Integrated Sensing and Communication (ISAC) is one new technology under development for Sixth Generation (6G) systems. This paper focuses on creating a simulation pipeline for dynamic vehicular traffic scenarios and a novel approach to reducing wireless communication overhead with a LiDAR-based system. The simulation pipeline can be used to generate data sets for numerous research. Additionally, developed error model for vehicle detection algorithms can be used to identify LiDAR performance with respect to different parameters like LiDAR height, range, and laser point density. A periodic beam index map is developed by capturing antenna azimuth and elevation angles which denote maximum Reference Signal Receive Power (RSRP) for a simulated receiver grid on the road and classifying areas using Support Vector Machine (SVM) algorithm to reduce the number of Synchronization Signal Blocks (SSBs) that needed to send in Vehicle to Infrastructure (V2I) communication.

The mmWave communication up to 71 GHz is already specified in 3rd generation partnership project (3GPP)5G New Radio (NR), and communication in sub-THz bands is being studied for 6G widely in the academia and industry. Operation with very narrow beamwidths and much higher bandwidths in contrast to Frequency Range 1 (sub-6 GHz) can cater to the high data rate requirements at the expense of extra signal processing burden to overcome the unfavourable conditions such as high attenuation and scattering in the presence of obstacles. Such severe signal power attenuation caused by an obstacle may degrade the network performance due to link failures occurring as a result of line-of-sight (LoS) to non-LoS (NLoS) transitions. These limitations raise the necessity of a sensing system to collect situational awareness data to assist the wireless communication network. This work proposes a method to improve the LoS detection and user localization accuracy using multiple light detection and ranging (LiDAR) sensors co-located in access points (APs). We also propose an approach to predict the LoS transitions based on static LiDAR maps and the proposed method detected the LoS transition 400ms before its occurrence.

5G New Radio (NR) mmWave operates with narrow beams. Beam-based connections require careful management of beams to ensure a reliable connection, specially when the user has mobility. 5G NR defines beam management procedures to achieve this, at the expense of periodic reporting with increased overheads and resource usage. Concurrently, recent interest in sensing for assisting wireless systems provides an opportunity to extract situational awareness information which can aid in proactive decisions for the network. In this work, we utilize an infrastructure-mounted light detection and ranging (LiDAR) sensor system simultaneously operating with the wireless system to predict future beam decisions. A recurrent neural network (RNN) based learning model is proposed for the beam prediction, employing tracking information of users facilitated by the LiDARs and beam sequence information from the wireless system. Furthermore, a method for predictive beam management with increased periodicity of the reporting mechanism and aperiodic reporting is analyzed. The results for the considered scenario reveal 86.8% of the resources can be saved compared to the conventional beam reporting procedure, while achieving an 88.7% accuracy for optimal beam decisions.

Transmission power variance constrained power allocation in single carrier multiuser (MU) single-input multiple-output (SIMO) systems with iterative frequency domain (FD) soft cancelation (SC) minimum mean squared error (MMSE) equalization is considered in this paper. It is known in the literature that peak to average power ratio (PAPR) at the transmitter can be decreased by reducing the variance of the transmit power. In this paper, we derive a power variance constraint to statistically control the PAPR. This constraint is plugged into a convergence constrained power allocation (CCPA) problem and successive convex approximation (SCA) approach via series of geometric programs (GP) is developed. Numerical results are presented in the form of complementary cumulative distribution functions (CCDFs) to demonstrate the effectiveness of the proposed method.

Peak to average power ratio (PAPR) constrained power allocation in single carrier multiuser (MU) single-input multiple-output (SIMO) systems with iterative frequency domain (FD) soft cancelation (SC) minimum mean squared error (MMSE) equalization is considered in this paper. To obtain full benefit of the iterative receiver, its convergence properties need to be taken into account also at the transmitter side. In this paper, we extend the existing results on the area of convergence constrained power allocation (CCPA) to consider the instantaneous PAPR at the transmit antenna of each user. In other words, we will introduce a constraint that PAPR cannot exceed a predetermined threshold. By adding the aforementioned constraint into the CCPA optimization framework, the power efficiency of a power amplifier (PA) can be significantly enhanced by enabling it to operate on its linear operation range. Hence, PAPR constraint is especially beneficial for power limited cell-edge users. In this paper, we will derive the instantaneous PAPR constraint as a function of transmit power allocation. Furthermore, successive convex approximation is derived for the PAPR constrained problem. Numerical results show that the proposed method can achieve the objectives described above.

This paper presents a cooperative decentralized scheme for adjusting the Uplink (UL)-Downlink (DL) configuration of a Small Cell Network (SCN) with a TDD air interface. The goal of the cooperative decentralized scheme is to make a more efficient use of common wireless resources, selecting convenient TDD-frame configurations to maximize a sum utility function that takes into account both individual traffic demands and actual interference coupling situations. The cooperative decentralized scheme for UL/DL adaptation can be executed locally at each Base Station (BS), and relies solely on the exchange of low-rate signaling information among neighboring cells. Based on observed performance improvements, we conclude that cooperative decentralized schemes are a viable option for flexible-TDD implementation in SCN environments, particularly in presence of cells with strong interference coupling and low-rate signaling capabilities.

An iterative receiver for a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of the a posteriori probability (APP) algorithm, the repeat-accumulate (RA) decoder, and the least-squares (LS) channel estimator. An obvious problem, with more than two blocks in an iterative receiver, is to find the optimal activation schedule of the different blocks. This paper proposes to use extrinsic information transfer (EXIT) charts to characterize the behavior of the receiver blocks and find out the optimal activation schedule for them. A semi-analytical expression of the EXIT function is derived for the decision directed LS channel estimator. An algorithm is proposed to generate the EXIT function of the APP algorithm as a function of channel estimate mutual information (MI). Surface fitting is used to get closed form expressions for the EXIT functions of the APP algorithm and the RA decoder. Trellis search based algorithms are shown to find the convergence with the lowest possible complexity using the EXIT charts. With the proposed concept, the activation scheduling can be adapted to prevailing channel circumstances and unnecessary iterations will be avoided.

This paper addresses the problem of power allocation for single carrier point-to-point multiple input multiple output (MIMO) systems with iterative frequency-domain (FD) soft cancellation (SC) minimum mean squared error (MMSE) equalization. Two novel heuristic power allocation methods are proposed. The proposed methods explicitly take into account the convergence properties of the iterative equalizer while transmission power is minimized. The proposed heuristic schemes are based on, convergence constraint power allocation (CCPA), technique that decouples the spatial interference between streams using singular value decomposition (SVD), and minimize the transmission power while achieving the target mutual information for each stream after iterations at the receiver side. The proposed heuristic transmission schemes are inspired by well-known greedy algorithm resulting in a simple and efficient solutions to the power allocation problem. Numerical results show that the proposed heuristic schemes can achieve close to optimal performance in the terms of equalizer convergence as well as the total transmission power.

Relays can be used between the source and the destination to improve network coverage or reliability. In the relay based distributed space-time block-coded (DSTBC) single-carrier (SC) transmission scheme, asynchronism in time and frequency causes degradation in system performance because of the interblock interference, non-coherent combining and multiuser interference. The simultaneous presence of timing offset and carrier frequency offset also destroy the orthogonal structure of DSTBC. In this paper, we study the combined effect of timing offset and carrier frequency offset and propose a two stage equalization technique for this system at the destination terminal. Technique is based on interference cancellation and cyclic prefix reconstruction. The proposed equalization technique maintains the orthogonal structure of DSTBC and allows the use of low complexity one-tap frequency-domain equalizer. The technique significantly alleviates the effect of time offsets and frequency offsets at the destination without increasing the complexity of the receiver or disturbing the 3rd generation partnership project-long term evolution (3GPP LTE) uplink frame structure or the data rate over frequency selective channels.

An iterative receiver for a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of the a posteriori probability (APP) algorithm, the repeat-accumulate (RA) decoder, and the least-squares (LS) channel estimator. An obvious problem, with more than two blocks in an iterative receiver, is to find the optimal activation schedule of the different blocks. This paper proposes to use extrinsic information transfer (EXIT) charts to characterize the behavior of the receiver blocks and find out the optimal activation schedule for them. An analytical expression of the EXIT function is derived for the LS channel estimator. An algorithm is proposed to generate the EXIT function of the APP algorithm as a function of channel estimate mutual information (MI). Surface fitting is used to get closed form expressions for the EXIT functions of the APP algorithm and the RA decoder. A trellis search based algorithm is shown to find the convergence with the lowest possible complexity using the EXIT charts. With the proposed concept, the activation scheduling can be adapted to prevailing channel circumstances and unnecessary iterations will be avoided.

This paper proposes a technique to compress the data with equal length code words. A novel source coding technique, multiple label mapping (MLM), is introduced. With MLM it is possible to produce a source code which uses equal length code words. Moreover, it is shown that with the MLM technique, it is possible to achieve near limit compression without using variable length coding (VLC). However this requires that the source probability grouping is performed so that after MLM each code word has almost equal appearance probability, and that full a priori feedback is available. Numerical results demonstrate proper operability of the proposed system.

This paper proposes a novel linear precoder design technique for single carrier single-user multiple input multiple output (MIMO) systems with frequency-domain (FD) soft cancellation (SC) minimum mean squared error (MMSE) iterative equalization where the convergence properties of the equalizer are taken into account. The proposed precoder design technique, convergence constrained precoding (CCP), minimizes the transmission power while it achieves the target mutual information for each stream after the iterations at the receiver side. We show that the optimality criterion for the proposed design can be formulated as a convex optimization problem. The results demonstrate that our proposed technique outperforms the existing linear precoding techniques by ensuring the convergence with a reduced transmission power. Furthermore, we show that with CCP we can adjust transmission according to convergence properties of the iterative equalizer in a more flexible way than, e.g., minimum sum mean squared error (MinSumMSE) and maximum information rate (MaxRate) precoding.

Relays are used between the source and the destination to improve network coverage and reliability in cooperative relay system. Imperfect time delay synchronization at the receiver arises because of time difference in propagation of the signals from the source and the relay to the receiver. The performance degrades due to interference from the previous block and the defective channel matrix. In this paper, we study the effect of time delay asynchronism and propose to use interblock interference cancellation and cyclic prefix reconstruction techniques on amplify and forward relay based distributed space-time block coding for single carrier-frequency domain equalization system, which removes the unwanted interference part and reconstructs the defective channel matrix to circulant one. The proposed method significantly reduces the effect of time delay asynchronism at the receiver without disturbing the 3rd generation partnership project-long term evolution (3GPP LTE) uplink frame structure, data rate and increasing the complexity over frequency selective channels.

In this the paper, impact of minimum mean squared error (MMSE) based linear precoding on the convergence of iterative multiuser detector in multiuser multiple input multiple output (MIMO) uplink single carrier communications is studied. The influence of linear precoding on iterative MMSE based multiuser detector is investigated via the multi-dimensional EXIT analysis. It is shown that the use of the linear precoding enhances the separability of the EXIT planes of the simultaneous streams over without precoding; This invokes the idea that different code rate be allocated to the each transmitted streams at the transmitter. Especially, in the case of multiuser communication precoding has significant roles in the convergence property of iterative detector.

In this paper, we address the problem of multiple-input multiple-output (MIMO) spatial multiplexing (SM) systems in the presence of antenna fading correlation. It is well known that severe spatial correlations present at the transmitter and/or receiver can significantly compromise the performance of existing SM systems. Recent results showed that joint-over-antenna (JA) iterative detection schemes can improve the performance of SM systems in correlated channels as compared to schemes that detected the signals on an antenna-by-antenna basis. We extend this idea in this paper by incorporating a so-called antenna doping (AD) scheme into the SM system, in order to further counteract the detrimental effects of spatial correlation. Through simulations, we show that AD can improve the performance by 3-4 dB in severe spatial correlation as compared to non-doping systems. This improvement is explained with the aid of extrinsic information transfer (EXIT) charts, which illustrate the convergence behavior of the JA iterative detection with and without AD.

Multiuser multiple-input-multiple-output (MIMO) wireless systems have great potential in improving information rate, diversity and resistance to against interference. The primary objective of this paper is to derive for broadband signaling a new iterative frequency domain (FD) multiuser MIMO signal detection technique for joint-over-antenna (JA) detection. The proposed detector is based on soft-cancellation and minimum mean square error (MMSE) filtering, followed by maximum a posteriori probability (MAP) detector to detect several of each users transmit antennas. The purpose of jointly detecting several transmit antennas is to preserve the degrees of freedom (DoF) for MMSE. Computational complexities with FD and its time domain (TD) counterpart are evaluated in this paper, and it is shown that FD requires significantly lower complexity than TD. Numerical results show that JA significantly outperforms the receiver that detects transmit antenna signals antenna-by- antenna (AA). The proposed iterative FD JA technique achieves larger performance gains compared to AA when the total number of transmit antennas is larger than the number of receiver antennas, as well as in the presence of spatial correlation.