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.

Introduction

Background. The degrees of freedom introduced by multiple antennas at the transmitters and receivers of wireless communication systems facilitate multiplexing gains and diversity gains. A wireless point-to-point link with M transmit and N receive antennas constitutes an M-by-N multiple-input multiple-output (MIMO) communication system. The ergodic capacity of an M-by-N MIMO fading channel increases almost linearly with min{M,N} provided that the fading meets certain mild conditions. Hence, it is not surprising that MIMO has attracted a lot of research interest since it enables significant performance and throughput gains without requiring extra transmit power and bandwidth. However, limitations on the number of antennas that a wireless device is able to support as well as the significant signal processing power and complexity required in MIMO tranceivers limit the gains that can be achieved in practice.

To overcome the limitations of traditional MIMO, the concept of cooperative communication has been proposed for wireless networks such as fixed infrastructure cellular networks and wireless ad-hoc networks. The basic idea of cooperative communication is that the single-antenna terminals of a multiuser system can share their antennas and create a virtual MIMO communication system. Thereby, three different types of cooperation may be distinguished, namely, user cooperation, base station (BS) cooperation, and relaying. Theoretically, user cooperation and BS cooperation are able to provide huge performance gains, when compared with noncooperative networks. However, the required information exchange between users and BSs may make these options less attractive in practice.

Introduction

Cellular communication systems provide wireless coverage to mobile users across potentially large geographical areas, where base stations (BSs) provide service to users as interfaces to the public telephone network. Cellular communication is based on the principle of dividing a large geographical area into cells which are serviced by separate BSs. Rather than covering a large area by using a single, high-powered BS, cellular systems employ many lower-powered BSs each of which covers a small area. This allows for the reuse of the frequency bands in cells which are not too close to each other, increasing mobile user capacity with a limited spectrum allocation.

Traditional narrowband cellular systems require the cochannel interference level to be low. Careful design of frequency reuse among cells is then crucial to maintain cochannel interference at the required low level. The price of low interference, however, is a low frequency reuse factor: only a small portion of the system frequency band can be used in each cell. More recent wideband approaches allow full frequency reuse in each cell, but the cost of that is increased intercell interference. In both approaches, the capacity of a cell in a cellular network, with six surrounding cells, is much less than that of a single cell operating in an intercell interference-free environment. In this chapter, we survey an approach that allows the cell with neighbors to achieve essentially the same capacity as the interference-free cell.

Introduction

The continually increasing number of users and the rise of resource-demanding services require a higher link data rate than the one that can be achieved in current wireless networks. Wireless cellular networks, in particular, have to be designed and deployed with unavoidable constraints on the limited radio resources such as bandwidth and transmit power. As the number of new users increases, finding a solution to meet the rising demand for high data rate services with the available resources has became a challenging research problem. The primary objective of such research is to find solutions that can improve the capacity and utilization of the radio resources available to the service providers. While in traditional infrastructure networks the upper limit of the source destination (S–D) link's data capacity is determined by the Shannon capacity, advances in radio transceiver techniques such as multiple-input multiple-output (MIMO) architectures and cooperative or relay-assisted communications have led an enhancement in the capacity of contemporary systems.

In the MIMO technique the diversity relies on uncorrelated channels, and is achieved by employing multiple antennas at the receiver side, the transmitter side, or both, and by sufficiently separating the multiple antennas (of same polarization). The MIMO technique can be used to increase the robustness of a link as well as the link's throughput. Unfortunately, the implementation of multiple antennas in most modern mobile devices may be challenging due to their small sizes.

Introduction

The spectral efficiency of existing cellular networks is limited by interference. In cellular mobile networks, the dominant interference comes from adjacent cells. This is especially true when the users are located near the cell edges where the interference from the adjacent cells is very strong. By getting the adjacent base stations (BS) to cooperate, spatial antenna diversity in each BS can be utilized to cancel the interference. To obtain BS cooperation, multiple BSs share information about the transmitted messages to their respective users and wireless channels via a backbone network. Each BS can transmit either a single symbol stream or multiple symbol streams to its respective mobile station (MS). Individual BSs and MSs are equipped with multiple transmit and receive antennas, respectively. Each BS transmitter uses the transmitted signal information from other BSs and wireless channel conditions to precode its own signal. The precoded signal for each BS is broadcast through all BS transmit antennas in the same frequency band and time slots. The precoding operation and transmit receive antenna coefficients are chosen in such a way as to minimize the interference coming from other BS transmissions. The calculated receive antenna coefficients are then sent from the transmitter to the receiver through a wireless channel prior to the data transmission. In this chapter, we consider the use of a cooperative BS system to eliminate the interference in cellular networks.

Introduction

Wireless cellular networks have to be designed and deployed with unavoidable constraints on the limited radio resources such as bandwidth and transmit power. With the boom in the number of new users and the introduction of new wireless cellular services that require a large bandwidth or data rate, the demand for these resources, however, is rising exponentially. Finding a solution to meet this increasing demand with the available resources is a challenging research problem. The primary objective of such research is to find solutions that can improve the capacity and utilization of the radio resources that are available to the service providers. Based on the concept of relay channels, cooperative communication has been found to greatly enhance the performance of a resource-constrained wireless network. It can achieve benefits similar to those of the multipleinput multiple-output (MIMO) system without the need for multiple antennas at each node. By allowing users to cooperate and relay each other's messages to the destination, cooperative communication also improves the transmission quality. Because of the limited power and bandwidth resources of the cellular networks and the multipath fading nature of the wireless channels, the idea of cooperation is particularly attractive for wireless cellular networks.

Proposed cooperative schemes or strategies, such as decode-and-forward (DF), amplify-and-forward (AF), and coded cooperation, usually involve two steps of operation.

Introduction

The cellular structure is a central concept in wireless network deployment. A wireless cellular network comprises base stations geographically located at the centre of each cell serving users within the cell boundary. The assignment of the users to the base stations depends on the relative channel propagation characteristics. As a mobile device can usually receive signals from multiple base stations, the mobile is typically assigned to the base station with the strongest channel gain. Signals from all other base stations are regarded as intercell interference. However, at the cell edge, it is often the case that the propagation path-losses from two or more base stations are similar. In this case, the signal-to-noise-and-interference ratio (SINR) could be close to 0 dB, even if the mobile is assigned to the strongest base station. To avoid excessive intercell interference in these cases, traditional cellular networks employ a fixed frequency reuse pattern so that neighboring base stations do not share the same frequency. In this manner, neighboring cells are separated in frequency so that cell-edge users do not interfere with each other.

The traditional fixed frequency reuse schemes are effective in minimizing intercell interference, but are also resource intensive in the sense that each cell requires a substantial amount of nonoverlapping bandwidth, so that only a fraction of the total bandwidth can be made available for each cell. Consequently, the standardization processes for future wireless systems have increasingly targeted maximal frequency reuse, where all cells use the same frequency everywhere.

Introduction

In conventional cellular systems, cochannel interference is a serious issue that degrades system performance. The spectral efficiency of cellular networks is fundamentally limited by the interference between cells and users sharing the same channel for both downlink and uplink. Generally, there are two kinds of cochannel interference: intracell interference and intercell interference.

The intracell interference can be resolved by allocating orthogonal frequency resources. To mitigate intercell interference, there are several general approaches such as frequency reuse, cell sectoring, and spread spectrum transmission. The most commonly used technique is to avoid using the same set of frequencies in neighboring cells. This approach leads to the decrease of the number of available channels within each cell.

Universal frequency reuse, i.e., reuse factor of 1, is preferred for future broadband wireless communications systems, such as the Third Generation Partnership Project (3GPP) long-term evolution (LTE) and worldwide interoperability for microwave access (WiMAX). In the orthogonal frequency-division multiple access (OFDMA) systems, which do not have processing gain as the code-division multiple access (CDMA) system, how to achieve the goal of both universal frequency reuse and reducing intercell interference is a key challenge.

The concept of fractional frequency reuse (FFR) has been suggested to improve spectrum efficiency by applying reuse partition techniques, in which the inner region of the cell is assigned the whole frequency spectrum and the outer region is only assigned a small fraction of the frequency spectrum.

Introduction

A cellular communication system is designed based on the concept of frequency reuse, in which the same frequency resources are reused at a certain distance from a cell site. Traditionally, a cellular system has been composed of cell sites operating independently except in some inevitable scenarios like handover. Independent operation of each cell site makes it possible to deploy a wireless system at a low cost, while maintaining the quality of the voice service. However, due to the large amount of interference from neighboring cell sites, cell-edge users experience bad channel conditions. Furthermore, the cell-edge interference becomes more severe, when the frequency reuse factor is 1, which is a common assumption for cellular systems designed for high capacity. Therefore, with the conventional cellular designs, it is difficult to achieve high data throughput for users located at cell edges.

However, as the need for high-speed data communication increases, cooperative communications between the neighboring cell sites and UEs are being more intensively studied not only in academia but also in industry. One of the main focuses of these studies is to increase the data throughput for the cell-edge UEs. To increase the throughput of the cell-edge UEs, neighboring eNodeBs cooperate to enhance the signal quality and/or decrease the interference level. Coverage extension through a wireless relay is another research focus of cooperative communication. Interference management and cooperation between eNodeBs are important issues in a heterogeneous network.

Introduction

In this chapter, we consider space-time coding strategies for multiple-relay cooperative systems that effectively harness available spatial diversity. More specifically, the goal is to examine ways to forward signals efficiently from multiple relays to the destination while addressing the important practical issue of synchronization among the relays. We assume a general two-phase transmission protocol as illustrated in Figure 6.1. In the first phase of the protocol, the source broadcasts a message which is received by the relays and (possibly) the destination. During the second transmission phase, a subset of the relays, possibly in conjunction with the source, transmits additional information to the destination. This protocol is useful in practical scenarios where signals received at the destination due to transmissions directly from the source (Phase 1) will not carry enough useful information because of noise, fading, and/or interference.

It is expected that Phase 2 will dramatically increase the reliability of the system, but if the symbols cannot be decoded correctly after the second phase, the protocol can restart by returning to Phase 1 or Phase 2.

The primary problem associated with forwarding information from multiple relays to the destination is determining how the information should be spread out among the relays over space and time. This is analogous to the classic spacetime coding problem in point-to-point multiple-transmit-antenna systems, and so it is often called the distributed space-time coding problem.

Introduction

Future communication systems will be decentralized and ad-hoc, hence allowing various types of network mobile terminals to join and leave. This makes the whole system vulnerable and susceptible to attacks. Anyone within communication range can listen to and possibly extract information. While these days we have numerous cryptographic methods to ensure high-level security, there is no system with perfect security on the physical layer. Therefore, the physical layer security is attracting renewed attention. Of special interest is so-called information-theoretic security since it concerns the ability of the physical layer to provide perfect secrecy of the transmitted data.

In this chapter, we present different scenarios of a decentralized system that protects the broadcasted data on the physical layer and makes it impossible for the eavesdropper to receive the packets no matter how computationally powerful the eavesdropper is. In approaches where information-theoretic security is applied, the main objective is to maximize the rate of reliable information from the source to the intended destination, while all malicious nodes are kept ignorant of that information. This maximum reliable rate under which a perfectly secret communication is possible is known as the secrecy capacity.

This line of work was pioneered by Aaron Wyner, who defined the wiretap channel and established the possibility of secure communication links without relying on private (secret) keys.