separate the signals for different users. This paper proposes an accurate method for estimating phase and frequency errors that are present in the received signal. Combined with multi-user sequence estimation, an approach is developed that uses a cross-coupled, digital phase-locked loop (DPLL) to track the phase and frequency estimates during demodulation. Additionally, the frequency estimates are smoothed across multiple data slots to improve the performance. Simulation results are presented showing the efficacy of this approach to compensate for phase and frequency errors present in single-antenna ANSI-136 handsets.

Abstract Channel estimation is an integral part of standard adaptive receiver designs used in narrowband, digital wireless communication systems. In this tutorial paper, commonly used approaches to channel estimation are reviewed. Both time‐invariant and time‐varying channels are considered. For time‐varying channels, both pilot symbol interpolation and data‐directed channel tracking are considered. Applications include the Global System for Mobile communications, the Enhanced Data rates for Global Evolution system, and another Time‐Division Multiple‐Access system known as Telecommunications Industry Association/Electronics Industry Association/Interim Standard—136 (TIA/EIA/IS‐136 or IS‐136). Copyright © 2001 John Wiley & Sons, Ltd.

Doppler spread estimation in digital mobile radio systems is described. An optimal approach (in the sense of maximum likelihood estimation) for Doppler spread estimation is derived. Suboptimal approaches, with trading off in performance and complexity, are developed from the optimal algorithm. In practical systems, the Doppler spread must be estimated in the presence of frequency offsets between the transmitter and the receiver. Hence, an algorithm that decouples Doppler estimation from automatic frequency compensation (AFC) is also presented. The proposed algorithms rely on channel estimation over the known fields of a TDMA burst. Such algorithms can be applied easily to systems with pilot symbols or a pilot channel.

In this paper, efficient and practical approaches for Doppler spread estimation in wireless mobile radio systems are described. A hypothesis-testing approach, given the channel autocorrelation estimate, is utilized for Doppler spread estimation. The channel autocorrelation is estimated slot-by-slot using the knowledge of the channel estimates over the known fields of a TDMA burst, and averaged over several slots to reduce the effect of noise. In practical systems, the Doppler spread must be estimated in the presence of frequency offsets between the transmitter and the receiver. Hence, an algorithm that decouples Doppler spread estimation from automatic frequency compensation (AFC) is also presented. In addition to the mean estimation error performance, the convergence and the tracking ability of the algorithms are evaluated via simulation using ANSI 136 Rev-B modulation and signal transmission format.

In this paper, successive cancellation of co-channel signals is described in the context of TDMA mobile radio systems employing coherent receivers. Both symbol aligned and misaligned co-channel signals are studied. Signal separability, which is a major problem in successive cancellation of co-channel signals, is obtained using the relative timing delay between co-channel signals. Both hard and soft subtractions are examined. Soft subtraction, where the estimated values are weighted with some reliability measure, leads to significant C/I gains for both coded and uncoded bits.

Both IS-136 and PDC digital cellular systems employ forward error correction (FEC) encoding followed by a form of DQPSK modulation. To optimize FEC decoder performance at the receiver, soft information from the DQPSK demodulator is required. For frequency nonselective fading channels, which occur often in these systems, coherent demodulation optimizes performance. In this paper, we derive the maximum a posteriori (MAP) bit estimate for DQPSK modulation in non-ISI channels, assuming knowledge of the channel response. The MAP estimator forms a bit log-likelihood ratio, which provides the optimal "soft information" for MLSE or MAP convolutional decoding. Both single and multiantenna receivers are considered. MAP estimation requires exponentiation and logarithm operations, as well as knowledge of the noise covariance. To reduce complexity, two approximate forms are developed which avoid the exponentiation and logarithm operations. If the noise has the same power on each antenna and is uncorrelated between antennas, then knowledge of the noise covariance is also not needed. Performance of the optimal and approximate schemes is evaluated via simulation for single and multi-channel receivers under static and frequency non-selective Rayleigh fading conditions. The approximate approaches are shown to be within 0.5 dB of the optimal approach and to outperform existing approaches.

The capacity and signal quality of wireless communication systems can be improved dramatically by enhancing the receiver performance in the presence of adjacent channel interference (ACI). The sequence error rate is minimized through joint demodulation of all signals, but with high implementation complexity. Complexity can be greatly reduced through the use of successive cancellation, in which signals are detected and subtracted in descending order of signal power. However, successive cancellation performs poorly when signals have similar power levels. In this paper, an improved successive cancellation receiver for adjacent channel signals is proposed. The conventional detector is replaced with a simple form of joint demodulation. As a result, the receiver combines the benefits of joint demodulation, which works well when signals have similar power levels, with the benefits of successive cancellation, which works well when signals have dissimilar power levels. Performance results for the Global System for Mobile (GSM) communication digital cellular system show an order of magnitude reduction in bit-error-rate when adjacent channel signals are closely spaced and have comparable power levels.

The capacity and signal duality of wireless communications systems can be improved by enhancing receiver performance in the presence of adjacent channel interference (ACI). In this paper, an MLSE receiver for joint demodulation of adjacent channel signals is developed. This receiver provides significant improvement in performance over a wide range of carrier to interference ratios. A practical approach is taken, in which conventional down-conversion of each signal is performed followed by joint demodulation at baseband. To provide coherent reception, a novel form of joint channel estimation is used, exploiting knowledge of the transmit and receive filter responses. Receiver performance is evaluated via simulation for the GSM digital cellular system.