Publisher Copyright: © 2026 IEEE. EC/HE/101192113/EU//AMBIENT-6G

5G and the future 6G are proposed for industrial environments where reliability and low latency processing is required for factory automation. TSN has been used in fixed networks to deliver highly reliable deterministic communications. The 6G core can be used to support services but requires re-designing the user plane to support TSN service specific requirements. This paper presents a novel design for integrating unlicensed DECT radio technology as part of 6G Radio Access Network (RAN) to support services with deterministic requirements such as TSN. Design and implementation of SW gNB using DECT as radio technology and interaction with 5G network to support TSN is presented.

The rapid growth of smartphones, laptops, and IoT devices has created an increasing demand for seamless, secure, and energy-efficient wireless direct communication. Current popular solutions, such as AirDrop and Intel Unison, rely on Bluetooth Low Energy (BLE) for device discovery and pairing, alongside IEEE 802.11 (Wi-Fi) for high-speed data transmission. However, research has identified significant vulnerabilities in BLE, including information leakage and profile manipulation. To address these challenges, we propose an Enhanced Wireless Direct Connectivity (EWDC) framework that integrates Digital Enhanced Cordless Telecommunications (DECT)-2020 New Radio (NR) with Wi-Fi. In this framework, DECT replaces BLE to enable secure and efficient device discovery, while Wi-Fi supports high-bandwidth data transmission. Specifically, DECT utilizes its licensed spectrum to establish a secure communication channel for sharing Wi-Fi configuration information, enabling a secure and reliable setup of high-speed Wi-Fi data transmission links between devices. To validate this approach, we implemented the DECT MAC layer on the Nordic nRF9161-DK platform and evaluated the end-to-end delay between two devices. Our results demonstrate an impressive transmission delay of less than 1 μs for EWDC communication, enabling rapid device discovery and highly efficient operation. Furthermore, to enhance the security of wireless direct connections, the WireGuard, a VPN tunnel, is employed to encrypt data transmission over Wi-Fi providing robust protection for data shared on public frequency bandwidths. The proposed hybrid DECT-2020 NR and Wi-Fi solution significantly improves reliability, security, and communication efficiency, positioning it as a robust candidate for next-generation IoT communication systems.

The Ambient Internet of Things (AIoT), recently standardized by the 3rd Generation Partnership Project (3GPP), demands a low-power wide-area communication solution. Ambient Backscatter Communication (AmBC) is a promising approach that enables Backscatter Devices (BDs) to communicate by reusing existing signals without additional spectrum or energy cost. This paper investigates the feasibility of AmBC in the uplink of Long Term Evolution (LTE) cellular systems. We model the received BD signal, derive the optimal Maximum A Posteriori (MAP) detector, and propose simplified receiver architectures that achieve near-optimal performance with reduced complexity. A theoretical Bit Error Rate (BER) analysis is developed, including a Gaussian approximation, and the achievable coverage is evaluated. The results show that AmBC can sustain a BER on the order of 10−2at a reading distance of 1.5 m. Over-the-air experiments using commercial LTE uplink Sounding Reference Signals (SRS) further confirm the theoretical and simulation results. Overall, this work demonstrates that LTE cellular systems can natively support AmBC in the uplink, reinforcing its potential as a symbiotic radio paradigm for future low-power, spectrum-efficient AIoT connectivity.

The Long Term Evolution (LTE) is a promising can-didate to be used as a signal source in the Ambient Backscatter Communications (AmBC). LTE provides ubiquitous coverage, and LTE User Equipment (UE), such as mobile phone, can be used as the reader of a Backscatter Device (BD) signal with small firmware modifications. In this paper we measure a BD signal indoor coverage with commercial LTE base station as the illuminating ambient signal. The reader is synchronized to the LTE BS and estimates the BD signal from the LTE signal pilots. The BD is fully passive powered by a solar panel. The BD locations are distributed spatially along the corridor and for each BD location we measure the AmBC reader signal Bit Error Ratio (BER). The signal is uncoded. For each BD location the BER is measured from different directions with respect to the BD position. The measurement results show that along the corridor in most location, the observed BER is in order one percent. The results shed light on the feasibility of applications where the UE is in close proximity to the BD.

Ambient backscatter communication (AmBC) is a key enabler for green Internet of Things (IoT) employing ambient radio frequency (RF) signals for low-power communication. The AmBC devices discussed in the literature so far harvest light to power their microcontrollers for controlling RF modulation and reflection circuits. The ubiquitous presence of configurable light-emitting diodes (LEDs) based luminaires can also leverage such control functionalities by involving visible light communication (VLC). In this paper, we propose a visible light-enabled AmBC system that integrates VLC and AmBC for future ambient power-enabled IoT. We design LiBD, a backscatter device (BD) that uses visible light signals for both modulation control and energy supply. We demonstrate the real-time end-to-end data transmission with a proof of concept experiment. Evaluation results show that the LiBD supports multiple sub-6 GHz RF bands and can receive modulated light at frequencies up to 250 kHz. The investigations verify the feasibility of integrating the VLC and AmBC for future green IoT systems.

The utilization of millimeter-wave (mm Wave) fre-quencies presents a challenge due to their susceptibility to significant attenuation when encountering obstacles. Providing 5G cellular services using these frequencies has proven to be challenging. However, they exhibit suitability for fixed wireless access (FWA) applications. Fixed wireless links remain relatively stationary, allowing for network design centered around line-of-sight (LoS) coverage. This study delves into the investigation of LoS coverage by making use of existing base transceiver station (BTS) sites in a rural region of Finland. Laser-scanned geospatial data is employed to assess LoS coverage, considering both BTS and customer premise equipment (CPE) antenna heights. Additionally, measured throughput data from commercial 5G devices is utilized to estimate feasible user throughput. The assessment is carried out in the rural area of Pornainen, Finland, covering a total of 764 households and three pre-existing BTS sites. The analysis encompasses BTS tower heights ranging from 30 m to 400 m. Through this analysis, the study presents LoS coverage patterns for various combinations of BTS tower and CPE heights. Notably, the research demonstrates that residences with established LoS connections have the potential to achieve downlink throughput exceeding 3 Gbps at 26 GHz. This finding underscores the feasibility of high-speed connectivity in areas where LoS conditions are favorable, highlighting the potential for effective FWA deployment in rural settings.

In the ambient backscatter communication (AmBC) system, a backscatter device (BD) transmits its messages to receivers by modulating and reflecting incident radio frequency (RF) signals from ambient RF emitters. Most existing studies investigate single-antenna BDs and fabricate them using the conventional printed circuit board (PCB) method. In this paper, we propose flexible inkjet-printed integrated backscatter devices (IBDs) for indoor backscatter radios. We investigate and fabricate both single-antenna and multi-antenna IBDs using the inkjet printing technique. Since the commonly used substrate polyethy-lene terephthalate (PET) for inkjet-printed electronics has highly lossy properties, the printed feeding lines in the RF become inefficient. We propose to overcome this problem by positioning the backscatter switch next to each antenna and controlling them simultaneously with the baseband backscatter signal. Attenuation of the baseband control signal in printed lines is low leading to increase in overall efficiency of the proposed system. We validate the prototypes with received backscatter signal strength measurements in an anechoic chamber. The result shows that the printed four-antenna IBD can benefit approximately 9 dB diversity gain compared with the single-antenna version.

Ambient power enabled Internet of Things a.k.a. Ambient IoT is a novel concept connecting battery-free energy autonomous devices to the Internet. In this paper, we demonstrate the feasibility of using the channel estimator at the user equipment (UE) as a receiver for backscatter signals in LTE downlink. Our real-time demonstrator system consists of signal generator that mimics the operation of a base station (BS), a backscatter device (BD) modulating the incidence signal, and a software defined radio receiver that plays the role of the user equipment. The UE channel estimator and BD demodulation software is implemented with C++ and Python, respectively and made open source. Our results indicate that UE can demodulate the BD signal with bit error less than 10-3 when the downlink signal-to-noise ratio is larger than 10 dB when the pathloss between the BD and UE is less than 13 dB.

This paper presents experimental results of GPS free drone location using two antenna arrays. The experimental platform contains two synchronized stationary 4-by-4 rectangular antenna arrays. The arrays receive the signal emitted from a single antenna mounted on a drone. A Multiple signal classification (MUSIC) algorithm is applied to estimate the angle of arrival (AOA) at each array. The estimated AOA from both arrays is combined by the triangulation technique. We further employed the Extended Kalman Filter (EKF) to mitigate the estimated 3D location errors from the triangulation. To evaluate the performance of the AOA estimation, we conducted several measurements with different types of trajectories using a test-bed. The location estimation results of the proposed method are quantitatively compared and evaluated with the GPS trajectory of the drone. The estimation results have verified that the proposed experimental approach can localize and track the drone with reasonable accuracy.

Ambient intelligence demands collaboration schemes for distributed constrained devices which are not only highly energy efficient in distributed sensing, processing and communication, but which also respect data privacy. Traditional algorithms for distributed processing suffer in Ambient intelligence domains either from limited data privacy, or from their excessive processing demands for constrained distributed devices. In this paper, we present Camouflage learning, a distributed machine learning scheme that obscures the trained model via probabilistic collaboration using physical-layer computation offloading and demonstrate the feasibility of the approach on backscatter communication prototypes and in comparison with Federated learning. We show that Camouflage learning is more energy efficient than traditional schemes and that it requires less communication overhead while reducing the computation load through physical-layer computation offloading. The scheme is synchronization-agnostic and thus appropriate for sharply constrained, synchronization-incapable devices. We demonstrate model training and inference on four distinct datasets and investigate the performance of the scheme with respect to communication range, impact of challenging communication environments, power consumption, and the backscatter hardware prototype.

This paper presents a method for three dimension (3D) drone location estimation based on measured signals transmitted from a flying drone. During the experiment, we considered a single antenna mounted on the drone for signal transmission and a 4-by-4 rectangular array positioned at a known stationary location for receiving the incoming signal. Once the signal strength from the source is measured, the 3D position of the drone is estimated using the MUltiple SIgnal Classification (MUSIC) algorithm. The estimated values are then fed into an Extended Kalman Filter (EKF) as a measurement model, and the movement of the drone is formulated in a 3D trajectory plane. In order to evaluate the performance of our approach, we considered a histogram distribution and probability density function (pdf) of the drone position estimation error during its trajectory. The estimated 3D position of the drone is compared with the GPS values, and we ensure that the drone is localized based on the received signal from the experimental setup by first estimating the direction of the signal using MUSIC, and then tracking it using EKF in the predefined drone trajectory area.

Ultra-wideband terahertz (THz) wireless communication systems are anticipated as a promising solution for applications with high bandwidth requirements in an indoor environment. To design the communication system operating at THz or sub-THz frequencies, it is important to acquire fundamental knowledge about the radio propagation characteristics at those frequencies. The main target of this paper is to conduct power angular spectrum (PAS) measurements at sub-THz frequencies of 90, 95, and 100 GHz in a line-of-sight (LOS) office corridor environment, and validate the ray tracing (RT) simulation results with the measurements. A sophisticated photonics-based measurement setup with high accuracy is utilized for measurement, whereas, an in-house built RT tool is used for simulation. The PAS is measured and simulated at eight different locations and a decent agreement is achieved between both. Whereas the other channel characteristics like root mean square delay spread (RMS-DS) and angular spread (RMS-AS) are only investigated through RT simulations. In the case of direct orientation, the root mean square error of about 1.5, 0.9, and 3.7 dB is found between the measured and simulated received signal power level at 90, 95, and 100 GHz, respectively.

A better and accurate knowledge about the channel propagation characteristics is required to fully exploit the commercial frequency band of 26 GHz for Fifth Generation (5G) of cellular systems. Little is known about suitability of current urban macrocellular sites for serving millimeter wave frequency e.g., 26 GHz for 5G base stations. Therefore, in order to efficiently utilize the existing macro sites infrastructure an extensive millimeter wave outdoor measurement campaign is needed. Hence, in this paper we carry out a wide band continuous wave measurement spanning over a bandwidth of 800 MHz. Measurements are done at eighty-one equally separated frequency points in 26 GHz band. The measurements are performed with 76 m and 44 m transmitter antenna height in urban environments, with sufficient number of measurement locations. Mainly, we target the non-line of sight and obstructed-line of sight conditions. We carefully compute the path loss based on the measurement data, and also present the path loss exponent based large scale path loss model for two different considered scenarios. This paper also we discuss the impact of transmitter antenna height on the signal propagation.

Industrial Internet of Things (IIoT) and Industry 4.0 are used interchangeably while talking about the revolution in the field of manufacturing and logistic industries. IIoT is a digital ecosystem of connected devices, machines, equipment, and robots that communicate with each other without or with minimum human intervention. The 28 GHz band and 60 GHz band are two lucrative Millimeter Wave (mmWave) bands for 5G, and are getting popular since they enable standalone private network for IIoT. To ensure the successful deployment of IIoT in practice, we need to revisit our understanding of the radio channel characteristics at target frequencies in Indoor Factory (InF) environments. In this paper, we have considered three operating frequencies i.e., 3.5 GHz, 28 GHz and 60 GHz, and we investigate the performance of several Distributed Antenna System (DAS) and non-DAS layouts in 3GPP specified InF environment that is characterized by high density of blockers. The performance of the system is quantified in terms of received power, SINR, outage ratio, application layer throughput, and system capacity. The system performance is analyzed with Three-Dimensional (3D) Ray Tracing (RT) simulations. The acquired simulation results and related discussion provided in this paper gives insightful information about the communication properties in an indoor industrial environment.

Propagation characteristics of different frequency bands have a fundamental impact on the network planning aspects of practical cellular systems. A reasonable understanding of the radio propagation characteristics is already established and well-known large-scale propagation models are available for sub-6 GHz frequencies of operation. However, it is not true for a commercially available band of 26 GHz for fifth-generation (5G) of mobile systems in Europe, and better and accurate path loss models are required. In this research work, we carried out comprehensive continuous wave (CW) channel measurements at three potential 5G frequencies i.e., 1.9 GHz, 3.8 GHz, and 26 GHz in the city of Porvoo, Finland. The existing macrocellular base station (BS) site location is utilized during the measurement campaign. The large bandwidth available at 26 GHz makes it a feasible solution for fixed wireless access (FWA). The coverage achievable by these three bands was evaluated by fitting the alpha-beta-gamma (ABG) and close-in (CI) free space model to the measured path loss. This paper presents a link budget with practical considerations for different frequencies. In the light of acquired results, uplink (UL) is found coverage limited at all considered frequencies, and the attained results highlight the possibility of using 26 GHz band for FWA. Although, the outdoor-to-indoor service provisioning is challenging, however, interestingly it is found that around 1 kilometer and half kilometer coverage can be achieved in downlink (DL) at 26 GHz frequency for the use case of FWA and mobile users, respectively, in an outdoor environment.

The main target of this article is to propose a simple Received Signal Strength Indicator‐ (RSSI‐) based adaptive Physical Layer (PHY) selection approach for Bluetooth Low Energy 5.0 (BLE 5) and compare the performance of adaptive PHY selection with the performance of individual PHY. This article also validates the simulation results acquired from the in‐house developed Ray Tracing (RT) tool with the BLE 5 measurements conducted in a corridor of the TUAS building, Aalto University. The performance metrics considered for the analysis are RSSI, throughput, and outage ratio. The impact of different transmission power on BLE 5 is also analyzed. The obtained simulation results indicate a Root Mean Square Error (RMSE) of about 4.6 dB between the measured and the simulated RSSI at 2.4 GHz frequency. By investigating these results, an adaptive PHY selection algorithm is proposed in this article. The adaptive PHY selection approach enhances the mean throughput of the system and improves the outage ratio as well. In the light of acquired results, the adaptive PHY selection scheme shows significant performance gain and is found more beneficial in the case of an environment with mixed RSSI samples, i.e., a mix of low and high RSSI values.

Internet of Things (IoT) has revolutionized the concept of connectivity from only humans to almost everything capable of being connected. Wireless communication technologies are considered as the vital building blocks of IoT. Bluetooth Low Energy (BLE) with the highest penetration rate in consumer products has an important role in enabling IoT applications. BLE version 5 has recently been developed to meet the versatile requirements of IoT use cases. In this paper, we investigate the practical performance of BLE 5 in indoor office environment, and study the performance of its novel features. Our evaluation metrics in this study are throughput and Received Signal Strength Indicator (RSSI). In this study, BLE 5 measurements are conducted by using nRF52840 chip from Nordic Semiconductor. The acquired measurement results indicate that new Physical Layers (PHYs) of BLE 5 provide extended coverage and improves the throughput in indoor scenarios. The 2 Mbps uncoded PHY significantly improves the throughput in good RSSI zones. However, the throughput drastically drops in case of zones with moderate to weak RSSI. In particular, the feature of the coded physical layer helps extending the Bluetooth coverage, especially in Non-Line of Sight (NLOS) scenarios.

The main target of this paper is to propose a preferred set of features from a cellular network for using as predictors to do the classification between the rogue flying drone User Equipments (UEs) and regular UEs for different Machine Learning (ML) models. Furthermore, the target is to study four different machine learning models i.e. Decision Tree (DT), Logistic Regression (LR). Discriminant Analysis (DA) and K-Nearest Neighbour (KNN) in this paper, and evaluate/compare their performance in terms of identifying the flying drone UE using three performance metrics i.e. True Positive Rate (TPR), False Positive Rate (FPR) and area under Receiver Operating Characteristic (ROC) curve. The simulations are performed using an agreed 3GPP scenario, and a MATLAB machine learning tool box. All considered ML models provide high drone detection probability for drones flying at 60 m and above height. However, the true drone detection probability degrades for drones at lower altitude. Whereas, the fine DT method and the coarse KNN model performs relatively better compared with LR and DA at low altitude, and therefore can be considered as a preferable choice for a drone classification problem.

The future 5th Generation (5G) wireless networks are expected to support a variety of Bandwidth (BW) hungry applications. Millimeter wave (mmWave) communications, and Ultra Dense Network (UDN) deployment along with smart Distributed Antenna System (DAS) can be considered as a tempting solution for cellular networks. The aim of this paper is to analyze the performance of different UDN and DAS configurations in an indoor environment i.e. the real university office building at 3.5 GHz, 28 GHz, and 60 GHz frequency. System performance is analyzed by performing ray launching simulations using a three dimensional floor plan. The obtained results show the incapability of basic indoor solution in providing the ubiquitous Quality of Service (QoS) in an indoor environment at higher frequencies. Simulation results show that it is inevitable to have a dedicated indoor network with UDN or DAS configuration to provide homogeneous coverage in an indoor condition. It is found that in spite of more interference the UDN deployment provides a higher system capacity compared with DAS due to more number of cells. However, the gain of cell densification saturates with the increasing number of cells.

The main target of this paper is to evaluate the performance of a switched beam antenna in a macro-cellular environment at 28 GHz frequency. Another objective of this study is to compare the performance of a cellular system equipped with 7-beams switched beam antenna with conventional system implemented with wide 65° horizontal HPBW antenna. A campaign of 3D ray tracing simulations was carried out by using realistic 3D building data. Performance metrics considered for this study are RX level, SINR, system spectral efficiency, and the relative gain. Different configurations of 7-beams antenna is studied and the advantages and the disadvantages of considered configurations are highlighted in this paper. It is learned from the acquired results that an optimal configuration of 7-beams antenna can provide upto only 209.72 % of relative gain with respect to a traditional 3-sector site deployment. However, the relative performance gain of a 7-beam antenna can be negative under certain circumstances.

Narrow-Band Internet of Things (NB-IoT) is 3GPP's cellular technology designed for narrow-band and Low-Power Wide Area Network (LPWN). NB-IoT provides deep indoor coverage for thousands of low-data-rate and low-powered devices. Coverage enhancement for devices in weak coverage condition is enabled by having signal repetitions over extended period of time in order to boost the signal quality. Performance gain from repetitions of signals is limited by channel estimation quality. In this paper we analyze impact of channel coherence time on the uplink coverage. In addition to analytical performance bound and simulation results, we also present coverage performance results from practical measurements using a NB-IoT prototype. It is reported how the NB-IoT coverage improvement is limited by the channel estimation quality and coherence time of the channel.

Machine-type communication (MTC) devices usually have low-data rate, and in some applications, latency is critical. In long-term evolution, establishing a connection requires a relatively complex handshaking procedure. Such an approach is suitable for a system serving only a few high-activity users, but it becomes cumbersome for MTC traffic, where large amounts of low-activity users intermittently transmit a small number of packets. We propose a random access channel (RACH)-based scheme for the future 5G system that allows MTC users to send small packets within the random access burst. Device activity detection, channel estimation, authentication, and data decoding are performed simultaneously from the same access burst. In addition to the inherent reduction in energy consumption, the scheme eliminates the signaling overhead and creates more resources for data transmission. We have constructed an analytical framework for the detection performance of a multiple-input-multiple-output receiver in a frequency-selective channel. This has been validated with simulations, and results show that a one-shot correlate-and-cancel algorithm is sufficient for activity detection and channel estimation when the base station either employs multiple receive antennas or schedules multiple resource blocks for MTC RACH.

We consider D2D communication underlying cellular uplink communication when single stage interference cancellation receivers are available to improve local service. The interference cancelation configurations and transmission powers are jointly optimized in the network to maximize a network utility. Each receiver may or may not cancel the signal from the dominant interferer. With N-1 D2D pairs and one cellular transmitter, there are 2Npossible IC state combinations. A scheduling problem is formulated to allocate resources to these combinations, and network utility is maximized by iterating between scheduling weight and transmit power. In a simulation where sum rate or proportionally fair network utility is maximized, we observe significant gains in the spectral efficiency enjoyed by the users.

We investigate a non-cooperative interference canceling and power control (IC-PC) game in a Gaussian interference channel, where the receivers are able to process at most two codewords at a time. We characterize the equilibria of this game. As opposed to the pure power control game and the rate splitting game between the same players, we find that in the IC-PC game, there exist Nash equilibria where a player voluntarily reduces his power in order to enable interference canceling and achieve a higher rate.

The authors consider a short-range cognitive network with secondary users (SUs) generating voice calls. The SUs measure the TV spectrum and classify the measured bands as either idle or occupied. When most of the measured bands are detected to be occupied, there might not be enough capacity to serve all the SUs' calls. In this study the authors identify the minimum required number of measured bands such that the probability to serve all the secondary calls is controlled. The detection performance requirements imposed by the primary systems are also satisfied. The authors formulate this problem as an optimisation problem with optimisation parameters the number of users measuring each band and the measurement time. For a small number of SUs the authors identify the minimum required number of measured bands by using exhaustive search. For a large number of users the authors propose to solve the optimisation problem by means of a greedy algorithm. The algorithm is verified against the exhaustive search results and it is found to perform remarkably well. Therefore it is suitable for practical secondary systems searching for sharing opportunities over the TV spectrum.

The main requirement for secondary operation over the TV white spaces is interference control. In this paper, we propose an interference control scheme that allows multiple secondary systems to maintain their aggregate interference at the TV receivers under specific protection limits. The main characteristic of the proposed scheme is the small signaling overhead required for the cooperation between the secondary systems. The secondary systems need only to communicate their locations to a central network controller. The controller can then allocate the transmission power levels to the different systems such that the TV receivers are sufficiently protected. At the same time, the sum of the transmission power levels allocated to the secondary systems is maximized.

The estimation of the total interference generated from a secondary system is essential for protecting the primary receivers. However, interference level estimation from a large number of secondary transmitters is a challenging problem. In this paper, we estimate the aggregate interference as an integration over the power spatial density in the secondary system's deployment area. We modify such integration-based model to contain the correlation in shadow fading. We apply the model on a cellular system downlink and study how well the proposed analytical model describes the interference level in correlated and non-correlated slow fading environment. The analysis indicates that for cell size less than five km the integration based model describes interference relatively well. For larger cell sizes, the interference is dominated by a few strong sources and has to be computed by summing over the power of all individual transmitters. It is also illustrated that the full correlated and independent slow fading provide two extremes of the amount of generated interference. The complex estimation of the impact of the fading cross correlation can be avoided by using those two extreme models as bounds to the interference level.

We consider a short range cognitive network searching for spectrum holes from very wide bandwidth. In practice, one cognitive user can sense only a small portion of spectrum. Unfortunately, in fading environment a reliable detection scheme requires measurements collected by multiple users. Because of that, it is unreasonable to expect a small-sized network to sense the complete candidate bandwidth. In this paper we propose an algorithm for optimal sensing of multiple spectrum bands by multiple cognitive users. The user allocation is optimized so that the expected opportunistic throughput is maximized and the total power spent for spectrum measurements is controlled. As a constraint we use the detection performance requirements imposed by the primary systems. For a small number of spectrum bands the optimal solution can be found by exhaustive search. For a large number of spectrum bands we view the spectrum sensing as a multiple choice knapsack problem. By using algorithms for this class of problems we propose two heuristics that are suitable for optimizing spectrum sensing in multiband cognitive networks. These algorithms provide quick, near optimal solutions and are therefore suitable for practical spectrum sensing systems.

In a bandwidth limited channel the constellation shaping can easily provide 1 dB SNR improvement. The conventional view is to handle coding and shaping as two separate operations. Because of that, it is usually difficult to incorporate shaping into decoder structure. In this paper we propose to combine a trellis based constellation shaping and turbo code. We suggest to select the shaping code and the turbo code to have a same trellis structure. The resulting code can be turbo decoded by iterating between the shaping and the channel code. Because the trellises have the same structure we could tap into shaping gain without changing the conventional turbo decoder structure. Accordingly to the simulations the proposed structure provides 0.8 dB gain over the comparable bit interleaved coded modulation (BICM) system. This gain is achieved without the increase of turbo decoder complexity.

A major issue in feedback systems is to use the feedback bits most efficiently. In this paper, we use information theory to get an upper limit on the value of feedback bits in an optimum AMC system. The AMC optimization problem is simplified by using ideal error performance (i. e. a step function like performance curve) characteristic of capacity-reaching codes. Given a strong enough code such as turbo code similar step function based approximation can be used. The results show nice match between the solution sets from the ideal error performance approximation and the real error performance.

In this paper we investigate the detection of OFDM primary signals using autocorrelation. The conventional model for signal detection in cognitive radio assumes that the primary signal is either absent or present with a fixed level. We show that the conventional model is the source of significant discrepancy between the analytical prediction of the detection algorithm and the simulations. We propose to design the autocorrelation-based detector using the uniform approximation for the distribution of the primary signal power. The uniform approximation allows to derive the optimal decision threshold by using the Lagrangian optimization. Finally, we are able to design the autocorrelation-based detector such that the spectrum reuse is enhanced and the analytical prediction of the detection algorithm achieves a better match with the simulation results.

The autocorrelation-based detection of OFDM signals with cyclic prefix is an appealing method for cognitive radio because it has low complexity and it allows to separate between different OFDM-based legacy systems. Unfortunately, it is also sensitive to noise estimation errors provided that a single estimate of the autocorrelation function is calculated. In this paper we design an autocorrelation-based detector for OFDM signals with cyclic prefix that is also robust in the low SNR under noise uncertainty. The proposed decision statistic allows us to calculate the error probabilities in a closed-form.

In this paper, we consider optimum rate quantization of Adaptive Modulation and Coding (AMC) systems by jointly designing the MCS levels and intervals. Optimum quantization leads to coupled non-algebraic equations, and is generally not amenable for analysis. Here, we propose two approximate AMC rate quantization methods, which are based on an observation of the optimal condition and the numerical results in the literature. The numerical results show that both proposed methods are near-optimum in expected throughput.

The primary signal detection is an essential operation for the secondary spectrum usage. In this paper we extend the covariance based detection for multiple-antenna receiver. The proposed method uses the noise power estimation and does not suffer from the noise level uncertainty. We analyze the detection algorithm and compute the distribution of the decision variable not only for the pure noise case but also for the jointly presence of primary signal and noise. By deriving the distribution of the primary signal in noise we are able to use the detection probability as the detector design constraint. Our analysis takes advantage of the high amount of samples available at the detector. The proposed method sets the foundation for the analysis of any detector that involves cross correlation, summing and squaring operations of samples.

Most algorithms for secondary spectrum usage are solely based on signal detection. The frequencies where the primary signal is detected with level comparable to the noise are considered occupied. As a result vast areas in the proximity of primary cells become illegal for spectrum reuse. In this paper we propose an algorithm that enhances spatial spectrum reuse by allowing secondary users to communicate in the presence of primary signal. We study how much the spectrum utilization is increased by using the proposed algorithm. The algorithm has multiple decision stages and it is based both on signal detection and generated interference estimation. It allows to minimize the decision errors and control the generated interference to primary user receivers. The algorithm is modeled by using Bayesian hypothesis testing approach. The required prior probabilities are related to the geographical interpretation of the studied system. The constructed model allows to find the optimal decision levels through the Lagrangian optimization. The algorithm performance is evaluated as a function of the number of measured power samples. Comparison to a simple detection based scheme indicates recognizable improvement especially for a low number of samples.

In this paper we analyze the performance of the distributed power detection algorithm operating in a shadowing environment and with communication constraints. A well performing detection algorithm is critical for detecting a primary user's signal for dynamic spectrum allocation purposes. Dynamic spectrum allocation allows a secondary user to use a spectrum chunk provided that the primary user is not disturbed. In a shadowing environment one secondary user could not guarantee a reliable detection of primary user's signal with acceptable false detection probability. The detection performance can be greatly enhanced by combining measurements from secondary users at a fusion centre. Such combining requires communication bandwidth. We provide equations and numerically compute the bounds for two extremes of communication requirements. In the first scheme the secondary users send a full loglikelihood ratio, which in principle would require infinite amount of communication capacity. In the second scheme the secondary users send to the fusion centre only one bit, describing the hard decision made based on the loglikelihood ratio. These two cases provide performance bounds for possible practical implementations.

This paper introduces a method for calculating the mutual information between the messages sent to a loop and returning from a loop in a Tanner graph. This mutual information is defined as the difference between the cases when the loop is open and the loop is closed. The proposed method suggests to track the change of information in each node in the loop. The paper explains in detail how to calculate the amount of information change in a node

In This work we derive an error model for the modified Gilbert multiplier, soft gate. Such multiplier is the basic building block of an analog turbo decoder. Error in the soft gate impacts the performance of the decoder. Our purpose is to derive the equation that allows to minimize this error. The error model describes variation at the multiplier output and is derived based on the mismatch in the individual transistors. We are looking at the CMOS process where the transistors are operating in the subthreshold. The mismatch is described as the variation in current factor and threshold voltage of the individual transistors. These parameters depended on circuit production process and therefore the model allows to study the impact of the process parameters to the error in decoding. As it turns out the soft gate error depends on the working point of the multiplier. In weak inversion the relative impact of the individual transistor mismatch error to the soft gate output error is higher than in strong inversion.