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This book provides an introduction to Bluetooth programming, with a specific focus on developing real code. The authors discuss the major concepts and techniques involved in Bluetooth programming, with special emphasis on how they relate to other networking technologies. They provide specific descriptions and examples for creating applications in a number of programming languages and environments including Python, C, Java, GNU/Linux, Windows XP, Symbian Series 60, and Mac OS X. No previous experience with Bluetooth is assumed, and the material is suitable for anyone with some programming background. The authors place special emphasis on the essential concepts and techniques of Bluetooth programming, starting simply and allowing the reader to quickly master the basic concepts before addressing advanced features.
Written to address technical concerns that mobile developers face regardless of the platform (J2ME, WAP, Windows CE, etc.), this 2005 book explores the differences between mobile and stationary applications and the architectural and software development concepts needed to build a mobile application. Using UML as a tool, Reza B'far guides the developer through the development process, showing how to document the design and implementation of the application. He focuses on general concepts, while using platforms as examples or as possible tools. After introducing UML, XML and derivative tools necessary for developing mobile software applications, B'far shows how to build user interfaces for mobile applications. He covers location sensitivity, wireless connectivity, mobile agents, data synchronization, security, and push-based technologies, and finally homes in on the practical issues of mobile application development including the development cycle for mobile applications, testing mobile applications, architectural concerns, and a case study.
Future generations of wireless networks will place great demands on the performance of radio access technology. This book describes the features of various mobile access technologies and assesses their strengths and weaknesses. In particular, it describes the underlying principles and practical implementation schemes for time division duplexing (TDD). The book begins with an overview of next-generation wireless systems. It then describes the basics of duplex communication modes, interference in cellular systems, and multiple user access techniques. Focusing on TDD systems, dynamic channel assignment algorithms are discussed, as are multi-hop communications schemes, radio resource management, interference cancellation, and smart antennas. Real-world examples from UMTS, wireless LAN, and Bluetooth systems are described. The book is aimed at all those involved in the design and implementation of wireless systems, as well as at graduate students and researchers working in the area of wireless communications. For more information visit www.cambridge.org/9781107407794.
Do you need to understand the solutions that allow multimedia communications between mobile networks and fixed wireless communications? If so, this practical book, presenting the fundamentals of individual fixed and mobile wireless technologies in terms of architectures, standards, management capabilities and quality of service issues, is essential reading. Adopting the term Fixed-Mobile Convergence (FMC), an analysis of the interworking between cellular networks and a variety of wireless technologies, such as WLAN, WiMAX, RFID and UWB, is provided. An in-depth study of the convergent solutions offered by UMA and IMS is also given, together with up-to-date information about products, vendors and current service offerings. You'll also find criteria for analyzing and evaluating fixed-mobile convergent products and services, and numerous diagrams and feature/component tables. This practical text is ideal for engineers and practitioners in the field of telecommunications and wireless communications, as well as graduate students of electrical and computer engineering.
Wireless sensor networks promise an unprecedented fine-grained interface between the virtual and physical worlds. They are one of the most rapidly developing information technologies, with applications in a wide range of fields including industrial process control, security and surveillance, environmental sensing, and structural health monitoring. Originally published in 2005, this book provides a detailed and organized survey of the field. It shows how the core challenges of energy efficiency, robustness, and autonomy are addressed in these systems by networking techniques across multiple layers. The topics covered include network deployment, localization, time synchronization, wireless radio characteristics, medium-access, topology control, routing, data-centric techniques, and transport protocols. Ideal for researchers and designers seeking to create algorithms and protocols and engineers implementing integrated solutions, it also contains many exercises and can be used by graduate students taking courses in networks.
Embedded network systems (ENS) provide a set of technologies that can link the physical world to large-scale networks in applications such as monitoring of borders, infrastructure, health, the environment, automated production, supply chains, homes and places of business. This book details the fundamentals for this interdisciplinary and fast-moving field. The book begins with mathematical foundations and the relevant background topics in signal propagation, sensors, detection and estimation theory, and communications. Key component technologies in ENS are discussed: synchronization and position localization, energy and data management, actuation, and node architecture. Ethical, legal and social implications are addressed. The final chapter summarizes some of the lessons learned in producing multiple ENS generations. A focus on fundamental principles together with extensive examples and problem sets make this text ideal for use on graduate courses in electrical engineering and computer science. It will also appeal to engineers involved in the design of ENS.
The design of an efficient multiple access and multiplexing scheme is more challenging on the uplink than on the downlink due to the many-to-one nature of the uplink transmissions. Another important requirement for uplink transmissions is low signal peakiness due to the limited transmission power at the user equipment (UE). The current 3G systems use the wideband code division multiple access (WCDMA) scheme both in the uplink and in the downlink. In a WCDMA downlink (Node-B to UE link) the transmissions on different Walsh codes are orthogonal when they are received at the UE. This is due to the fact that the signal is transmitted from a fixed location (base station) on the downlink and all the Walsh codes received are synchronized. Therefore, in the absence of multi-paths, transmissions on different codes do not interfere with each other. However, in the presence of multi-path propagation, which is typically the case in cellular environments, the Walsh codes are no longer orthogonal and interfere with each other resulting in inter-user and/or inter-symbol interference (ISI).
The problem is even more severe on the uplink because the received Walsh codes from multiple users are not orthogonal even in the absence of multi-paths. In the uplink (UE to Node-B link), the propagation times from UEs at different locations in the cell to the Node-B are different. The received codes are not synchronized when they arrive at the Node-B and therefore orthogonality cannot be guaranteed.
In the previous chapter, we discussed how multiple transmission antennas can be used to achieve the diversity gain. The transmission diversity allows us to improve the link performance when the channel quality cannot be tracked at the transmitter which is the case for high mobility UEs. The transmission diversity is also useful for delay-sensitive services that cannot afford the delays introduced by channel-sensitive scheduling. The transmission diversity, however, does not help in improving the peak data rates as a single data stream is always transmitted. The multiple transmission antennas at the eNB in combination with multiple receiver antennas at the UE can be used to achieve higher peak data rates by enabling multiple data stream transmissions between the eNB and the UE by using MIMO (multiple input multiple output) spatial multiplexing. Therefore, in addition to larger bandwidths and high-order modulations, MIMO spatial multiplexing is used in the LTE system to achieve the peak data rate targets. The MIMO spatial multiplexing also provides improvement in cell capacity and throughput as UEs with good channel conditions can benefit from multiple streams transmissions. Similarly, the weak UEs in the system benefit from beam-forming gains provided by precoding signals transmitted from multiple transmission antennas.
MIMO capacity
A MIMO channel consists of channel gains and phase information for links from each of the transmission antennas to each of the receive antennas as shown in Figure 7.1.
The LTE system requirements mandate significant improvement in performance relative to the Release 6 HSPA system. In particular, the spectrum efficiency improvement targets for the downlink are three to four times that of the Release 6 HSPA system. The spectral efficiency improvement targets for the uplink are relatively modest with two to three times improvement over Release 6 HSPA. One of the reasons for lower improvement targets for the uplink is that the same antenna configuration is assumed for the LTE system and Release 6 HSPA system. On the other hand for downlink, LTE assumes two transmit antennas while Release 6 HSPA baseline system assumes only one transmit antenna at the Node-B. Similar targets are set for the peak data rates and also cell-edge performance improvements. The spectral efficiency target for the MBSFN, which is a downlink only service, is set at an absolute number of 1 bps/Hz.
An evaluation methodology specifying the traffic models and simulation parameters was developed for assessing the performance of the LTE and Release 6 HSPA systems. The goal of the evaluation methodology is to provide a fair comparison as all the parties participating in the simulations campaign can evaluate performance under the same set of assumptions. In this chapter, we describe LTE simulations methodology and provide relative performance of the LTE system and Release 6 HSPA system.
Traffic models
In this section, we discuss various traffic models considered in the performance verification. The traffic mix scenarios are given in Table 19.1.
With the exception of a scheduling request, all uplink control consists of feedback information to support downlink transmissions. The channel quality feedback is provided to support downlink channel-sensitive scheduling and link adaptation. The rank and precoding matrix indication is used for selecting a downlink MIMO transmission format. The ACK/NACK signaling provides feedback on downlink hybrid ARQ transmissions. In contrast to uplink control, the only feedback information on the downlink is ACK/NACK signaling to support uplink hybrid ARQ operation and transmission power control (TPC) commands to support uplink power control. The reason for this asymmetry is simply the fact that both the uplink and the downlink schedulers resides in the eNB. Therefore, the bulk of downlink signaling involves uplink and downlink scheduling grants that convey information on the transmission format and resource allocation for both the uplink and downlink transmissions. In order to support the uplink channel-sensitive scheduling, the uplink channel quality is estimated from the uplink sounding reference signal (SRS).
The three downlink control channels transmitted every subframe are physical control format indicator channel (PCFICH), physical downlink control channel (PDCCH) and physical hybrid ARQ indicator channel (PHICH). The PCFICH carries information on the number of OFDM symbols used for PDCCH. The PDCCH is used to inform the UEs about the resource allocation as well as modulation, coding and hybridARQ control information. Since multiple UEs can be scheduled simultaneously within a subframe in a frequency or space division multiplexed fashion multiple PDCCHs each carrying information for a single UE are transmitted.
The goal of power control is to transmit at the right amount of power needed to support a certain data rate. Too much power generates unnecessary interference, while too little power results in an increased error rate requiring retransmissions and hence resulting in larger transmission delays and lower throughputs. In a WCDMA system, power control is important particularly in the uplink to avoid the near–far problem. This is because the uplink transmissions are nonorthogonal and very high signal levels from cell-center UEs can overwhelm the weak signals received from cell-edge UEs. Therefore, a very elaborate power control mechanism based on the fast closed-loop principle is used in the WCDMA system. Similarly, power control is used for the downlink of WCDMA systems to support the fixed rate delay-sensitive voice service. However, for high-speed data transmission in WCDMA/HSPA systems, transmissions are generally performed at full power and link adaptation is preferably used to match the data rate to the channel conditions.
The LTE uplink uses orthogonal SC-FDMA access and hence the near–far problem of WCDMA does not exist. However, high levels of interference from neighboring cells can still limit the uplink coverage if UEs in the neighboring cells are not power controlled. The cellular systems are generally coverage limited in the uplink due to limited UE transmit power. The increased levels of interference from neighboring cells increase Interference over Thermal (IoT) limiting coverage at the desired cell. Therefore, uplink power control is beneficial in an orthogonal uplink access as well.
The LTE system supports fast dynamic scheduling on a per subframe basis to exploit gains from channel-sensitive scheduling. Moreover, advanced techniques such as link adaptation, hybrid ARQ and MIMO are employed to meet the performance goals. A set of physical control channels are defined in both the uplink and the downlink to enable the operation of these techniques. In order to support channel sensitive scheduling and link adaptation in the downlink, the UEs measure and report their channel quality information back to the eNB. Similarly, for downlink hybrid ARQ operation, the hybrid ARQ ACK/NACK feedback from the UE is provided in the uplink.
Two types of feedback information are required for MIMO operation, the first is MIMO rank information and the second is preferred precoding information. It is well known that even when a system supports N × N MIMO, rank-N or N MIMO layers transmission is not always beneficial. The MIMO channel experienced by a UE generally limits the maximum rank that can be used for transmission. In general, for weak users in the system, a lower rank transmission is preferred over a higher rank transmission. This is because at low SINR, the capacity is power limited and not degree-of-freedom limited and therefore multiple layers transmission is not helpful. Moreover, when the antennas are correlated, the channel matrix is rank deficient leading to a single layer or rank-1 transmission. Therefore, the system should support a variable number of MIMO layers transmission to maximize gains from MIMO.
An important requirement for the LTE system is improved cell-edge performance and throughput. This is to provide some level of service consistency in terms of geographical coverage as well as in terms of available data throughput within the coverage area. In a cellular system, however, the SINR disparity between cell-center and cell-edge users can be of the order of 20 dB. The disparity can be even higher in a coverage-limited cellular system. This leads to vastly lower data throughputs for the cell-edge users relative to cell-center users creating a large QoS discrepancy.
The cell-edge performance may be either noise-limited or interference-limited. In a noise-limited situation that typically occurs in large cells in rural areas, the performance can generally be improved by providing a power gain. The power gain can be achieved by using high-gain directional transmit antennas, increased transmit power, transmit beam-forming and receive beam-forming or receive diversity, etc. The total transmit power is generally dictated by regulatory requirements and hence limits the coverage gains possible due to increased transmit power.
The situation is different in small cells interference-limited cases, where, in addition to noise, inter-cell interference also contributes to degraded cell-edge SINR. In this case, providing a transmit power gain may not help because as the signal power goes up, the interference power also increases. This is assuming that with a transmit power gain all cells in the system will operate at a higher transmit power.
Specification of a propagation channel model is of foremost importance in the design of a wireless communication system. A propagation model is used to predict how the channel affects the transmitted signal so that transmitters and receivers that best compensate for the channel's corrupting behaviors can be developed. A propagation model is also used as a basis for performance evaluation and comparison of competing wireless technologies. An example of such propagation models is ITU-R channel models that were developed for IMT-2000 system evaluation. A wireless propagation channel model needs to be refined as new system parameters (e.g. larger bandwidths and new frequency bands) or radio technologies exploiting new characteristics of the channel such as multi-antenna schemes are introduced. A well-defined channel model allows for the assessing of the system performance under new parameters as well as gains due to introduction of new radio technologies. The performance of multi-antennas technologies, for example, depends upon the spatial correlations between antennas. As ITU-R channel models do not characterize the spatial correlations, using these propagation models may lead to overestimating the gains of multi-antenna techniques. In order to provide a reasonable propagation platform for multi-antenna techniques evaluation, the spatial channel model (SCM) was developed. The SCM defines a ray-based model derived from stochastic modeling of scatters and therefore allows to model spatial correlations required for evaluation of multi-antenna techniques.
The current 3G systems use a wideband code division multiple access (WCDMA) scheme within a 5 MHz bandwidth in both the downlink and the uplink. In WCDMA, multiple users potentially using different orthogonal Walsh codes are multiplexed on to the same carrier. In a WCDMA downlink (Node-B to UE link), the transmissions on different Walsh codes are orthogonal when they are received at the UE. This is due to the fact that the signal is transmitted from a fixed location (base station) on the downlink and all the Walsh codes are received synchronized. Therefore, in the absence of multi-paths, transmissions on different codes do not interfere with each other. However, in the presence of multi-path propagation, which is typical in cellular environments, the Walsh codes are no longer orthogonal and interfere with each other resulting in inter-user and/or inter-symbol interference (ISI). The multi-path interference can possibly be eliminated by using an advanced receiver such as linear minimum mean square error (LMMSE) receiver. However, this comes at the expense of significant increase in receiver complexity.
The multi-path interference problem of WCDMA escalates for larger bandwidths such as 10 and 20 MHz required by LTE for support of higher data rates. This is because chip rate increases for larger bandwidths and hence more multi-paths can be resolved due to shorter chip times. Note that LMMSE receiver complexity increases further for larger bandwidths due to increase of multi-path intensity. Another possibility is to employ multiple 5 MHz WCDMA carriers to support 10 and 20 MHz bandwidths.
A cell search procedure is used by the UEs to acquire time and frequency synchronization within a cell and detect the cell identity. In the LTE system, cell search supports a scalable transmission bandwidth from 1.08 to 19.8 MHz. The cell search is assumed to be based on two signals transmitted in the downlink, the synchronization signals and broadcast control channel (BCH).
The primary purpose of the synchronization signals is to enable the acquisition of the received symbol timing and frequency of the downlink signal. The cell identity information is also carried on the synchronization signals. The UE can obtain the remaining cell/system-specific information from the BCH. The primary purpose of the BCH is to broadcast a certain set of cell and/or system-specific information. After receiving synchronization signals and BCH, the UE generally acquires information that includes the overall transmission bandwidth of the cell, cell ID, number of transmit antenna ports and cyclic prefix length, etc.
The synchronization signals and BCH are transmitted using the same minimum bandwidth of 1.08MHz in the central part of the overall transmission band of the cell. This is because, regardless of the total transmission bandwidth capability of an eNB, a UE should be able to determine the cell ID using only the central portion of the bandwidth in order to achieve a fast cell search.
The reference signals are used for channel quality measurements for scheduling, link adaptation and handoff, etc. as well as for data demodulation.
The LTE system design goal is optimization for low mobile speeds ranging from stationary users to up to 15 km/h mobile speeds. At these low speeds, eNode-B can exploit multi-user diversity gains by employing channel sensitive scheduling. For downlink transmissions, UEs feed back downlink channel quality information back to the eNode-B. Using a channel quality sensitive scheduler such as proportional fair scheduler, eNode-B can serve a UE on time-frequency resources where it is experiencing the best conditions. It is well known that when multi-user diversity can be exploited, use of other forms of diversity such as transmit diversity degrades performance. This is because multi-user diversity relies on large variations in channel conditions while the transmit diversity tries to average out the channel variations.
The LTE system is also required to support speeds ranging from 15–120 km/h with high performance. Actually, the system requirements state mobility support up to 350 km/h or even up to 500 km/h. At high UE speeds, the channel quality feedback becomes unreliable due to feedback delays. When reliable channel quality estimates are not available at eNode-B, channel-sensitive scheduling becomes infeasible. Under these conditions, it is desired to average out the channel variations by all possible means. Moreover, the channel sensitive scheduler has to wait for the right (good) channel conditions when a UE can be scheduled. This introduces delays in packet transmissions. For delay-sensitive traffic such as VoIP application, channel-sensitive scheduling cannot be used under most conditions.