This is Part II of the two-part Special Issue (SI) on 5G/6G Precise Positioning on Cooperative Intelligent Transportation Systems (C-ITS) and Connected Automated Vehicles (CAV). The SI aims at bringing together contribution from both academia and industry to highlight the recent progress in various aspects of positioning systems. We have included 30 original contributions in this two-parts SI. We kindly refer readers to Part I of this SI for a comprehensive overview written by the Guest Editorial Team.

Quantum Internet (QI) is a system of interconnected quantum computers able to exchange information encoded in the so called quantum bits (qubits). Differently from the classical counterpart, qubits benefit from a manifold properties guaranteed by quantum mechanics, such as superposition and entanglement. Despite the fact that quantum networks bring significant advantages, several phenomena can negatively impact the overall system, potentially hindering communication. In order to evaluate the network performance, a comprehensive probability expression is derived in this work to ultimately determine how many qubits are expected to be successfully received by nodes. On this basis, a Mixed-Integer Non-Linear Programming (MINLP) problem is formulated to fairly maximize the qubits exchanged between node pairs and jointly optimize (i) the position of the quantum source, and (ii) the entanglement distribution plan. To cope with the non-convexity of the problem, an iterative optimization algorithm, leveraging Block Coordinate Descendent (BCD) and Successive Convex Approximation (SCA) techniques, is proposed. A thorough simulation campaign is conducted to corroborate the theoretical findings. Numerical results demonstrates, under different parameter setups, that the proposed algorithm provides superior performance with respect to a baseline approach.

This paper focuses on trigger-based (TB) random access (RA) strategies for a multiple-packet reception channel with channel capability$M$($M$-MPR channel), where up to$M$packets can be received simultaneously, while more than$M$concurrent packet transmissions result in collisions and are considered lost. We model the contention for the TB MPR framework and derive the optimal RA strategies that maximize two metrics:i)the normalized saturation throughput, andii)the number of stations successfully occupying the MPR channel within each access round. We generalize the$p$-persistent carrier sense multiple access (CSMA) by enabling it to explore both the MPR dimension and the time dimension to adapt the access probabilities. We also propose suboptimal strategies to reduce the complexity, customized for the considered TB framework. Comprehensive performance evaluations and comparisons with respect to a wide range of system parameters and metrics are provided.

We consider a generalized version of Carrier-Sense Multiple Access (CSMA), where the contention window size is a constant and the back-off probability distribution can be varied. We address the optimization of a weighted throughput metric, identifying the optimal back-off Probability Density Function (PDF). We give a simple fixed-point algorithm to compute the optimal PDF and prove that the solution is unique. The weighted throughput definition caters for aspects other than the mere channel utilization. It reduces to plain utilization (normalized throughput) when all weights are equal to 1. We also reconnect our result to the classic analysis of saturated non-persistent CSMA, as introduced in the seminal paper by Tobagi and Kleinrock, proving formally that the modeling assumptions of that work, that lead to a Geometric PDF of back-off, actually correspond to the throughput-optimal choice, provided that the ratio of the Geometric PDF is suitably chosen.

The advancement of connected intelligent transportation systems (C-ITS) and connected automated vehicles (CAV) has brought about a growing need for precise positioning solutions. Positioning technologies play a crucial role in many use cases such as emergency call systems, disaster rescue operations, automated robotics, and more. To ensure the availability, reliability, and quality of location systems both indoors and outdoors, the evolution of cellular technology, particularly in the form of 5G/6G networks, promises to provide a new pathway towards achieving high precision positioning.

Many CSMA based MACs can abruptly degrade their performance when the optimized design parameters do not fit with the considered scenarios. The main issue is the lack of optimal adaptation of the MAC strategies to dynamic network conditions. Novel approaches based on learning, deep-learning, nature-inspired learning are gaining interest for their robustness to dynamic network conditions. In this paper, a simple adaptive MAC strategy based on the Q-learning has been proposed. Our proposal, called Q-CSMA, is able to dynamically tune the contention probability in a slotted CSMA to decrease the number of collisions, also reducing the packet latency. Q-CSMA has been compared with optimal p-persistent CSMA (p-pers-CSMA/ p*) and a sift-based CSMA (sift-CSMA).

A novel carrier sense multiple access strategy with collision avoidance (CSMA/CA) balancing contention probability and channel access time is proposed. The approach can be applied to any context where the computational simplicity of the MAC must be preferred to the complexity of the channel access strategy. Our MAC, called Delay-Collision CSMA (DC-CSMA), is a slotted nonpersistent CSMA/CA with nonuniform contention probability distribution, designed to reduce at the same time latency of contenders and preserve a high successful access probability. An utility function aiming at equalizing the effects of these two performance metrics is introduced, and the related theoretical properties and optimal distribution are derived. DC-CSMA is insensitive to the number of contenders and very robust with respect to contention window size, packet length, and impairments such as frame synchronization errors and hidden terminals, and it does not require any adaptive tuning to optimize its performance. Current technologies such as WSN, RFID, IoT devices can benefit from such a simple access technique. The numerical evaluation has been led out considering latency, successful probability and throughput, and DC-CSMA has been compared with other classical strategies such as CSMA with uniformly distributed contention probability, CSMA/$p^{\ast}$and Sift distribution.

Providing real-time cloud services to Vehicular Clients (VCs) must cope with delay and delay-jitter issues. Fog computing is an emerging paradigm that aims at distributing small-size self-powered data centers (e.g., Fog nodes) between remote Clouds and VCs, in order to deliver data-dissemination real-time services to the connected VCs. Motivated by these considerations, in this paper, we propose and test an energy-efficient adaptive resource scheduler for Networked Fog Centers (NetFCs). They operate at the edge of the vehicular network and are connected to the served VCs through Infrastructure-to-Vehicular (I2V) TCP/IP-based single-hop mobile links. The goal is to exploit the locally measured states of the TCP/IP connections, in order to maximize the overall communication-plus-computing energy efficiency, while meeting the application-induced hard QoS requirements on the minimum transmission rates, maximum delays and delay-jitters. The resulting energy-efficient scheduler jointly performs: (i) admission control of the input traffic to be processed by the NetFCs; (ii) minimum-energy dispatching of the admitted traffic; (iii) adaptive reconfiguration and consolidation of the Virtual Machines (VMs) hosted by the NetFCs; and, (iv) adaptive control of the traffic injected into the TCP/IP mobile connections. The salient features of the proposed scheduler are that: (i) it is adaptive and admits distributed and scalable implementation; and, (ii) it is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rates of the traffic delivered to the vehicular clients, instantaneous rate-jitters and total processing delays. Actual performance of the proposed scheduler in the presence of: (i) client mobility; (ii) wireless fading; and, (iii) reconfiguration and consolidation costs of the underlying NetFCs, is numerically tested and compared against the corresponding ones of some state-of-the-art schedulers, under both synthetically generated and measured real-world workload traces.

In this paper, a primary-secondary resource-management controller on Vehicular Networks is designed and tested. We cast the resource-management problem into a suitable constrained stochastic Network Utility Maximization problem and derive the optimal cognitive resource management controller, which dynamically allocates the access time-windows. We provide the optimal steady-state memoryless controllers under hard and soft primary-secondary collision constraints, showing as the hard controller does not present any optimality gap in the average utility with respect to the soft one, while, on the contrary, it is able to make the outage-probability vanishing. Then we generalize the framework integrating the controllers with different data fusion techniques, and test the controller behaviour in a non-stationary application scenario. Finally we provide the optimal steady-state hard controller with memory and compare it with the memoryless one.

In this paper, we design and test a full distributed and scalable resource-management scheduler for Vehicular Real-Time applications. We dynamically allocate the access time window (at the RoadSide Units) and the access rate and traffic flows (at the Vehicular Clients) under hard reliability collision constraints. We provide the optimal memoryless scheduler for network utility maximization, showing as it presents no loss in the network average utility with respect to not real-time soft reliability schedulers. Finally, the proposed scheduler exploits an ad-hoc designed soft-input/soft-output data fusion algorithm, able to supply in real-time reliable context-information, even in the presence of fading-affected and intermittent vehicular-to-infrastructure connectivity.

We design and test a distributed and adaptive resource management controller in Vehicular Access Networks, allowing energy and computing-limited car smart phones to opportunistically accede to a spectral-limited wireless backbone. We cast the resource management problem into a suitable constrained stochastic Network Utility Maximization problem and derive the optimal cognitive resource management controller, which dynamically allocates the access time-windows at the serving Roadside Units (i.e., the primary users) and the access rates and traffic flows at the served Vehicular Clients (i.e., the secondary users), allowing hard reliability guarantees to Roadside Units. We validated the controller performances in real-word application scenarios.

This paper focuses on the QoS-constrained jointly optimal adaptive distributed source coding, channel coding, network coding and power control for Co-Channel Interference (CCI)-limited wireless multiple class multicast networks, such as, for example, Wireless Sensor Networks (WSNs). The goal is to allocate the available system-wide resources by jointly performing Loss-Less Distributed Source Coding (LLDSC) and Intra-Session Network Coding (ISNC), while leveraging channel coding and power control for CCI-mitigation. Due to the presence of CCI, the resulting cross-layer optimization problem is inherently nonconvex. Hence, we develop a distributed, iterative and asynchronous algorithm for the optimal adaptive QoS management of the available bandwidth/power/flow resources. Actual performance and adaptive capability of the proposed resource management algorithm in the presence of: i) abrupt changes of the statistics of the source flows; ii) failures of the interior network nodes; and, iii) fast fading, are numerically tested.

In this paper, we focus on the quality-of-service (QoS)-constrained jointly optimal congestion control, network coding, and adaptive distributed power control for connectionless wireless networks affected by multiple access interference (MAI). The goal is to manage the available network resources, so as to support multiple multicast sessions with QoS requirements when intrasession network coding (NC) is allowed. To cope with the nonconvex nature of the resulting cross-layer optimization problem, we propose a two-level decomposition that provides the means to attain the optimal solution through suitable relaxed convex versions of its comprising subproblems. Sufficient conditions for the equivalence of the primary nonconvex problem and its related convex version are derived, occurrence of such conditions investigated, and performance with respect to conventional routing-based layered solutions analyzed. Moreover, we develop a distributed algorithm to compute the actual solution of the resource allocation problem that quickly adapts to network time-evolutions. Performance of this algorithm and its adaptivity are evaluated in the presence of varying network/fading conditions and noisy measurements.

Emerging media overlay networks for wireless applications aim at delivering Variable Bit Rate (VBR) encoded media contents to nomadic end users by exploiting the (fading-impaired and time-varying) access capacity offered by the "last-hop” wireless channel. In this application scenario, a still open question concerns the closed-form design of control policies that maximize the average throughput sent over the wireless last hop, under constraints on the maximum connection bandwidth available at the Application (APP) layer, the queue capacity available at the Data Link (DL) layer, and the average and peak energies sustained by the Physical (PHY) layer. The approach we follow relies on the maximization on a per-slot basis of the throughput averaged over the fading statistic and conditioned on the queue state, without resorting to cumbersome iterative algorithms. The resulting optimal controller operates in a cross-layer fashion that involves the APP, DL, and PHY layers of the underlying protocol stack. Finally, we develop the operating conditions allowing the proposed controller also to maximize the unconditional average throughput (i.e., the throughput averaged over both queue and channel-state statistics). The carried out numerical tests give insight into the connection bandwidth-versus-queue delay trade-off achieved by the optimal controller.

Traffic Engineering application to the cross-layer design of Multiple Access Interference (MAI)-affected powerlimited wireless networks, when Quality of Service constraints are also present, leads to deal with nonconvex resource allocation problems. Although several manageable-complexity solutions have been proposed, they are based on specific capacity functions and, generally, fail to provide reliable results in low-SINR (Signal to Interference plus Noise Ratio) scenarios. We develop a two-level decomposition that is able to find the optimal solution of a wide nonconvex cross-layer problem, which combines user utility, flow control, QoS multipath routing,Medium Access Control (MAC) design and power control, by means of a suitable relaxed convex version of its comprising flow control and power-allocation sub-problems. Sufficient conditions for the equivalence of the primary (nonconvex) problem and its related (convex) version are provided. Moreover, we develop a distributed, iterative, asynchronous algorithm for computing the solution of the overall nonconvex resource allocation problem, that is able to (quickly) self-adapt to possible network time evolutions (as, for example, node failure events) and, most importantly, that may be implemented on top of connectionless networking platforms. Actual performance of the overall proposed solution and its robustness against node-failure events are numerically tested and compared with the corresponding ones of Destination Sequenced Distance Vector-based single-path routing algorithms.

The interference induced by UWB communication on systems operating in the frequency range between 0 and 10.6 GHz is the main reason why the essential role in these systems' design is played by the pulse shape selection. That's why an accurate shaping choice can lead to avoid severe performance reduction and to guard systems coexistence. To this end, FCC (and ETSI in the near future) gave strict indications about the spectral limits to be respected, so as to define, as the purpose of UWB systems realization, the compliance with this spectral mask. The, widely used, choice of Gaussian-like pulses is, however, largely suboptimal from a power emission point of view since they are unable to maximize the signal-to-noise ratio (SNR). Goal of this contribution is to achieve a good compromise, in a cognitive way, between spectral emission, rate and synchronization errors robustness, via a modified version of the Parks-McClellan method, considering channel impairments due to its frequency-selective nature, to the inter-pulse interference and in-band interference.

Emerging media overlay networks for wireless applications aim at delivering Variable-Bit-Rate (VBR) encoded media contents to nomadic end-users by exploiting the (fading-impaired and time-varying) access capacity offered by the "last-hop" wireless channel. In this application scenario, a still open question concerns the design of control policies maximizing the average throughput over the wireless last-hop, under constraints on the maximum connection bandwidth allowed at the Application (APP) layer, the queue-capacity available at the data-link (DL) layer, and the average and peak transmit energies sustained by the Physical (PHY) layer. The main feature of the approach we follow relies on the maximization (on a per-slot basis) of the throughput averaged over the fading statistics and conditioned on the queue-state. The resulting optimal controller is rate-based and operates in a cross-layer fashion that involves the APP, DL and PHY layers of the underlying protocol stack. This means that the proposed controller dynamically allocates connection bandwidth at the APP Layer, throughput at the DL layer and transmit energy at the PHY layer by basing on both current queue and channel states. The carried out numerical tests give insights about the connection bandwidth-vs.-queue delay tradeoff attained by optimal controller.

Wireless mesh networks (WMNs) are envisioned for extending the coverage of WLANs by interconnecting the underlying access points (APs) via high-capacity wireless backbones. Since the ultimate goal of a WMN is to provide Internet connectivity to residential clients, WMN traffic is mainly routed over the backbone either toward the Internet gateways (IGWs) or from the IGWs to the APs. In principle, the transport capacity of a WMN can further be upgraded by equipping the underlying backbone routers with multiantenna (MA) radio modules. Motivated by the above consideration, in this paper, we focus on the optimized node selection (e.g., path-routing) over MA mesh backbones when the target is to maximize the end-to-end routed information rate subject to a constraint on the total power available for the relays. Under the assumption of Rayleigh-distributed block fading, we assume that point-to-point capacity-achieving space-time codes (STCs) are used for the single-hop link. At first, we tackle the routing problem when neither interference mitigation (IM) nor transmit beamforming (TB) is performed at the relay nodes, and then, we extend the analysis to the cases when IM and/or TB are also carried out. The effects of channel-state-information (CSI) possibly available at the relay nodes are also investigated. So doing, we are able to gain insight about the combined effect of spatial multiplexing and IM capabilities of the overall MA architecture on both end-to-end capacity and access medium performance of the considered WMN.

Main goal of this work is to give insight on the possible performance improvement arising in the wireless local and/or ad-hoc access from the synergic cooperation of two emerging paradigms, e.g., multi-antenna and cognitive radios. As application scenario, we consider both the faded uplink of a WLAN working in infrastructure-mode, where noncooperative Multi-Antenna cognitive radios attempt to join to a (possibly multi-antenna) access point (AP) and an ad-hoc scenario where each node can communicate with each free node. The target can be twofold and two different approaches are considered. The first is the competitive maximization of own access throughput in the presence of multiple-access Interference (MAI) induced by the other accessing terminals, the second one is the BER minimization. Being the radios cognitive, they are capable to autonomously learn the ambient-context and, then, self-configure their access strategy via suitable power-allocation that is time-frequency-code-space signal-shaping. Furthermore, a generalized approach is developed that allows the node to access with a (possibly hybrid) scheme to the medium by combining different x-DMA strategies under QoS-guaranteed access policy.

In this contribution, the problem of the synchronization for ultra wideband impulse radio (UWB-IR) systems, through the adoption of a multi-antenna platform working on multipath faded channels, is afforded. In this regard, we propose a novel UWB-IR synchronizer devoted to jointly estimate (according to the maximum likelihood (ML) criterium) the arrival times and their (Poisson distributed) number, composing a typical UWB-IR multipath faded channel. Such estimate is effected without any knowledge on the value of the channel paths (noncoherent ML synchronizer). The architecture of such synchronizer is based on a single-input multiple-output (SIMO) platform, instead of a multiple-input multiple-output MIMO one, according to a previous result in the literature. Related performance of this joint ML estimation is expressed in closed via the Cramer-Rao bound (CRB) and is tested by simulations, under acquisition and tracking conditions.

In this contribution we develop a multiple-input multiple-output (MIMO) impulse radio ultra wide band (IR-UWB) transceiver for orthogonal signalling over (baseband) muhipath faded MIMO channels. The proposed maximum-likelihood receiver results to be "partially coherent", since it is optimized to work without any information about channel coefficients, and it is based on the knowledge of the arrivals' times of the transmitted signals' replicas. The behavior of the proposed transceiver has been evaluated via three suitable versions of the Union-Chernoff Bound related to several indoor and outdoor propagation scenarios, and these limits are considered to introduce a novel family of unitary orthogonal space-time block codes (e.g., the space-time OPPM (STOPPM) codes), that are able to attain maximum diversity and coding gains.

The emerging proxy-based wireless content delivery networks (CDNs) should to be designed to download huge-size files over fading-affected channels. However, from a radio resource management point of view, several basic problems still need to be solved for such wireless delivery systems to operate efficiently. Specifically, due to the fading nature of the downlink channel, a still open basic problem is how to design optimal energy-allocation (for example, scheduling) policies that minimize the requested download time when constraints on the total available energy and peak energy are simultaneously active. In this contribution, this problem is solved for application scenarios where the downlink channel is slotted and continuous-state, the carried out traffic is elastic, and the resulting conveyed throughput is measured by any desired increasing concave rate function. Specifically, the optimal energy-allocation policy minimizing the download time is computed in closed form, and its performance is compared against that of a basic on-off heuristic energy scheduler on some Rayleigh-faded multi-antenna delivery systems of practical interest. The carried out performance comparisons point out that the presented optimal policy typically may outperform the heuristic one up to two orders of magnitude, especially when the delivery system is strongly energy limited.

In this contribution Time-Hopping (TH) codes are developed based upon the theory of congruences. These codes can be used for coherent multiuser asynchronous spread spectrum communication systems. They represent a compromise between Costas codes, which have nearly ideal auto-ambiguity properties, and congruential codes presenting nearly ideal cross-properties. The presented code applied not in ranging applications but communications system presents good performance in terms of Bit Error Rate (BER) for UltraWide Band Impulse Radio (UWB-IR) systems. Examples of typical auto- and cross-ambiguity functions are given to illustrate the performance of the presented codes jointly with BER evaluation.

This contribution analyzes the problem of multi-user interference suppression via estimation and subtraction. In particular it is shown that spatial diversity helps the suppression capability of a Base Station and this has an important impact on performance. By fact, we show that the best solution does not consist in transmit at maximum energy level but, in order to allow interference estimation and cancellation, a trade off has to be solved. So, interference suppression can give arise to performance improvements both for achieved throughput (that can be "enhanced") and for error probability (that can be reduced).

In this contribution, the problem of download time minimization, by considering channel state, is solved for application scenario where the downlink channel is slotted and continuous-state, while the resulting conveyed throughput is measured by any desired increasing concave rate-function. Specifically, the optimal energy-allocation policy minimizing the download-time is found and its performance is compared against that of a basic on-off type heuristic scheduler for some Rayleigh-faded multi-antenna downloading systems of practical interest

The paper focuses on competitively optimal power-control and signal-shaping for "ad-hoc" networks composed of multiple-antenna noncooperative transmit/receive terminals affected by spatially colored multi-access interference (MAI). The target is the competitive maximization of the information throughput of each link active over the network. For this purpose, the MAI-impaired network is modeled as a noncooperative strategic game, and sufficient conditions for the existence and uniqueness of the Nash equilibrium are provided. Specifically, the main contribution of the paper may be so summarized. First, we develop fully. distributed and scalable power-control and signal-shaping algorithms allowing the implementation of asynchronous space-division multiple access strategies (SDMACSs) able to guarantee the competitive maximization of the users' throughput under both best effort and contracted QoS access policies. Second, we give evidence that the developed SDMACSs outperform (in terms of aggregate throughput) the conventional centralized ones (such as TDMA/FDMA/CDMA), especially in operating scenarios affected by strong MAI.

The paper focuses on competitively optimal power-control and signal-shaping for "ad-hoc" networks composed of multiple-antenna noncooperative transmit/receive terminals affected by spatially colored multi-access interference (MAI). The target is the competitive maximization of the information throughput (measured in bits/slot) sustained by each link active over the network. For this purpose, the MAI-impaired network is modeled as a noncooperative strategic game, and sufficient conditions for the existence and uniqueness of the Nash equilibrium are provided. We develop fully distributed and scalable power-control and signal-shaping algorithms allowing the implementation of asynchronous space-division multiple access strategies (SDMACSs) able to guarantee the competitive maximization of the users' throughput under both best effort and contracted QoS access policies. We give evidence that the developed SDMACSs outperform (in terms of aggregate throughput) the conventional centralized ones (such as TDMA/FDMA/CDMA), especially in operating scenarios affected by strong MAI. We study the convergence property of the presented SDMACSs and show that, when the throughput set requested by the users is not achievable by the network, then the developed SDMACSs are able to move the working point of the system to the nearest one sustainable by the network. By exploiting the distributed feature of the presented SDMACSs, we propose two connection admission procedures (CAPs) able to optimize (in a competitive sense) the tradeoff between aggregate networking throughput and connection requirements advanced by the users.