Design guidelines for spatial modulation

A new class of low-complexity, yet energyefficient Multiple-Input Multiple-Output (MIMO) transmission techniques, namely the family of Spatial Modulation (SM) aided MIMOs (SM-MIMO) has emerged. These systems are capable of exploiting the spatial dimensions (i.e. the antenna indices) as an additional dimension invoked for transmitting information, apart from the traditional Amplitude and Phase Modulation (APM). SM is capable of efficiently operating in diverse MIMO configurations in the context of future communication systems. It constitutes a promising transmission candidate for large-scale MIMO design and for the indoor optical wireless communication whilst relying on a single-Radio Frequency (RF) chain. Moreover, SM may also be viewed as an entirely new hybrid modulation scheme, which is still in its infancy. This paper aims for providing a general survey of the SM design framework as well as of its intrinsic limits. In particular, we focus our attention on the associated transceiver design, on spatial constellation optimization, on link adaptation techniques, on distributed/ cooperative protocol design issues, and on their meritorious variants

ISAC-Enabled Beam Alignment for Terahertz Networks: Scheme Design and Coverage Analysis

As a key pillar technology for the future 6G networks, terahertz (THz) communication can provide high-capacity transmissions, but suffers from severe propagation loss and line-of-sight (LoS) blockage that limits the network coverage. Narrow beams are required to compensate for the loss, but they in turn bring in beam misalignment challenge that degrades the THz network performance. The high sensing accuracy of THz signals enables integrated sensing and communication (ISAC) technology to assist the LoS blockage and user mobility-induced beam misalignment, enhancing THz network coverage. In line with the 5G beam management, we propose a joint synchronization signal block (SSB) and reference signal (RS)-based sensing (JSRS) scheme to predict the need for beam switches, and thus prevent beam misalignment. We further design an optimal sensing signal pattern that minimizes beam misalignment with fixed sensing resources, which reveals design insights into the time-to-frequency allocation. We derive expressions for the coverage probability and spatial throughput, which provide instructions on the ISAC-THz network deployment and further enable evaluations for the sensing benefit in THz networks. Numerical results show that the JSRS scheme is effective and highly compatible with the 5G air interface. Averaged in tested urban use cases, JSRS achieves near-ideal performance and reduces around 80% of beam misalignment, and enhances the coverage probability by about 75%, compared to the network with 5G-required positioning ability

Optimizing resource allocation in eh-enabled internet of things

Internet of Things (IoT) aims to bridge everyday physical objects via the Internet. Traditional energy-constrained wireless devices are powered by fixed energy sources like batteries, but they may require frequent battery replacements or recharging. Wireless Energy Harvesting (EH), as a promising solution, can potentially eliminate the need of recharging or replacing the batteries. Unlike other types of green energy sources, wireless EH does not depend on nature and is thus a reliable source of energy for charging devices. Meanwhile, the rapid growth of IoT devices and wireless applications is likely to demand for more operating frequency bands. Although the frequency spectrum is currently scarce, owing to inefficient conventional regulatory policies, a considerable amount of the radio spectrum is greatly underutilized. Cognitive radio (CR) can be exploited to mitigate the spectrum scarcity problem of IoT applications by leveraging the spectrum holes. Therefore, transforming the IoT network into a cognitive based IoT network is essential to utilizing the available spectrum opportunistically. To address the two aforementioned issues, a novel model is proposed to leverage wireless EH and CR for IoT. In particular, the sum rate of users is maximized for a CR-based IoT network enabled with wireless EH. Users operate in a time switching fashion, and each time slot is partitioned into three non-overlapping parts devoted for EH, spectrum sensing and data transmission. There is a trade-off among the lengths of these three operations and thus the time slot structure is to be optimized. The general problem of joint resource allocation and EH optimization is formulated as a mixed integer nonlinear programming task which is NP-hard and intractable. Therefore, a sub-channel allocation scheme is first proposed to approximately satisfy users rate requirements and remove the integer constraints. In the second step, the general optimization problem is reduced to a convex optimization task. Another optimization framework is also designed to capture a fundamental tradeoff between energy efficiency (EE) and spectral efficiency for an EH-enabled IoT network. In particular, an EE maximization problem is formulated by taking into consideration of user buffer occupancy, data rate fairness, energy causality constraints and interference constraints. Then, a low complexity heuristic algorithm is proposed to solve the resource allocation and EE optimization problem. The proposed algorithm is shown to be capable of achieving a near optimal solution with polynomial complexity. To support Machine Type Communications (MTC) in next generation mobile networks, NarrowBand-IoT (NB-IoT) has emerged as a promising solution to provide extended coverage and low energy consumption for low cost MTC devices. However, the existing orthogonal multiple access scheme in NB-IoT cannot provide connectivity for a massive number of MTC devices. In parallel with the development of NB-IoT, Non-Orthogonal Multiple Access (NOMA), introduced for the fifth generation wireless networks, is deemed to significantly improve the network capacity by providing massive connectivity through sharing the same spectral resources. To leverage NOMA in the context of NB-IoT, a power domain NOMA scheme is proposed with user clustering for an NB-IoT system. In particular, the MTC devices are assigned to different ranks within the NOMA clusters where they transmit over the same frequency resources. Then, an optimization problem is formulated to maximize the total throughput of the network by optimizing the resource allocation of MTC devices and NOMA clustering while satisfying the transmission power and quality of service requirements. Furthermore, an efficient heuristic algorithm is designed to solve the proposed optimization problem by jointly optimizing NOMA clustering and resource allocation of MTC devices

Modulation options for OFDM-based waveforms: classification, comparison, and future directions

This paper provides a comparative study on the performance of different modulation options for orthogonal frequency division multiplexing (OFDM) in terms of their spectral efficiency, reliability, peak-to-average power ratio, power efficiency, out-of-band emission, and computational complexity. The modulation candidates are classified into two main categories based on the signal plane dimension they exploit. These categories are: 1) 2-D signal plane category including conventional OFDM with classical fixed or adaptive QAM modulation and OFDM with differential modulation, where information is conveyed in changes between two successive symbols in the same subcarrier or between two consecutive subcarriers in the same OFDM symbol and 2) 3-D signal plane category encompassing: a) index-based OFDM modulation schemes which include: i) spatial modulation OFDM, where information is sent by the indices of antennas along with conventional modulated symbols and ii) OFDM with index modulation, where the subcarriers’ indices are used to send additional information; b) number-based OFDM modulation schemes which include OFDM with subcarrier number modulation, in which number of subcarriers is exploited to convey additional information; and c) shape-based OFDM modulation schemes which include OFDM with pulse superposition modulation, where the shape of pulses is introduced as a third new dimension to convey additional information. Based on the provided comparative study, the relationship and interaction between these different modulation options and the requirements of future 5G networks are discussed and explained. This paper is then concluded with some recommendations and future research directions.This work was supported in part by the Scientific and Technological Research Council of Turkey (TUBITAK), under Grant 215E316

Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication

The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires advanced system capabilities far beyond existing network architectures. In particular, such massive communication has been recognized as a prime driver that can empower the 6G vision of future ubiquitous connectivity, supporting Internet of Human-Machine-Things for which massive access is critical. This paper surveys the most recent advances toward massive access in both academic and industry communities, focusing primarily on the promising compressive sensing-based grant-free massive access paradigm. We first specify the limitations of existing random access schemes and reveal that the practical implementation of massive communication relies on a dramatically different random access paradigm from the current ones mainly designed for human-centric communications. Then, a compressive sensing-based grant-free massive access roadmap is presented, where the evolutions from single-antenna to large-scale antenna array-based base stations, from single-station to cooperative massive multiple-input multiple-output systems, and from unsourced to sourced random access scenarios are detailed. Finally, we discuss the key challenges and open issues to shed light on the potential future research directions of grant-free massive access.Comment: Accepted by IEEE IoT Journa

MAC/PHY Co-Design of CSMA Wireless Networks Using Software Radios.

In the past decade, CSMA-based protocols have spawned numerous network standards (e.g., the WiFi family), and played a key role in improving the ubiquity of wireless networks. However, the rapid evolution of CSMA brings unprecedented challenges, especially the coexistence of different network architectures and communications devices. Meanwhile, many intrinsic limitations of CSMA have been the main obstacle to the performance of its derivatives, such as ZigBee, WiFi, and mesh networks. Most of these problems are observed to root in the abstract interface of the CSMA MAC and PHY layers --- the MAC simply abstracts the advancement of PHY technologies as a change of data rate. Hence, the benefits of new PHY technologies are either not fully exploited, or they even may harm the performance of existing network protocols due to poor interoperability. In this dissertation, we show that a joint design of the MAC/PHY layers can achieve a substantially higher level of capacity, interoperability and energy efficiency than the weakly coupled MAC/PHY design in the current CSMA wireless networks. In the proposed MAC/PHY co-design, the PHY layer exposes more states and capabilities to the MAC, and the MAC performs intelligent adaptation to and control over the PHY layer. We leverage the reconfigurability of software radios to design smart signal processing algorithms that meet the challenge of making PHY capabilities usable by the MAC layer. With the approach of MAC/PHY co-design, we have revisited the primitive operations of CSMA (collision avoidance, carrier signaling, carrier sensing, spectrum access and transmitter cooperation), and overcome its limitations in relay and broadcast applications, coexistence of heterogeneous networks, energy efficiency, coexistence of different spectrum widths, and scalability for MIMO networks. We have validated the feasibility and performance of our design using extensive analysis, simulation and testbed implementation.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/95944/1/xyzhang_1.pd

Multitone NB-IoT optimization based on filtered OFDM waveform

Narrowband Internet of Things (NB-IoT) is standardized by 3GPP as a novel radio-access scheme for next-generation IoT technology. In-band operation mode, as one of its deployment methods, shares the spectrum of LTE. To avoid interference leakage on adjacent resource blocks (RBs), the spectrum sharing system needs a spectrally well-localized waveform. In this thesis, we investigate filtered-OFDM waveform for NB-IoT in-band system. This is achieved by designing and exploiting optimized filter for each sub-band. Specifically, the optimum filter needs a suitable length, a relatively narrowed transition band, and adequate stopband attenuation, which efficiently reduces the required guard-band, minimizing the related overhead in resource usage. In the experiments, we simplify the system model by shifting the NB-IoT RB to the center of the LTE spectrum. Firstly, we test potential filter types with various transition bands, selecting suitable filter configurations with acceptable performance when the system operates under carrier frequency offset (CFO) of half subcarrier spacing. Then, we define two different power level test cases, which are based on the minimum SNR for 1% uncoded bit-error rate (BER), for examining NB-IoT and LTE error tolerance in asynchronous cases, when NB-IoT system fails to synchronize to the time-frequency alignment of LTE. Finally, the system performance in a multipath channel is evaluated. With filtered-OFDM, the out-of-band emission is suppressed effectively and the tolerance to time and frequency offset is significantly improved, which makes the proposed scheme suitable for supporting asynchronous NB-IoT operation

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&