Autonomous vehicles (AVs) require real-time, low-latency, and high-throughput communication to ensure safe and efficient operation. Fifth-generation (5G) and beyond communication networks, particularly New Radio (NR) operating at millimeter wave (mmWave) frequencies, offer promising solutions. However, higher frequencies introduce challenges like signal attenuation, blockage, and complexities of beam management. This paper provides a comprehensive survey of 5G and beyond communication networks, emphasizing their role in vehicle-to-everything (V2X) communication. It uniquely addresses the technical challenges of beam training and management, highlighting the application of artificial intelligence (AI) and machine learning (ML) techniques to optimize beam selection and reduce delays. Furthermore, the paper explores future directions, focusing on AI/ML-driven solutions to enhance beamforming and communication reliability in dynamic AV environments.

The implementation of indoor localization is being facilitated through commercially available low-cost mm-wave sensors. These sensors generate point cloud outputs containing noisy estimates of detected targets due to hardware noise and multipath reflections. In contrast to previously studied regression approaches, this study introduces a classification-based approach to predict the angle-of-arrival (AoA) and range of a human target from point clouds obtained from an mm-wave sensor. Our proposed methodology achieves a 7% and 26% improvement in AoA and range prediction, respectively, compared to the baseline models. All experiments have been conducted and validated using real data recorded by the mm-wave sensor.

Avstract-The primary concern in 5G and beyond wireless technologies revolve around the exponentially growing number of network users and subsequently increasing demand for frequency spectrum utilization. Traditional static spectrum allocation schemes have proven to be highly inefficient in using the available spectrum. In recent years, Dynamic Spectrum Sharing (DSS) solutions based on Cognitive Radio (CR) and Artificial Intelligence (AI)/Machine Learning (ML) have been proposed. CR involves spectrum sensing, spectrum sharing and decision-making paradigms essential for efficient use of radio frequency spectrum. AI/ML techniques, with their autonomous classification, learning, and decision-making capabilities, offer an improved approach. This paper proposes a Support Vector Machine (SVM) based ML technique for spectrum sensing in beyond 5G networks. A theoretical examination of detection and false alarm probabilities is first conducted. It is shown that the SVM algorithm achieves a high probability of detection at 99.66%, ensuring reliable spectrum sensing. Further, it is verified through simulations that the experimental outcomes align closely with the theoretical results concerning both detection and false alarm probabilities.

Ultra wideband (UWB) is a popular technology to address the need for high-precision indoor positioning systems in challenging industry 4.0 use cases. In line-of-sight (LOS) environments, UWB positioning errors in the order of 1–10 cm can be achieved. However, in non-line-of-sight (NLOS) conditions, this precision drops significantly, with errors typically >30 cm. Machine learning (ML) has been proposed to improve the precision in such NLOS conditions, but is typically environment-specific and lacks generalization to new environments and UWB configurations. As such, it is necessary to collect large data sets to train a neural network (NN) for each new environment or UWB configuration. To remedy this, this article proposes automatic optimizations for transfer learning (TL) deep NNs toward new environments and UWB configurations. We analyze error correction and (N)LOS classification models, using either feature- or channel impulse response (CIR)-based input data. Our TL solutions show a 50% error improvement and 15% (N)LOS classification accuracy improvement (for both feature- and CIR-based approaches) compared to a model trained in a different environment. We also analyze the impact on TL using a limited number of samples (25 to 400 samples). The highest accuracy is typically achieved by the CIR-based approach, where with only 50 samples from the new mixed (N)LOS environment, we show ±10 cm precision after error correction with 93% (N)LOS detection. The presented results demonstrate high-precision UWB localization (from 643 to 245 mm) through ML with minimal data collection effort in challenging NLOS environments.

The selection of an optimal photodetector area is closely linked to the attainment of higher data rates in optical wireless communication receivers. If the photodetector area is too large, the channel capacity degrades due to lower modulation bandwidth of the detector. A smaller photodetector maximizes the bandwidth, but minimizes the captured signal power and the subsequent signal-to-noise ratio. Therein lies an opportunity in this trade-off to maximize the channel rate by choosing the optimal photodetector area. In this study, we have optimized the photodetector area in order to maximize the channel capacity of a free-space optical link for a diverse set of communication scenarios. We believe that the study in this paper in general—and the closed-form solutions derived in this study in particular—will be helpful to maximize achievable data rates of a wide gamut of optical wireless communication systems: from long range deep space optical links to short range indoor visible light communication systems.

To bring fifth generation (5G) mobile communication capabilities to indoor users, small cells and distributed antenna systems are two promising technologies being considered. This paper investigates and compares the performance of indoor deployed small cell base station (SBS) and indoor distributed antenna systems (DAS) in an isolated multi-storey building. Each floor of the building is equipped with either an indoor SBS or an indoor DAS where geographically distributed remote radio heads (RRHs) are connected to a central unit (CU), and frequency reuse is employed among floors. Signal propagation characteristics within multi-storey buildings and the impact of inter floor interference on performance is analysed and compared for both systems. The effect of different reuse distances, pathloss exponents, penetration loss and co-channel interference on achievable rate is analysed over a wide range of potential mobile equipment (ME) locations.

Hybrid digital to analog precoding is widely used in millimeter wave system to reduce power consumption. The radio frequency (RF) chains consume maximum transmitted power, therefore, in this paper optimal number of RF chains are selected to achieve the desired energy efficiency (EE). The novelty of the proposed method is in two folds. First, the optimal number of RF chains are selected by the proposed bisection algorithm. Second, the optimal analog precoder is designed by power iteration algorithm, followed by the digital precoder which is designed by the known least squares method. The effect of the resolution of the phase shifters used in the analog precoder on EE is investigated. Simulation results show that the proposed algorithms outperform the existing algorithms in terms of the EE and the achievable capacity. It also showed that the hybrid precoding with an optimal number of quantized bits of resolution attains the best EE performance.

Hybrid digital to analog (D-A) precoding and decoding design has recently been the focus of considerable fascination for reducing the number of costly radio- frequency (RF) chains in millimeter-wave (mm-Wave) systems. This paper investigates multi-user joint hybrid D-A precoding and decoding design for mm-Wave large antenna systems. The intrinsic focus of this work is to reduce the interference caused by users sharing the same scatterers during simultaneous uplink transmission. The analog precoder and decoder, firstly, are jointly designed using a Riemannian optimisation method based on Stiefel manifold (ROSt) in order to maximise the desired signal while reducing the interference. Then, the digital decoder is also designed jointly using Minimum Mean-Square Error (MMSE) based on effective channels. To significantly enhance the performance, an iterative algorithm is further presented that employs uplink and downlink effective channels. To accomplish this, the analog precoder and decoder are jointly designed based on downlink effective channels and steepest descent (SD) algorithm. Once again MMSE is applied for the digital decoder by exploiting effective channels. Extensive simulations demonstrate that the achievable rate of our proposed ROSt and SD algorithms surpasses the achievable rate of the existing algorithms in hybrid D-A paradigms.

Hybrid digital-to-analog (D-A) precoding is a promising technology to reduce the number of radio frequency (RF) chains in a millimetre-wave (mm-Wave) multiple-input multiple-output (MIMO) system. To reap the full scale benefits of the hybrid D-A precoding, in this paper, two algorithms are proposed to maximise the capacity of the hybrid D-A mm-Wave MIMO system. The first algorithm is based on the principle of manifold optimisation (MO). The second algorithm operates on particle swarm optimisation (PSO). These two algorithms are compared with three existing hybrid D-A precoding algorithms in the literature. The simulation results show that the proposed algorithms achieve higher capacity than the existing hybrid D-A precoding algorithms with lower computational complexity.

Massive multiple input multiple output communication is now possible using millimeter wave frequency band. In this paper a transmit antenna selection algorithm is developed which satisfies a quality of service (QoS) for a given user. In order to achieve a particular level of QoS, the number of transmit antennas required is determined by remodeling it as a Knapsack Problem (KP). The smallest subset of antenna elements is found at the transmitter side to achieve the desired level of QoS using KP. Furthermore, we have compared our algorithm with the sorted and unsorted sequential selection algorithm (SSA). Our algorithm achieves similar performance as compared to SSA but with lower computational complexity than the sorted SSA. Moreover, the energy efficiency of our algorithm is similar to that of the sorted SSA but superior to unsorted SSA, as it is not sensitive to the arrangement of the antenna gains.

As a promising solution to offload cellular traffic, device-to-device (D2D) communication has been adopted to help disseminate contents. In this paper, the D2D offloading utility is maximized by proposing an optimal content pushing strategy based on the user interests and sharing willingness. Specifically, users are classified into groups by their interest probabilities and carry out D2D communications according to their sharing willingness. Although the formulated optimization problem is nonconvex, the optimal solution is obtained in closed-form by applying Karush-Kuhn-Tucker conditions. The theoretical and simulation results show that more contents should be pushed to the user group that is most willing to share, instead of the group that has the largest number of interested users.

The capacity of a millimetre-wave (mm-Wave) system can be improved by adopting a hybrid digital-to-analog (D-A) precoding system. Therefore, in this paper, an algorithm is proposed to maximise the capacity of the hybrid D-A mm-Wave system. This algorithm is a geometric approach which is based on the principle of Stiefel Manifold optimisation (SMO). Our proposed algorithm is compared with three known hybrid D-A precoding algorithms in the literature. The analytical and simulation results show that the proposed algorithm achieves higher capacity than the existing hybrid D-A precoding algorithms.

Device to Device (D2D) communication with content caching has recently been proposed as an exciting and innovative technology for next generation cellular networks. This paper presents a novel content caching and delivery method which allows multiple devices caching the same content and the content being sent via multiple devices to single device (MDSD) communication using D2D links to enhance user experience in terms of outage probability. A closed form expression of the outage probability is derived by considering how the content caching popularity affects achievable signal to interference plus noise ratio (SINR). The simulation and theoretical results show that as the popularity of the video increases, the outage probability of the system decreases substantially. On the other hand, the results show using MDSD enhances the SINR performance and decreases the outage probability of the system significantly.

Supporting high user density and improving millimeter- wave (mm-Wave) spectral-efficiency (SE) is imperative in 5G systems. Current hybrid digital-to-analog beamforming (D-A BF) base stations (BS) can only support a particular user per radio frequency (RF) chain, which severely restricts mm-Wave SE. In this paper a novel low-complexity selection combining (LC- SC) is proposed for supporting high user density for mm-Wave BS. When compared with the current state of the art hybrid D-A BF, simulations show that LC-SC can support high user density and attain higher SE.

Device-to-Device (D2D) communication has been proposed as a promising way to offload traffic from the cellular network. In this paper, with the joint impact of user preference and selfishness, the D2D assisted content dissemination process is investigated in order to maximize the offloading gain via D2D communications. An alternative group pushing optimization (AGPO) algorithm is proposed to solve the formulated nonconvex problem. In addition, for the special case of two groups, the optimal solution is derived in closed-form to help validate the algorithm. Finally, the simulation results show that the AGPO algorithm converges to the global optimum and has a much lower complexity compared to exhaustive search.

Device-to-device (D2D) assisted offloading heavily depends on the participation of human users. The content preference and sharing willingness of human users are two crucial factors in the D2D assisted offloading. In this paper, with consideration of these two factors, the optimal content pushing strategy is investigated by formulating an optimization problem to maximize the offloading gain measured by the offloaded traffic. Users are placed into groups according to their content preferences and share content with intergroup and intragroup users at different sharing probabilities. Although the optimization problem is nonconvex, the closed-form optimal solution for a special case is obtained, when the sharing probabilities for intergroup and intragroup users are the same. Furthermore, an alternative group optimization (AGO) algorithm is proposed to solve the general case of the optimization problem. Finally, simulation results are provided to demonstrate the offloading performance achieved by the optimal pushing strategy for the special case and AGO algorithm. An interesting conclusion drawn is that the group with the largest number of interested users is not necessarily given the highest pushing probability. It is more important to give high pushing probability to users with high sharing willingness.

Millimetre waves (mm-Waves) with massive multiple input and multiple output (MIMO) have the potential to fulfill fifth generation (5G) traffic demands. In this paper, a hybrid digital-to-analog (D-A) precoding system is investigated and a particle swarm optimisation (PSO) based joint D-A precoding optimisation algorithm is proposed. This algorithm maximises the capacity of the hybrid D-A mm-Wave massive MIMO system. The proposed algorithm is compared with three known hybrid D-A precoding algorithms. The analytical and simulation results show that the proposed algorithm achieves higher capacity than the existing hybrid D-A precoding algorithms.

Millimeter-wave (mm-Wave) systems with hybrid digital-to-analog beamforming (D-A BF) have the potential to fulfill 5G traffic demands. The capacity of mmWave systems is severely limited as each radio frequency (RF) transceiver chain in current base station (BS) architectures support only a particular user. In order to overcome this problem when high density of users are present, a new algorithm is proposed in this paper. This algorithm operates on the principle of selection combining (SC). This algorithm is compared with the state of the art hybrid D-A BF. The simulation results show that our proposed hybrid D-A BF using SC supports higher density of users per RF chain. Furthermore, our proposed algorithm achieves higher capacity than what is achieved by the current hybrid D-A BF systems.

Neighbour discovery is an important process in device-to-device (D2D) communications. In cellular networks, D2D discovery signals are multiplexed with cellular signals causing in-band emission interference (IEI). IEI degrades D2D user equipments (DUEs) discovery range and cellular user equipments (CUEs) throughput. In this paper, a new discovery method is proposed by applying power control strategy. In this method, DUEs are arranged into two groups depending on whether the received power of a reference signal sent from the based station (BS) to DUEs is larger than a given threshold. A high received reference signal at a DUE indicates strong IEI which may be caused by the DUE to the BS. Then, Group-1 contains DUEs which cause low IEI while Group-2 contains DUEs which cause severe IEI. A new strategy to mitigate IEI is proposed for Group-2. Firstly, CUEs send scheduling information in predefined blocks. Secondly, DUEs estimate the symbols which are orthogonal to CUE. This will assist DUEs to boost their discovery transmission power, reduce IEI and improve the discovery performance.

Content caching between multiple devices to single device (MD2SD) using device to device (D2D) link is studied in this paper. A general outage probability for video content delivery using the popularity and storage size of the user equipment (UE) is derived. This outage probability is modelled as a function of popularity of video, storage size, and signal to interference plus noise ratio (SINR). Our main contribution is a closed form expression and a tractable approximation. The simulation results show that as the popularity of the video increases, the outage probability of the system decreases. It is also analysed that increasing the storage space on the UE decreases the outage probability of the system.

In this letter, a joint detector for cooperative communication networks is proposed when the destination has limited hardware processing capability. The transmitter sends its symbols with the help of L relays. As the destination has limited hardware, only U out of L signals are processed and the energy of the remaining relays is lost. To solve this problem, a joint preprocessing based detector is proposed. This joint preprocessor based detector operate on the principles of minimizing the symbol error rate (SER). For a realistic assessment, pilot symbol aided channel estimation is incorporated for this proposed detector. From our simulations, it can be observed that our proposed detector achieves the same SER performance as that of the maximum likelihood (ML) detector with all participating relays. Additionally, our detector outperforms selection combining (SC), channel shortening (CS) scheme and reduced-rank techniques when using the same U. Our proposed scheme has low computational complexity.

In this paper, a new detector is proposed for an amplify-and-forward (AF) relaying system. The detector is designed to minimize the symbol-error-rate (SER) of the system. The SER surface is non-linear and may have multiple minimas, therefore, designing an SER detector for cooperative communications becomes an optimization problem. Evolutionary based algorithms have the capability to find the global minima, therefore, evolutionary algorithms such as particle swarm optimization (PSO) and differential evolution (DE) are exploited to solve this optimization problem. The performance of proposed detectors is compared with the conventional detectors such as maximum likelihood (ML) and minimum mean square error (MMSE) detector. In the simulation results, it can be observed that the SER performance of the proposed detectors is less than 2 dB away from the ML detector. Significant improvement in SER performance is also observed when comparing with the MMSE detector. The computational complexity of the proposed detector is much less than the ML and MMSE algorithms. Moreover, in contrast to ML and MMSE detectors, the computational complexity of the proposed detectors increases linearly with respect to the number of relays.

Multivariate generalized Gaussian density (MGGD) is used to approximate the multiple access interference (MAI) and additive white Gaussian noise in pulse-based ultrawide bandwidth (UWB) system. The MGGD probability density function (pdf) is shown to be a better approximation of a UWB system as compared to multivariate Gaussian, multivariate Laplacian and multivariate Gaussian-Laplacian mixture (GLM). The similarity between the simulated and the approximated pdf is measured with the help of modified Kullback-Leibler distance (KLD). It is also shown that MGGD has the smallest KLD as compared to Gaussian, Laplacian and GLM densities. A receiver based on the principles of minimum bit error rate is designed for the MGGD pdf. As the requirement is stringent, the adaptive implementation of the receiver is also carried out in this paper. Training sequence of the desired user is the only requirement when implementing the detector adaptively.

Efficient receiver designs for cooperative communication systems are becoming increasingly important. In previous work, cooperative networks communicated with the use of L relays. As the receiver is constrained, it can only process U out of L relays. Channel shortening and reduced-rank techniques were employed to design the preprocessing matrix. In this paper, a receiver structure is proposed which combines the joint iterative optimization (JIO) algorithm and our proposed threshold selection criteria. This receiver structure assists in determining the optimal Uopt. Furthermore, this receiver provides the freedom to choose U ≤ Uoptfor each frame depending upon the tolerable difference allowed for mean square error (MSE). Our study and simulation results show that by choosing an appropriate threshold, it is possible to gain in terms of complexity savings without affecting the BER performance of the system. Furthermore, in this paper the effect of channel estimation errors is investigated on the MSE performance of the amplify-and-forward (AF) cooperative relaying system.

The ever growing demand of higher data rates can now be addressed by exploiting cooperative diversity. This form of diversity has become a fundamental technique for achieving spatial diversity by exploiting the presence of idle users in the network. This has led to new challenges in terms of designing new protocols and detectors for cooperative communications. Among various amplify-and-forward (AF) protocols, the half duplex non-orthogonal amplify-and-forward (NAF) protocol is superior to other AF schemes in terms of error performance and capacity. However, this superiority is achieved at the cost of higher receiver complexity. Furthermore, in order to exploit the full diversity of the system an optimal precoder is required. In this paper, an optimal joint linear transceiver is proposed for the NAF protocol. This transceiver operates on the principles of minimum bit error rate (BER), and is referred as joint bit error rate (JBER) detector. The BER performance of JBER detector is superior to all the proposed linear detectors such as channel inversion, the maximal ratio combining, the biased maximum likelihood detectors, and the minimum mean square error. The proposed transceiver also outperforms previous precoders designed for the NAF protocol.

In this paper, we propose optimal linear detectors for non-orthogonal amplify-and-forward cooperative protocol when considering a single-relay scenario. Two types of detectors are proposed based on the principles of minimum mean square error (MMSE) and minimum bit error rate (MBER). The MMSE detector minimizes the mean square error, while the MBER minimizes the system bit error rate (BER). Both detectors exhibit excellent BER performance with relatively low complexity as compared to the maximal likelihood (ML) detector. The BER performance of both detectors is superior to the channel inversion, the maximal ratio combining, and the biased ML detectors.

In this letter, a new detector is proposed for amplify-and-forward (AF) relaying system when communicating with the assistance of$L$relays. The major goal of this detector is to improve the bit error rate (BER) performance of the receiver. The probability density function is estimated with the help of kernel density technique. A generalized Gaussian kernel is proposed. This new kernel provides more flexibility and encompasses Gaussian and uniform kernels as special cases. The optimal window width of the kernel is calculated. Simulations results show that a gain of more than 1 dB can be achieved in terms of BER performance as compared to the minimum mean square error (MMSE) receiver when communicating over Rayleigh fading channels.

In this paper, a new detector is being proposed for amplify-and-forward (AF) relaying system when communicating with the assistance of L number of relays. The major goal of this detector is to improve the bit error rate (BER) performance of the system. The complexity of the system is further reduced by implementing this detector adaptively. The proposed detector is free from channel estimation. Our results demonstrate that the proposed detector is capable of achieving a gain of more than 1-dB at a BER of 10-5as compared to the conventional minimum mean square error detector when communicating over a correlated Rayleigh fading channel.

This paper investigates and compares the performance of wireless sensor networks (WSN) when sensors operate on the principles of cooperative communications. We consider a scenario where the source transmits signals to the destination with the help of L sensors. As the destination has the capacity of processing only U out of these L signals, U strongest signals are selected while the remaining (L - U) signals are suppressed. A preprocessing block similar to channel-shortening (CS) is proposed in this contribution. However, this preprocessing block employs rank-reduction technique instead of CS. This detector operates on the principles of principal components (PC). From our simulations it can be observed that this detector is capable of achieving a similar bit error rate (BER) performance as the full-rank MMSE detector with significantly lower complexity. It outperforms the CS-based detector in terms of BER performance when using fixed amplification factor. However, for variable gain amplification factor a tradeoff between the diversity gain and the receiver complexity can be observed. From the simulations it can be concluded that the BER performance of the PC-based detector when using variable gain amplification factor are better than that of the CS-based detector for lower signal to noise ratio.

In this paper a range of reduced-rank adaptive multiuser detectors (MUDs) are proposed and investigated for the hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. The adaptive MUDs are operated based on the recursive least square (RLS) principles. Three types of reduced-rank techniques are investigated, which are the principal component (PC), cross-spectral metric (CSM) and Taylor polynomial approximation (TPA). These reduced-rank adaptive techniques are beneficial to achieving low-complexity, high spectral-efficiency and robust detection in hybrid DSTH UWB systems. In this contribution bit error rate (BER) performance of the hybrid DS-TH UWB systems using proposed reduced-rank adaptive MUDs is investigated by simulations, when communicating over UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Our simulation results show that, given a sufficiently high rank of the detection subspace, the reduced-rank adaptive MUDs are capable of achieving a similar BER performance as that of the full-rank ideal minimum mean-square error MUD (MMSE-MUD) but with significantly lower detection complexity. Furthermore, the TPA-based reduced-rank adaptive MUD is capable of yielding a better BER performance than the PC- or CSM-based reduced-rank adaptive MUD, when the same but relatively low rank detection subspace is assumed.

In this paper we consider the low-complexity detection in hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. A reduced-rank adaptive LBER detector is proposed, which is operated in the least bit error-rate (LBER) principles within a detection subspace obtained with the aid of the principal component analysis (PCA)-assisted reduced-rank technique. Our reduced-rank adaptive LBER detector is free from channel estimation and does not require the knowledge about the number of resolvable multipaths as well as that about the multipaths' strength. In this paper the bit error-rate (BER) performance of the hybrid DS-TH UWB system is investigated, when communicating over the UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Our study and simulation results show that this reduced-rank adaptive LBER detector constitutes a feasible detection scheme for deployment in practical pulse-based UWB systems.

In this contribution reduced-rank adaptive minimum mean- square error multiuser detector (MMSE-MUD) is proposed and investigated for the hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. The adaptive MMSE-MUD is operated based on the normalised least mean-square (NLMS) principles associated with using Taylor polynomial approximation (TPA)-assisted reduced-rank technique. It can be shown that the reduced-rank adaptive technique is beneficial to achieving low-complexity, high convergence speed and robust detection in hybrid DS-TH UWB systems. In this contribution bit-error-rate (BER) performance of the hybrid DS-TH UWB systems using proposed reduced- rank adaptive MMSE-MUD is investigated, when communicating over UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Our simulation results show that the TPA-assisted reduced-rank adaptive MMSE-MUD is capable of achieving a similar BER performance as that of the full-rank adaptive MMSE-MUD but with significantly lower detection complexity.

In this contribution an adaptive detection scheme based on least mean square (LMS) principles is proposed and investigated in the context of the hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. The bit-error-rate (BER) performance of the hybrid DS-TH UWB system is investigated when communicating over the UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Furthermore, since both the pure DS-UWB and pure TH-UWB constitute special examples of the hybrid DS-TH UWB, their BER performance is also investigated in this contribution for the sake of comparison with that of the hybrid DS-TH UWB. Our study and simulation results show that the LMS-aided adaptive detection can be a feasible detection scheme for deployment in practical DS-, TH- or hybrid DS-TH UWB systems. It can be shown that, with the aid of a training sequence of reasonable length, the considered UWB schemes are capable of achieving a BER performance which is close to that achieved by the minimum mean-square error (MMSE) detector with perfect channel knowledge.

In this contribution decision-directed adaptive detection scheme based on normalised least mean-square (DD/NLMS) principles is proposed and investigated for the hybrid direct- sequence time-hopping ultrawide bandwidth (DS-TH UWB) system. The bit-error-rate (BER) performance of the hybrid DS-TH UWB system is investigated when communicating over the UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Since both the pure DS-UWB and pure TH-UWB constitute special examples of the hybrid DS-TH UWB, their BER performance is also investigated in this contribution for sake of comparison with that of the hybrid DS-TH UWB. Our study and simulation results show that the DD/NLMS-aided adaptive detection constitutes a feasible detection scheme for practical DS-, TH- or hybrid DS-TH UWB systems. With the aid of a training sequence of reasonable length, our study shows that the considered UWB schemes are capable of achieving the BER performance that is close to that achieved by the minimum mean-square error (MMSE) detector with perfect channel knowledge. Furthermore, the DD adaptive techniques may be employed by UWB systems in order to improve their spectral-efficiency.

This paper investigates and compares the performance of hybrid direct-sequence time-hopping (DS-TH) ultrawide bandwidth (UWB) systems using full-rank and various reduced-rank detections when minimum mean-square error (MMSE) principles are applied, while communicating over Nakagami-m fading channels. In addition to the full- rank MMSE detection, three classes of reduced-rank MMSE techniques are investigated, which are derived based on the principles of principal components (PC), cross-spectral metric (CSM) and Taylor polynomial approximation (TPA), respectively. Our study and simulation results show that the reduced-rank techniques constitute a family of promising detection techniques for UWB systems, which are capable of achieving similar bit error rate (BER) performance as the full-rank detection, while with a detection complexity that is significantly lower than that of the full-rank detection.

This paper presents a novel ultrawideband (UWB), direct sequence code division multiple access (DS-CDMA) aided system designed for the IEEE 802.15.3a UWB channel specifications. Substantial performance improvements can be attained by serially concatenated channel encoding combined with a unity rate code (URC). We compare the performance of the iterative aided decoding correlation (Corr) and minimum mean square error (MMSE) detectors exchanging extrinsic information between the URC's decoder as well as the outer recursive systematic convolutional (RSC) code's decoder. Moreover, the iterative decoding convergence analysis of the proposed system is carried out with the aid of extrinsic information transfer (EXIT) charts. As expected, the iteratively decoded fully-loaded system employing MMSE detection outperforms its counterpart employing the equivalent Corr detection. Explicitly, UWB DS-CDMA using the MMSE detector attains a BER of 10-5at Eb/No=2 dB when supporting U=32 users employing i=12 decoding iterations, while the same system using the Corr detector operates at BER-10-1.

This paper presents a novel analysis on the decoding convergence of Time Hopping (TH) and Direct Sequence (DS) Code-Division Multiple-Access (CDMA) Ultrawide Bandwidth (UWB) systems when communicating over multipath Nakagami channels. The analysis is based on the Extrinsic Information Transfer (EXIT) chart where the UWB systems are serially concatenated pulse-position modulated TH and code-synchronous DS-CDMA. It is shown from an EXIT chart analysis that the multipath diversity can yield a larger area under the EXIT curve of the inner detector. This area is related to the achievable rate of the system and it can be exploited with the aid of iterative detection. Simulation results of the iteratively detected TH and DS-CDMA UWB schemes verify the EXIT chart analysis.

This paper investigates and compares the performance of various ultrawide bandwidth (UWB) systems when communicating over Nakagami-m fading channels. Specifically, the direct-sequence (DS), time-hopping (TH) and hybrid direct-sequence time-hopping (DS-TH) UWB systems are considered. The performance of these UWB systems is studied, when using the conventional single-user correlation detector or the minimum mean-square error (MMSE) multiuser detector. Our simulation results show that the hybrid DS-TH UWB system may outperform a corresponding pure TH-UWB or pure DS-UWB system in terms of the achievable error performance. Given the total spreading gain of the hybrid DS-TH UWB system, there is an optimal setting of the TH spreading factor and DS spreading factor, which results in the best error performance.