Introduction

Long Term Evolution (LTE) of the Universal Mobile Telecommunications System (UMTS) was developed to ensure that the technology remains competitive for the foreseeable future. Requirements for the LTE Rel-8 system include improved system capacity and coverage, improved user experience through higher data rates and reduced latency, reduced deployment and operating costs, and seamless integration with existing systems. The requirements may be broken down into different categories – system performance, latency, coverage, deployment, and complexity. To achieve these goals, new designs for the radio access networks and system architectures are needed.

The next-generation wireless broadband technology is changing the way we work, live, learn, and communicate through effective use of state-of-the-art mobile broadband technology. The packet-data-based revolution started around 2000 with the introduction of 1x Evolved Data Only (1xEV-DO) and 1x Evolved Data Voice (1xEV-DV) in 3GPP2 and High Speed Downlink Packet Access (HSDPA) in 3GPP. The wireless broadband fourth-generation technology (4G) is an evolution of the packet-based 3G system and provides a comprehensive evolution of the Universal Mobile Telecommunications System specifications so as to remain competitive with other broadband systems such as 802.16e (WiMAX). Specification work was started in late 2004 on Long Term Evolution (LTE) of the UMTS Terrestrial Radio Access and Radio Access Network intended for commercial deployment in 2010. Two main components constitute the LTE system architecture — the Evolved Universal Terrestrial Radio Access Network (E-UTRAN) and the Evolved Packet Core (EPC).

Introduction

OFDM systems naturally benefit from the use of multi-antenna systems (MASs), which improves the capacity and coverage of the LTE system significantly. In the downlink, four different multi-antenna transmission techniques are supported – transmit diversity, closed-loop spatial multiplexing using precoding codebooks, open-loop spatial multiplexing, and user-specific reference-symbol-based beamforming [1]–[3]. Spatial multiplexing can be used to support single-user MIMO (SU-MIMO), whereby multiple data streams (or spatial layers in LTE terminology) are transmitted to the same user simultaneously in the same time–frequency resource, or multi-user MIMO (MU-MIMO), whereby multiple data streams (or layers) are transmitted to different users simultaneously using the same time–frequency resource. A significant gain in system capacity can be achieved with MIMO [4]. In the uplink, SU-MIMO is not possible since the UE can only transmit on one antenna. However, MU-MIMO can be supported in the uplink. In this chapter, a comprehensive description of various multi-antenna technologies for Rel-8 downlink and uplink is presented, together with details of their performance.

Introduction

Rel-8 LTE delivers improved system capacity and coverage, improved user experience through higher data rates, reduced-latency deployment, and reduced operating costs, and seamless integration with existing systems. Further enhanced requirements, however, were approved in 2008 to allow LTE to be approved as a radio technology for International Mobile Telecommunications-Advanced (IMT-Advanced). IMT-Advanced requirements are defined by the International Telecommunication Union, which is an organization that provides globally accepted standards for telecommunications. This further advancement for LTE is known as LTE-Advanced (LTE-A). The LTE-A requirements are shown inand focus mainly on improvements in system performance and latency reduction. From Table 6.1, it can be seen that the target cell and user spectral efficiencies have increased significantly. Peak data rates of 1 Gbps in the downlink and 500 Mbps in the uplink must be supported. Target latencies have been significantly reduced as well. In addition to advancements in system performance, deployment and operating-cost-related goals were also introduced. They include support for cost-efficient multi-vendor deployment, power efficiency, efficient backhaul, open interfaces, and minimized maintenance tasks. A comprehensive list of LTE-A requirements can be found in [1].

Introduction

LTE uplink provides an increase in capacity (both sector and cell-edge) by a factor of 2–3 compared with previous UMTS high-speed uplink packet access (HSUPA) systems at substantially less latency. This enables efficient support of high-rate data services such as FTP, HDTV broadcast, and HTTP as well as delay-sensitive services such as VoIP and video streaming. In LTE, several technological enhancements have been introduced in the uplink air interface to enable this improvement. They include orthogonal uplink transmission from intra-cell users, frequency-selective scheduling, shorter subframe size, support for 64-QAM modulation, multi-user spatial multiplexing, subframe bundling, semi-persistent scheduling, fractional power control, inter-cell interference control, and efficient control channels.

Introduction

LTE Rel-8 and WiMAX are the two main wireless broadband technologies based on OFDM which are currently being commercialized. Both of these technologies are being enhanced (LTE-Advanced and 802.16m) so as to support higher peak rates, higher throughput and coverage, and lower latencies, resulting in a better user experience. Further, both LTE-Advanced and 802.16m were approved by the ITU as IMT-Advanced technology. Also several operators are considering deploying both these technologies or migrating their existing WiMAX system to LTE or 802.16m. In this chapter, these two main broadband technologies are compared with respect to their features and system performance. Also, WiMAX and LTE co-existence and migration scenarios are briefly discussed.

Introduction

In this chapter the details of LTE downlink transmission are discussed. The LTE downlink air interface uses the OFDM multiple-access technique described in Chapter 2. The use of OFDM transmission technology provides significant advantages over other radio transmission techniques. They include high spectral efficiency, support for broadband data transmission, the absence of intra-cell interference (i.e. multiple users in the same cell can share the same subframe without interfering with each other), resistance to inter-symbol interference arising from multipath operation, natural support for MIMO schemes, a low-complexity receiver, and support for frequency-domain techniques such as frequency-selective scheduling, a single-frequency network, and soft fractional frequency reuse. In addition to OFDM, LTE also utilizes several other features to enhance system performance and user experience. They include short frame size to minimize latency, a single-frequency network to provide high-data-rate broadcast services, VoIP support to increase voice capacity, coverage for very large cells, and coverage for high-speed users (up to 350 km/h) [1]–[2].

System analysis and performance metrics

In this book, system-level performance results based on comprehensive system simulations of cellular networks are provided. An example of the cellular layout used for system simulation is shown in Figure A.1. This is a typical 19-site, 57-cell system using a hexagonal grid. In this case, a cell is viewed as a sector of the physical site. However, in LTE each cell is treated as an independent eNB. The spacing between each site and the next is dependent on the deployment scenario. For example, in urban micro-cell deployment, the inter-site distance is 200 m. Users are dropped randomly into the simulation space. For instance, in urban micro-cell deployment, 570 users are randomly dropped. After the users have been dropped, long-term radio characteristics such as pathloss and shadowing are calculated. Users are then assigned to the cell using the minimum pathloss as the cell-selection criterion. For the urban micro-cell example, on average, approximately 10 users will be associated with each cell.

Genesis of wireless technology

The digital cellular technology revolution started with the introduction of GSM (Groupe Special Mobile) in the late 1980s. The GSM technology was based on time-division multiple access (TDMA) and was capable of supporting data services of up to 9.6 kbps. In the early 1990s, IS-95, a standard based on code-division multiple-access (CDMA) technology was introduced. This offered data rates of up to 14.4 kbps and improved spectral efficiencies over a GSM system. Subsequently, both these technologies evolved over time, with each phase offering higher peak rates and improved sector/edge spectral efficiencies. Both GSM and IS-95 CDMA evolved in different phases. In 1997, the Generalized Packet Radio System (GPRS) based on packet data instead of circuit data was standardized, followed by Enhanced Data Rates for Global Evolution (EDGE). Also, at the end of 1998, the Third-Generation Partnership Project (3GPP) was started. This was responsible for defining a third-generation (3G) wideband CDMA (WCDMA) standard based on the evolved GSM core network. At the same time the GSM standardization work was moved from ETSI SMG2 to 3GPP, and was called GERAN. Similarly, in the United States the IS-95 standard evolved to cdma2000 under the umbrella of Third-Generation Partnership Project 2 (3GPP2).

In this chapter, we give an outlook onto some further issues connected to CoMP, where major research is still ongoing. In Section 15.1, it is shown that CoMP can also be used for purposes other than spectral efficiency and fairness increase, namely for the localization of terminals in cases where GPS is not available. Section 15.2 then discusses the usage of CoMP in conjunction with relaying, showing that both technologies can complement each other well in providing efficient and ubiquitous mobile broadband access. Section 15.3 discusses how the planning and optimization of future networks will be affected due to the introduction of CoMP, while Section 15.4 addresses one essential yet unanswered aspect of CoMP: How does CoMP perform in terms of energy efficiency?

Using CoMP for Terminal Localization

Location information about user equipments (UEs) is a valuable characteristic and can be exploited in various layers of mobile communications systems. At the application layer, the availability of location information provides new market opportunities by enabling location based services. In lower system layers, performance improvements can be achieved using location information for optimizing handover or radio resource management for example. Nowadays, an increasing number of UEs are equipped with global positioning system (GPS) chipsets, which allows location determination at the terminals themselves. Satellite based localization reaches its limits for instance in urban canyon environments or even indoors. However, these environments typically show high user densities.

Motivation

Mobile communication has gained significant importance in today's society. As of 2010, the number of mobile phone subscribers has surpassed 5 billion [ABI10], and the global annual mobile revenue is soon expected to top $1 trillion [Inf10]. While these numbers appear promising for mobile operators at first sight, the major game-changer that has come up recently is the fact that the market is more and more driven by the demand for mobile data traffic [Cis10]. This is simply because Moore's law in semiconductors leads to continuously more powerful mobile devices with larger storage capacity, which in the era of Web 2.0 require regular synchronization with the Internet. Consequently, Moore's law can also be found in the increase of data rates in wireless communications, as illustrated in Fig. 1.1. The main challenge, however, is that mobile users tend to expect the fast and cheap Internet access that they are used from their fixed lines (e.g. ADSL), but anytime and anywhere while being on the move. This puts mobile operators under the pressure to respond to the increasing traffic demand and provide a more homogeneous quality of experience (QoE) over the area (often referred to as improved fairness), while continuously decreasing cost per bit - and addressing the more and more crucial issue of energy efficiency [FMBF10].

The Mobile Internet - A Success Story so far

When 3G was launched initially with WCDMA technology (Release 99), it was rather a disappointment with not many services being successful. Some years later, the mobile Internet took off when a number of factors came together:

• HSPA as a technological evolution of 3G with low latency and higher data rate

• Attractive flat-rate price plans by mobile operators

• Availability of mobile broadband hardware in terms of dongles and built-in 3G modules in notebooks

• Smart phones with attractive user interfaces, e.g., iPhone, Android

• Complete country-coverage with HSPA and HSPA+ by mobile operators.

This take-up of the mobile Internet generated substantial additional revenues for mobile operators, at a time when voice and text message revenues started to decline in saturated markets such as Europe. For example, Vodafone had a data revenue growth of 19% in financial year 2009/2010, with more than €4 Billion generated by non-SMS data. Today, only 11% of phones are smartphones, but by 2013 it is expected that more than a third of all active phones within the Vodafone network will be smartphones.

This data revenue growth comes along with a cost for mobile operators - namely data traffic growth. Fig. 2.1 shows the actual and projected traffic growth for Vodafone's European networks in Petabytes/year [Vod10]. It can be seen that data traffic has substantially surpassed voice traffic.

In this chapter, we now look into algorithm implementation aspects connected to CoMP. In Section 10.1, the issue of numerically robust and flexible multicell precoding is addressed, while Section 10.2 looks into the performance of interference rejection combining filters under practical conditions.

Robust and Flexible Base Station Precoding Implementation

As we have seen in Sections 6.3 and 6.4, spectral efficiency can be significantly increased if downlink CoMP schemes based on multi-cell joint signal processing are applied. Here, multiple base stations (BSs) perform a joint and coherent transmission towards multiple user equipments (UEs). Especially cell-edge users with symmetric links gain from the joint transmission (JT) with minimized inter-cell and inter-user interference compared to conventional cellular mobile networks.

In a cellular system, a spatial downlink resource allocation algorithm may switch between a single link transmission comprising one BS and one UE, a single BS multi-user scenario or finally a multi-cell joint transmission. The precoder must be able to cope with different system setups or matrix dimensions respectively. Such an implementation requires a higher signal processing flexibility as compared to non-cooperative setups. Physical link parameters like line-of-sight (LOS), non-LOS, or correlated transmit and receive antenna patterns influence the CoMP multi-user MIMO (MU-MIMO) eigenvalue spread and finally the spatial diversity and multiplexing gains.

Furthermore, in real-time hardware, the link parameters are related to finite precision effects.