Even though there is no universally accepted definition, short-range wireless communications typically refers to a wide variety of technologies with communication ranges from a few centimeters to several hundreds of meters. While the last three decades of the wireless industry have been mostly dominated by cellular systems, short-range wireless devices have gradually become a more integrated part of our everyday lives over the last decade. The Wireless World Research Forum (WWRF) envisions that this trend will accelerate in the upcoming years: by the year 2017, it is expected that seven billion people in the world will be using seven trillion wireless devices [1]. The majority of these devices will be short-range wireless devices that interconnect people with each other and their environments.

While the reliability of wireless communication systems has been studied in detail in the past, a comprehensive study of different factors affecting reliability for short-range wireless systems and how they can be handled is not available in the literature, to date. The present book intends to fill this gap by covering important reliability problems for short-range wireless communication systems. The scope of the contributions in the book is mostly within the domain of wireless personal area networks (WPANs) and wireless sensor networks (WSNs), and issues related to wireless local area networks (WLANs) are not specifically treated.

Due to the differences in application scenarios, quality of service (QoS) requirements, signaling models, and different error sources and mitigation approaches, the high-rate and low-rate systems will be addressed in separate parts of the book.

In this chapter, technologies and standards for low data rate communication systems for wireless personal area networks (WPANs) and wireless sensor networks (WSNs) are discussed. First, ZigBee technology based on the IEEE 802.15.4 standard, and then low-rate UWB technology based on the IEEE 802.15.4a standard are reviewed. Finally, some of the related standards that are being developed by IEEE 802.15 working groups (WGs) are summarized.

Overview and application examples

Together with the recent advances in radio frequency (RF) and MEMS integrated circuit technologies, wireless sensors are becoming cheaper, smaller, and more capable. Through WSNs, a wealth of new applications are becoming possible, including surveillance, building control, factory automation, and in-vehicle sensing [1]. In the near future, we will observe that buildings, furniture, cars, streets, highways, etc. will all comprise WSNs. The Wireless World Research Forum (WWRF) envisions that by the year 2017 about 7 billion people in the world are expected to be using 7 trillion wireless devices, and the majority of these devices will be short-range wireless devices including small-size, low-power, low-complexity WSNs [2]. In order to provide a better picture of potential WSN applications, recent example applications in the literature are listed in Table 6.8 towards the end of the chapter.

WSNs may be typically deployed in large numbers and the network may need to operate for an extensive duration on the same battery. Therefore, key requirements for WSN transceivers include low-cost sensor nodes, small form factors, and low energy consumption.

As wireless channels are fading and error-prone in nature, the adaptive modulation and coding (AMC) scheme is important in wireless communication systems to enhance reliability and spectral efficiency. By adapting transmission schemes to time-varying channels conditions, AMC can provide attractive rate and error performance characteristics. AMC has been widely adopted in the wireless standards, such as GSM and CDMA cellular systems, IEEE 802.11 WLANs, IEEE 802.16 WMANs and also the WPANs based on the short-range ultra-wideband (UWB) systems like the multi-band orthogonal frequency division multiplexing (MB-OFDM) and millimeter wave (MMW).

On the other hand, the automated repeat request (ARQ) scheme is typically used as the link-layer error-control mechanism. By retransmitting the corrupted packets, ARQ can further improve the reliability of wireless systems. The interaction of the queueing and ARQ in the link layer with AMC in the PHY layer provides interesting cross-layer design problems.

The AMC adopted in the conventional narrowband systems over flat-fading channels (e.g., Rayleigh and Nakagami-m fading) has been studied extensively in the literature [1–4]. There has also been considerable interest in the design and analysis of joint AMC and ARQ transmission systems [5–8]. However, the performance of AMC in short-range high-rate systems, considering the UWB channel characteristics and media access control (MAC) protocols, is much less explored. This chapter is intended to fill this gap by presenting a detailed study of the error-control mechanisms employed in high-rate WPANs.

In this chapter, we consider the channel estimation issue in orthogonal frequency division multiplexing (OFDM)-based short-range high-rate wireless communication systems. Even though a number of channel estimation schemes have been proposed for various OFDM systems, few of them are practically suitable for use in the ECMA-368 ultrawideband (UWB) and 60 GHz millimeter-wave communication systems in which limitations on cost and reliability are generally stringent [1, 2]. The main goal of this chapter is to summarize and compare existing channel estimation techniques and to identify an efficient candidate for the practical implementation of low-cost and ultrareliable short-range wireless communication devices.

This chapter begins with an introduction of channel modelling in Section 3.1. Time-dispersive or frequency selective channel propagation characteristics are studied based on the clustering property of multipath components (MPCs). In Section 3.2, several existing channel estimation schemes are reviewed with the focus on those based on training sequences with a block-type structure. Least-squares (LS), linear minimum mean-squared error (LMMSE) and maximum-likelihood (ML)-based algorithms are highlighted followed by a detailed description of a multistage channel estimator. We compare these estimators in terms of their mean-squared error (MSE) performance and complexity for ECMA-368 UWB applications, and show that the multistage channel estimator strikes desirable performance–complexity tradeoffs. Section 3.3 is devoted to studying the impact of channel estimation errors on the system performance. Analysis and numerical examples show that, in terms of symbol error rate (SER) and frame error rate (FER), the multistage channel estimator substantially outperforms the conventional LS approach and it performs comparably to the ML estimator, under various highly noisy multipath channel conditions.

Towards adaptive wireless personal area networks (WPANs)

Introduction and motivation

Recent years have witnessed a growing demand on wireless technologies, thanks to their convenience and the variety of services offered. This success is leading to an increasing adoption of wireless systems, especially the ones operating in the unlicensed 2.4 GHz industrial, scientific, and medical (ISM) frequency band. As a result, the spectrum is overcrowded and shared by a variety of standards, causing serious coexistence problems due to their cross-interference: this may lead to performance degradation or even network malfunctioning.

To overcome the problem of spectrum scarcity, and allow the network to maintain its level of performance and reliability, a cognitive radio (CR) approach can be applied. As will be discussed here, this emerging wireless communication paradigm aims at providing a more effective and flexible spectrum usage by observing the radio environment and adapting transmission parameters consequently. According to the CR approach, instead of a fixed frequency assignment, smart nodes are envisioned to constantly perform “spectrum sensing” and dynamically allocate themselves to the best available channel, thus achieving reliable and spectrally efficient communication. The first step towards the implementation of a CR system is the characterization of interference between coexisting systems. This chapter in particular focuses on wireless personal area networks (WPANs), based on the IEEE 802.15.4 standard, operating in the presence of IEEE 802.11b Wi-Fi traffic. As is evident in Figure 9.1, there is an almost complete overlap between the channels allocated for these two systems [1, 2].

Chapter 11 describes how teams of wireless nodes can work together to improve the reliability of signaling. Due to the inherent uncertain, time-varying, and shared nature of the wireless environment (reflected in shadowing, small-scale fading, and interference), it is difficult to achieve extremely high reliability over a single wireless link even when advanced signal-processing techniques such as diversity and multiuser detection are employed. However, since wireless transmissions are inherently broadcast – overheard by all nodes within range – a natural approach to reliability is to develop cooperative techniques. Cooperative techniques exploit in parallel many helper nodes, called relays, to increase the diversity of the available wireless links. These techniques can yield large improvements in reliability and throughput as well as large decreases in energy consumption.

The chapter starts with an overview of various cooperative communications methods that can be employed depending on the level of channel state information (CSI) and device synchronization. The chapter then considers two techniques in more detail: relaying using virtual beamforming and rateless codes. In both cases, we start out with an analysis of a “fundamental building block” that consists of one source, a number of parallel relays, and one destination. In the virtual beamforming technique, the relays rebroadcast the source signal that they have decoded. Relays adjust their transmission amplitudes and phases to ensure that their transmissions interfere constructively, maximizing the destination's signal-to-noise ratio (SNR). In the rateless coding approach, the relays individually decode the source message.

Introduction

The design of large-scale distributed wireless networks (e.g., mesh and ad-hoc networks, relay networks) poses a set of new challenges to information theory, communication theory, and network theory. Such networks are characterized by the large size of the network both in terms of the number of nodes (i.e., dense) and in terms of the geographical area the network covers. Each terminal can be severely constrained by its computational and transmission/receiving power. It is therefore important to understand how to utilize efficiently the physical infrastructure and system resources (power, bandwidth, etc.). Moreover, delay and complexity constraints along with diversity-limited channel behavior may require transmissions under insufficient levels of coding protection causing link outages. These constraints require an understanding of the performance limits of such networks and associated implications on network architectures jointly in terms of power and bandwidth efficiency and link reliability, especially when designing key operational elements essential in these systems, such as multihop routing and relay processing algorithms, bandwidth allocation policies, and relay deployment models.

Generally speaking, characterizing the fundamental limits of communication over large-scale distributed wireless networks is a difficult problem, owing to the highly complex nature of the information exchange among multiple terminals. Even the capacity of the classical relay channel is not solved yet. One simplification in this regard is to characterize the scaling laws, where the goal is to investigate how a certain performance measure (throughput, energy, delay, etc.) scales as the number of nodes in the network grows asymptotically large.

In low-rate wireless networks, energy saving has been one of the recent important research challenges. Compared to high-rate networks designed for multimedia data streaming or large file transfer, low-rate systems focus mainly on monitoring and control applications. In most of these applications, devices are expected to have low data rates and to operate on battery. Since replacing or recharging the battery is difficult in many situations, conserving battery power without comprising reliability is one of the essential challenges. In this chapter, we discuss the energy efficiency of medium access control (MAC) layer protocols because they control actual transmission and reception of devices, and therefore play a critical role in the energy consumption aspects.

Background on energy efficiency

Recently, saving energy has been a prominent topic in the wireless communications and networking community. Almost all devices changing our lifestyle such as laptops, smart phones, and small environmental sensors operate on battery, and equip wireless interfaces to connect to the outside world. Trouble comes mainly from the following fact: while most technologies for portable electronic devices are evolving very rapidly, the energy density of batteries has crawled by merely a factor of 3 over the past 15 years [1]. Moreover, in many applications, such as environmental sensing, replacing or recharging batteries is costly and not feasible.

The only standard MAC protocol for the low-power and low-rate wireless networks is the IEEE 802.15.4 protocol [2]. Although the standard supports energy saving, the actual energy saving is not realized without proper use of certain functions.

This chapter presents an analysis of the gain in system capacity and reliability that can be achieved with the use of multiple-antenna array systems. The general philosophy of multiple-input multiple-output (MIMO) systems is introduced and practical design considerations are highlighted. We focus on two short-range wireless communication technologies of interest and promise, namely ultrawideband (UWB) and 60 GHz systems, and discuss them in the context of MIMO systems. Based on measurements and simulations, we discuss the propagation channel conditions and investigate their impact on MIMO performance. An important aspect of the propagation channel is its spatial correlation, which we analyze in detail and draw conclusions for MIMO array design. For our candidate communication schemes, we investigate MIMO transmission strategies such as time-reversal, beamforming, and waterfilling, and evaluate the corresponding performance improvement. We provide physical insights into the results and make recommendations for the practical design of future wireless systems based on UWB and 60 GHz MIMO techniques.

Principles of MIMO systems

Boosting the capacity and reliability of a wireless link has been a topic of great interest for several decades in communications design. The use of multiple-antenna or MIMO arrays in wireless systems has attracted attention owing to the potential for increasing performance [1–4]. After excessive interest in the last decade, MIMO techniques now form part of many current narrowband and wideband wireless standards and applications, some examples of which are the IEEE 802.11n WiFi and 802.16e WiMAX systems, and a host of proposed 4G systems.

In this chapter, two technologies for high data-rate communications systems for wireless personal area networks (WPANs) are discussed. Namely, the ultrawideband (UWB) technology that operates in the 3.1–10.6 GHz band and the millimeter wave (MMW) technology (also called 60 GHz radio) that can use the 57–64 GHz band in most parts of the world are considered. First, a generic overview is given and various application scenarios are discussed. Then, the ECMA standard for high-rate UWB systems is studied. Finally, two standards for the 60 GHz MMW radio are investigated.

Overview and application scenarios

In order to realize high-speed communications systems with low power consumption, signals with very large bandwidths need to be employed. One way of designing such communications systems is to use UWB signals as an underlay technology by utilizing all or part of the frequency spectrum between 3.1 and 10.6 GHz [1–3]. According to the US Federal Communications Commission (FCC), a UWB signal is defined as having an absolute bandwidth of at least 500 MHz or a relative (fractional) bandwidth of larger than 20% [3–4].

In order not to cause any adverse effects on other wireless systems in the same frequency band, such as IEEE 802.11a wireless local area networks (WLANs), certain power emission limits are imposed on UWB devices by regulatory authorities, such as the FCC in the USA [3] and the Electronic Communications Committee (ECC) in Europe [5].

Introduction

The systematic study of relaying and cooperation in the context of digital communication goes back to the work of Van der Meulen and Cover and El Gamal. The basic relay channel of consists of a source, a destination, and a relay node. The system models in are either discrete memoryless channels (DMC), or continuous-valued channels which are characterized by constant (nonrandom) links and additive white Gaussian noise.

The study of cooperative wireless communication is a more recent activity that started in the late 1990s, and since then has seen explosive growth in many directions. Our focus is specifically on aspects of cooperative communication related to cellular radio. Aside from the fading model, the defining aspects of a cellular system are base stations that are connected to an infrastructure known as the backhaul, which has a much higher capacity and better reliability than the wireless links. The endpoints of the system are mobiles that operate subject to energy constraints (battery) as well as constraints driven by the physical size of the device that lead to bounds on computational complexity and the number of antennas, among other considerations. There are multiple mobiles in each cell as well as frequency reuse, leading to intracell interference and intercell interference, respectively. The exponential path-loss laws lead to significant variations in signal power at various points in the cell.

Introduction

Mobile communication systems have to provide exponentially increasing data rates for an increasing number of subscribers using ubiquitous data services. As the capacity per cell is limited by the available bandwidth, the same time frequency resources must be spatially reused. Hence, the more the user density increases, the higher the spatial reuse must be to satisfy the demand for high data rate services. This chapter discusses relaying as a candidate technology to increase the spatial reuse and therefore to provide the required data rates while reducing energy consumption in mobile communication systems.

Two motivating examples

A challenging property as well as an opportunity for exploiting the wireless channel is nonlinear signal attenuation (path-loss), which offers the possibility to concentrate power at certain points in the network and spatially reuse resources within a mobile communication network. Consider an additive white Gaussian noise (AWGN) channel with a path-loss exponent α = 4, receiver noise power N, and transmission power P. Given these qualities and assuming a downlink transmission where a terminal can use the received signals from each radio access point (RAP), the observed signal-to-noise ratio (SNR) at a normalized distance d is given by ρ(d) = Σi P/N · |di − d|−α, where di is the position of the ith RAP.

Introduction

Coordinated multipoint (CoMP) transmission is considered as a promising multiple-input multiple-output (MIMO) technique that can be a primary element for better intercell interference (ICI) control in the next generation cellular networks. The classical MIMO technique uses a colocated antenna array for beamforming to the direction of an intended user while trying to reduce interstream and interuser interference. However, such single-cell MIMO transmissions cause intensified narrow beams and can interfere with other cells' users. In multicell simulations, interference from adjacent cells is even more detrimental. It is found that, depending on the scenario, no less than 30% of the user equipment (UEs) in a cell will have a wideband signal-to-interference-and-noise ratio (SINR) below 0 dB. Various techniques to combat this problem have been proposed by standardization organizations such as 3GPP LTE and IEEE 802.16e/m. Typical examples include sectorization using directional antenna, ICI randomization with interference cancelation at the receiver, and ICI avoidance techniques, such as ICI-aware power control, fractional frequency reuse (FFR), and intercell scheduling. These techniques can be deployed in addition to MIMO but often lead to either loss of average sector throughput or increased receiver complexity. CoMP transmission has been proposed and supported by many companies, including Ericsson, Motorola, Alcatel-Lucent, Huawei, Qualcomm, Samsung, LGE, ETRI, DoCoMO, Nortel, and is believed to be a promising ICI mitigation solution that can improve cell-edge throughput as well as average sector throughput with little complexity increase at the receiver side.

Introduction

The deployment of relays in cellular system has been standardized in the WiMAX, IEEE 802.16j standard and is a topic of discussion in the advanced specifications of Third Generation Partnership Project (3GPP) long-term evolution (LTE). Although commercial relay deployments in cellular systems are not prominent at present, future wireless cellular systems will involve operation with dedicated relays to improve coverage, increase cell-edge throughput, deliver high data rates, and assist group mobility. The proposed architecture is such that relays would be placed at certain locations (planned or unplanned) in the cell to help in forwarding the message from the base station to the user in the downlink, and from the user to the base station in the uplink. Relays will be more sophisticated than simple repeaters and could perform some digital base band processing to help the destination terminal get better reception. These relays will rely on air interfaces, and hence avoid the considerable backhaul costs involving data aggregation and infrastructure costs associated with backbone connectivity. However, there are a lot of open issues that require research to answer.

Research challenges

Some of the major research issues in relay-based cellular systems are as follows:

(1) Throughput gains due to relay deployments In cellular networks that are coverage limited, deploying relays can help in multihop transmission and provide power gains due to a reduction of distance attenuation.