A Cross-Layer Design on the Basis of Multiple Packet Reception in Asynchronous Wireless Network

We consider the problem of quality of service (QoS) routing in multi-hop wireless networks where data are transmitted from a source node to a destination node via multiple hops. The routing component of a QoS-routing algorithm essentially involves the link and path metric calculation which depends on many factors such as the physical and link layer designs of the underlying wireless network, transmission errors due to channel fading and interference, etc. The task of link metric calculation basically requires us to solve a tandem queueing problem which is the focus of this paper. We present a unified tandem queue framework which is applicable for many different physical layer designs. We present both exact and approximated decomposition approaches. Using the queueing framework, we can derive different performance measures, namely, end-to-end loss rate, end-to-end average delay, and end-to-end delay distribution. The proposed decomposition approach is validated and some interesting insights into the system performance are highlighted. We then present how to use the decomposition queueing approach to calculate the link metric and incorporate this into the route discovery process of the QoS routing algorithm. The extension of the queueing and QoS routing framework to wireless networks with class-based queueing for QoS differentiation is also presented.

IEEE 802.11ax is the emerging standard release of the next-generation of wireless local area networks (WLANs). The core idea is to enhance the area throughput in high-density deployment scenarios through high efficiency (HE) multiple access control (MAC) and physical layer (PHY) technology. Orthogonal frequency-division multiple access (OFDMA) technology has been selected as the key techniques in 802.11ax. However, the existing OFDMA technology has an interference diffusion problem, i.e., multi-user parallel transmission aggravates the interference to the surrounding cells. To solve these problems, we propose a spatial clustering group-based OFDMA protocol (SCG-OFDMA). In the SCG-OFDMA protocol, the concurrent transmission of nodes with close spatial distance can reduce the degree of interference diffusion. Particularly, the SCG-OFDMA protocol and process are designed based on the 802.11ax Multi-User (MU) MAC framework. The computer simulation analysis results demonstrate an improvement in the throughput of 36.62% at most.

Most of the proposed communication protocols exploiting the collaborative nature of WSNs and its correlation characteristics improve energy efficiency. However, they follow the traditional layered protocol architectures; specifically, the majority of these communication protocols are individually developed for different networking layers, i.e., transport, network, medium access control (MAC), and physical layers. While they may realize high performance in terms of the metrics related to each of these individual layers, they are not jointly optimized to maximize the overall network performance while minimizing the energy expenditure. Considering the scarce energy and processing resources of WSNs, joint optimization, and design of networking layers, i.e., cross-layer design, stands as the most promising alternative to inefficient traditional layered protocol architectures.The basic principle of cross-layer design is to make information available to all levels of the protocol stack. It allows the definition of protocols or mechanisms that do not meet the isolation layers of the OSI model (van der Schaar M, Shankar NS, Wirels Commun 12(4):50–58, 2005; Srivastava V, Motani M, Commun Mag 43(12):112–119, 2005). In fact, cross-layer integration and design techniques result in significant improvement in terms of energy conservation in WSNs (van Hoesel L, Nieberg T, Wu J, Havinga PJM, Wirel Commun 11(6):78–86, 2004; Yetgin H, Cheung KTK, El-Hajjar M, Hanzo L, Trans Veh Technol 64(8):3795–3803, 2015). Several researches started by focusing on the cross-layer interaction and design to develop new communication protocols (Melodia T, Vuran MC, Pompili D, The state of the art in cross-layer design for wireless sensor networks. Vol 3883, in Lecture Notes in Computer Science-Wireless Systems and Network Architectures in Next Generation Internet (EuroNGI), by M Cesana and L Fratta, Berlin/Heidelberg: Springer, pp 78–92, 2005). Yet, these works either provide analytical results without communication protocol design or perform pairwise cross-layer design within limited scope, e.g., only MAC and network layers, which do not consider all of the networking layers involved in WSNs communication, such as transport, network, MAC, and physical layers.Considering the scarce energy and processing resources of WSNs, joint optimization, and design of networking layers, i.e., cross-layer design, stands as the most promising alternative to inefficient traditional layered protocol architectures. There are considerable benefits of rethinking the protocol functions of networking layers in a unified way so as to provide a single communication module for efficient communication in WSNs.KeywordsCross-layering approachesLayers interactionsSingle-layer integrated moduleHeuristic approachCross-layering MAC and network layersCross-layering physical and MAC and network layers PANELCLBTPGFPlusXLPCross-layer design for WSNs security

5G has achieved large-scale commercialization across the world and the global 6G research and development is accelerating. To support more new use cases, 6G mobile communication systems should satisfy extreme performance requirements far beyond 5G. The physical layer key technologies are the basis of the evolution of mobile communication systems of each generation, among which three key technologies, i.e., duplex, waveform and multiple access, are the iconic characteristics of mobile communication systems of each generation. In this paper, we systematically review the development history and trend of the three key technologies and define the Non-Orthogonal Physical Layer (NOPHY) concept for 6G, including Non-Orthogonal Duplex (NOD), Non-Orthogonal Multiple Access (NOMA) and Non-Orthogonal Waveform (NOW). Firstly, we analyze the necessity and feasibility of NOPHY from the perspective of capacity gain and implementation complexity. Then we discuss the recent progress of NOD, NOMA and NOW, and highlight several candidate technologies and their potential performance gain. Finally, combined with the new trend of 6G, we put forward a unified physical layer design based on NOPHY that well balances performance against flexibility, and point out the possible direction for the research and development of 6G physical layer key technologies.

Multiple packet reception (MPR) is becoming a viable reality for wireless random access protocols thanks to advances in the physical layer and new coding techniques. In the simplest $K$ -MPR model, a receiver can resolve up to $K\geq 1$ parallel transmissions. We extend the classical analysis of pure and slotted ALOHA to $K$ -MPR devices with arbitrary degree $K$ for fixed and variable packet size. Through a parsimonious modeling approach, we derive relatively simple analytical expressions. In this way, we gain insight and quantitative understanding on the fundamental tradeoffs between pure and slotted ALOHA and on the scaling of maximum achievable throughput with $K$ .

Deep learning is driving a radical paradigm shift in wireless communications, all the way from the application layer down to the physical layer. Despite this, there is an ongoing debate as to what additional values artificial intelligence (or machine learning) could bring to us, particularly on the physical layer design; and what penalties there may have? These questions motivate a fundamental rethinking of the wireless modem design in the artificial intelligence era. Through several physical-layer case studies, we argue for a significant role that machine learning could play, for instance in parallel error-control coding and decoding, channel equalization, interference cancellation, as well as multiuser and multiantenna detection. In addition, we will also discuss the fundamental bottlenecks of machine learning as well as their potential solutions in this paper.

This paper presents SECANT (Spectrum Efficient Communications and Advanced Networking Technology) as a novel multiuser communication protocol that integrates advanced physical (PHY) layer techniques for adaptive multiple access and interference management. SECANT supports concurrent multiple access (MA) transmissions to common receivers and parallel peer-to-peer (P2P) transmissions in the network. SECANT combines multiuser multiple-input multiple output (MU-MIMO), multiuser detection (MUD), and interference alignment (IA) methods at the PHY layer such that spectrum efficiency can be improved in both interference and signal spaces. An adaptive medium access control (MAC) mechanism is developed to enable spectrum efficiency gains at the PHY layer by managing concurrent transmissions and interference levels. Numerical results indicate significant spectrum efficiency gains (>14 times for fully loaded, and >56 times for 25% loading) that can be achieved over conventional single antenna systems with static MAC protocols.

Although cooperative communication has been proposed at the physical layer to address multi-path fading effects, how physical layer gains with cooperative communication can translate to tangible performance benefits in end-to-end flows remains to be an open problem. This paper represents one step forward towards a deeper understanding of the interplay between end-to-end throughput and physical layer cooperative communication, in the general context of multi-hop multi-channel wireless networks. Based on a decode-and-forward physical layer design with rateless codes, we reformulate the problem of routing and channel assignment to account for physical layer cooperation. We design a distributed protocol to solve the new problem. Our simulation results have validated the effectiveness of our protocol to offer a substantial gain with respect to stabilizing the offered aggregate throughput in the network.Keywordscooperative communicationchannel assignmentmulti-hop multi-channel wireless networks

Objectives: The objective of using cross layer approach in Adaptive Modulation and Coding (AMC) based wireless systems is to enhance the spectral efficiency and reliability of transmission n time varying MIMO channel. Methods: A cross layered design using k-NN based AMC with Improved Low-Density Parity Check Accumulate codes (ILDPCA) that opt for nonuniform division of check nodes at the physical layer and Incremental Redundancy Hybrid Retransmission Request (IRHARQ) at the link layer is implemented. The encoded symbols are routed consecutively over MIMO fading channels. The MIMO channel is predicted at the receiver and is forwarded to the AMC controller. IR-HARQ regulates packet retransmission with new codeword on failure. Findings: The performance of the cross layer design is assessed in terms of BER, packet loss and spectral efficiency. The proposed cross layer with ILDPCA coders improves the spectral efficiency by 45% compared to the conventional systems but still maintaining acceptable PLR. Application: Therefore the proposed adaptive system can be adopted for reliable adaptive transmission over MIMO network and is suitable for multimedia applications. Keywords: Cross Layer, Multiple Input Multiple Output, Reliability, Wireless System Design

Adaptive techniques play a key role in modern wireless communication systems. The concept of adaptation is emphasized in the Adaptation in Wireless Communications Series through a unified framework across all layers of the wireless protocol stack ranging from the physical layer to the application layer, and from cellular systems to next-generation wireless networks. Adaptation and Cross Layer Design in Wireless Networks is devoted to adaptation in the data link layer, network layer, and application layer. The book presents state-of-the-art adaptation techniques and methodologies, including cross-layer adaptation, joint signal processing, coding and networking, selfishness in mobile ad hoc networks, cooperative and opportunistic protocols, adaptation techniques for multimedia support, self organizing routing, and tunable security services. It presents several new theoretical paradigms and analytical findings which are supported with various simulation and experimental results. Adaptation in wireless communications is needed in order to achieve high capacity and ubiquitous communications. The current trend in wireless communication systems is to make adaptation dependent upon the state of the relevant parameters in all layers of the system. Focusing on simplified cross layer design approaches, this volume describes advanced techniques such as adaptive resource management, adaptive modulation and coding, 4G communications, QoS, diversity combining, and energy and mobility aware MAC protocols. The first volume in the series, Adaptive Signal Processing in Wireless Communications (cat no.46012) covers adaptive signal processing at the physical layer.

Recently, research on sixth-generation (6G) networks has gained significant interest. 6G is expected to enable a wide-range of applications that fifth-generation (5G) networks will not be able to serve reliably, such as tactile Internet. Additionally, 6G is expected to offer Terabits per second (Tbps) data rates, 10 times lower latency, and near 100% coverage, compared to 5G. Thus, 6G is expected to expand across all available spectrums including terahertz (THz) and optical frequency bands. In this manuscript, mixed-carrier communication (MCC) is investigated as a novel physical layer (PHY) design for 6G networks. The proposed MCC version in this study is based on visible light communication (VLC). MCC enables a unified transmission PHY design to connect devices with different complexities, simultaneously. The design trade-offs and the required signal-to-noise ratio (SNR) per individual modulation schemes embedded within MCC are investigated. The complexity analysis shows that a conventional optical OFDM receiver can capture the high-speed bit-stream embedded within MCC. For a forward error correction (FEC) bit-error-rate (BER) threshold of 3.8×10−3, MCC is optimized to maximize the spectral efficiency by embedding 2-beacon phase-shift keying (2-BnPSK) within an MCC envelope on top of 12 bits per beacon position modulation (BPM) symbol.

Fast and reliable high-speed intersatellite communication (ISC) between small satellites is dependent on the physical layer (PL) design of the onboard communication system. However, as with nonlegacy systems, the lack of architecture and design information pertaining to the development of the PL of an LED-based visible light communication (VLC) system for ISC poses significant challenges to architecting the communication system. Addressing these challenges requires a holistic approach to the specification of the system design. To this end, we explore the use of model-based systems engineering (MBSE) principles in mitigating the design complexity of the PL architecture for the VLC system. Design concerns and gaps are addressed by developing an executable black-box system model that specifies the conceptual architecture of the system, and a parametric model that analyzes multiple system configurations based on generated values for the signal-to-noise ratio and bit error rate parameters. We utilize the structural, behavioral, and parametric semantics of SysML to define, specify, visualize, and analyze the various system design configurations. The resulting PL black-box system specification is verified through model execution.

Multimedia transmissions over wireless networks need continuous media play out. In order to meet best Quality of Services, higher layers data depend on lower layer parameters. That is readily known as cross-layer design. Our cross-layer design model optimizes the physical layer, MAC layer and application layer. Video summary frames are transmitted via MIMO transmit/receive diversity with AMC at the physical layer and Payload and data rate adaptation at the MAC link layer and source coding at the application layer. We, first model the finite-state Markov chain (FSMC) for the physical layer service and based on that, we then characterize the Lagrangian relaxation and Dynamic programming to find the optimal shortest path. The source coding as well as retransmission requests are based on the channel-state information (CSI) and the system controller is implemented in all the three physical, MAC layer and application layers. The numerical results revealed that our proposed cross-layer design can efficiently achieve the effective throughput and distortion gain.

Deep learning approaches applied in diverse fields further the expectations and demands of 5G wireless networks and necessitates leveraging the intelligence to network with widespread renewed interest of big data. The integration of machine learning (ML) notion across core and edge infrastructure of wireless networks imparts intelligence. ML can enable mobile devices to intelligently monitor their environment by learning the features of a wireless channel—its dynamics, traffic pattern, requests, and user context, among other aspects. ML enables the infrastructure to learn from the wireless networking environment and adaptively makes decision, which provides optimized solutions for best connectivity, resource allocation, quality-of-service parameters, etc. ML can redefine how the physical layer functions, namely, coding/decoding, channel estimation, channel equalization, and modulation/demodulation at the transmitter and receiver sides. The majority of the communication system is modeled as a linear system, but practically, ML captures the nonlinear effects of hardware and quantization and provides a better solution. A combined approach is possible through ML for the solutions provided in the literature for individual blocks, say, coding, resource allocation block. Also parallel processing ability and distributed memory aid to complexity reduction at the respective block. The proliferation of graphics processing unit–enabled hardware provides speedy action. These are the benefits of deep learning in physical layer design. This chapter intends to provide a deep learning model addressing the physical layer of the network. The authors propose an intelligent ML detector at the multiple-input multiple-output receiver able to classify a signal constellation and the transmitted antenna.

This paper proposes the design of enabling technologies for practical wireless communication systems operating in the TV white space (TVWS). The main objective of this paper is to cover a macro perspective on the system design blocks including: (a) targeted use case applications and governing regulations, (b) channelization, physical (PHY) layer and medium access control (MAC) layer designs, and (c) achievable throughput and range. It is the intention of this paper to serve as a general guideline for designing wireless communication systems operating in TVWS. The core system design addresses both PHY and MAC layer issues with realistic system considerations. In the PHY layer, a channelization design that fits into the area-specific TV channels and a transceiver that enables data exchange in the TV bands are designed. In the MAC layer, a cognitive engine that manages access to vacant TV channels and MAC functionalities that facilitate effective medium access are also proposed. As a result, the system is capable of supporting up to a typical throughput of 80 Mbps, and a maximum number of 40 users, assuming all users performing the most bandwidth-hungry application in the use case scenario. The corresponding operating range is found reach up to 400 m.