Browsing by Subject "Wireless communication systems"

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Adaptive antenna systems for mobile broadband communications
(2002) Dong, Liang; Ling, Hao; Xu, Guanghan
Mobile broadband communication is experiencing rapid growth in technology, markets and range of services. This rapid growth has driven the recent surge of research and development activities for high-data-rate/high-mobility wireless systems, with improved network performance and enhanced economics. One technology thrust in wireless communications is the use of adaptive antennas at the transceivers, along with the associated advanced array signal processing, to improve cell coverage, link quality and system capacity. This dissertation first provides a framework of adaptive antenna systems for wireless communications, and characterizes the multipath fading channels of mobile broadband systems. In particular, we consider antenna systems for the base station, as well as multiple-input multiple-output systems where antenna systems are utilized at both the base station and the mobile unit. It is proved that the channel fading can be modeled and predicted using linear models of low order. The correlation of fading at multiple antennas or over the wideband is exploited to perfect channel modeling and prediction. Secondly, this dissertation develops the theory of adaptive antenna arrays with applications to mobile broadband systems. Through analysis of the propagation pattern and the channel structure, new techniques of uplink power control and downlink beamforming are derived to adapt to the rapid variation of the vector channel. The low variability of the channel subspace and the negligible distance between uplink and downlink channel subspaces are exploited to enhance the performance of adaptive transmission. Constraints are put on the model structure, which leads to a reduction of computational complexity of the channel estimation. Finally, this dissertation describes the correlation of sub-channels embedded in the multiple-input multiple-output antenna systems, and discusses its effect on the channel capacity. Multiple antennas with dissimilar radiation patterns are employed to introduce decorrelation of the sub-channels, thus increasing channel capacity. Specifically, a prototype of compact antenna array at the mobile unit is proposed that exploits antenna pattern diversity. In summary, this dissertation investigates the modeling and prediction of the time-varying multipath channels of antenna systems, while developing new techniques for mobile broadband communications that are based on the channel characterization. The general feasibility of the algorithms developed in this dissertation is demonstrated through a ray tracing simulator in various scattering environments.
Applying active network adaptability to wireless networks
(2004) Song, Seong-kyu; Nettles, Scott M.
The IP-based Internet, although wildly successful, is limited in its ability to evolve and adapt, in particular at the network layer. Mobile/wireless networking is an important emerging area in which adaptivity and evolvability is likely to be especially important due in part to the widely varying nature of the underlying communication channels themselves. We believe that active networking (AN) enables valuable adaptivity that existing technologies currently lack. This is because AN enables highly flexible packet functionality, on-the-fly protocol deployment, even on a packet-by-packet granularity, and cost-effective network expansion. Because adaptivity and evolvability is at a premium, we have chosen to test our belief in the mobile/wireless networking domain using three case studies: Mobile IP, ad hoc routing, and TCP over wireless. In our work, we demonstrate AN’s adaptivity by developing a series of designs, simulation studies, and working prototypes. Mobile IP is a protocol that supports mobility within the existing IP architecture by separating naming and addressing. While its design fits the conventional architecture and is feasible in current networks, Mobile IP exemplifies the inability of current networks to evolve effectively. Using Active Packet evolution and Update evolution techniques, we show how to deploy the new protocol and to evolve networks to support Mobile IP. Ad hoc networks are infrastructureless networks in which hosts are typically mobile and must act as routers. Mobility makes routing hard because the state of links changes frequently and routing heterogeneity is likely. We show how AN can provide useful routing adaptation to host mobility, in addition to routing evolution. In the last case study, we address the performance degradation of TCP over lossy links. TCP’s congestion control may cause under-utilization of bandwidth in wireless networks. We demonstrate AN’s adaptation to changing link conditions. Furthermore, taking advantage of flexible cross-layer interactions, we show AN’s ability to adapt to changes in TCP flow information. We show that active packets are especially useful in this context because they are extremely agile and allow adaptation on a packet-by-packet basis.
CDMA ad hoc networks: design and performance tradeoffs
(2005) Yang, Xiangying; De Veciana, Gustavo
This dissertation proposes new principles for designing and performance evaluation for spread spectrum based ad hoc networks. We ﬁrst highlight the advantages of spread spec trum, in the form of Code Division Multiple Access (CDMA), in handling quality of ser vice (QoS) requirements, enhancing energy efﬁciency, and enabling spatial multiplexing of bursty trafﬁc. Then, based on stochastic geometric models and simulation, we show the ALOHA-like random channel access and 802.11-like simple contention and handshaking based schemes are poor at achieving good capacity or efﬁcient spatial reuse, especially un der bursty and heavy load. We show that this is because the closest interferers severely penalize the performance of the network, particularly for a direct sequence CDMA (DS CDMA) system. Therefore, it is necessary to reconsider system design for spread spec trum ad hoc networks. To this end, we consider improving system performance at differ ent network layers. At the physical layer, we ﬁrst propose to use interference cancelation techniques, in particular, successive interference cancelation (SIC), at receivers to handle strong nearby interferers. Our analysis not only shows the signiﬁcant improvement on capacity from SIC but also indicates that just canceling a few nearest interferers will pro vide most of the performance gain. Therefore, SIC is particularly suitable for DS-CDMA ad hoc networks to enhance capacity, incurring only a small amount of extra complexity. In addition, at the MAC layer, we show how idealized contention resolution among ran domly distributed nodes results in clustering of successful transmitters and receivers, in turn leading to efﬁcient spatial reuse. This motivates explicitly inducing clustering among contending nodes to achieve even better spatial reuse. We propose two distributed mech anisms to realize such clustering and show substantial capacity gains over simple random access/ALOHA-like and even RTS/CTS based protocols – on the order of 100-700%. We examine under what regimes such gains can be achieved, and how clustering and contention resolution mechanisms should be optimized to do so. We further extend our MAC design for inducing clustered contention in ad hoc networks to support hop-by-hop relaying on different spatial scales. By allowing nodes to relay beyond the set of nearest neighbors using varying transmission ranges (scales), one can reduce the number of hops between a source and destination so as to meet end-to-end delay requirements. To that end we propose a multi-scale MAC clustering and power control mechanism to support transmissions with different ranges while achieving high spatial reuse. The considerations, analysis and sim ulations included in this thesis suggest that the principle of inducing spatial clustering in contention has substantial promise towards achieving high spatial reuse, QoS, and energy efﬁciency in spread spectrum ad hoc networks.
Compensation of nonlinear distortion and frequency offset in OFDM systems
(2001-12) Chang, Sekchin, 1969-; Powers, Edward J.
Orthogonal frequency division multiplexing (OFDM) systems exhibit many advantages in wireless as well as wireline environments. However, two crucial limiting issues should be overcomed for applicaiton of OFDM scheme to wireless systems: sensitivities to nonlinear distortion and frequency offset. This dissertation deals with applications of compensation schemes in OFDM systems to solve the sensitivity problems associated with nonlinear distortion and frequency offset in the systems. With regard to compensation of nonlinear distortion in OFDM systems, a Volterra-based predistorter has been applied to transmitter of OFDM systems. As a minimum mean square error (MMSE) predistorter, the Volterrabased predistorter can offer global solution with a proper learning architecture. The previous learning architecture didn’t make an efficient training for the predistorter because the learning algorithm utilized only indirect structure. For more efficient training, we propose a new learning algorithm which utilize direct as well as indirect structures in this dissertation. Our simulation shows that the new learning algorithm achieves a gain of 5 dB or more over the previous learning scheme. In this dissertation we also simplify the structure of the Volterra-based predistorter. Our simulation shows that the number of the predistorter coefficients can be reduced by 52.4% using the simplified scheme. Since the structure of the predistorter is efficiently simplified, the predistorter exhibits more rapid convergence rate that the original Volterra-based predistorter in training the coefficients. We also present a compensation scheme of inter-carrier interference (ICI) due to frequency offset in OFDM systems. For efficient cancellation of the ICI effects, we propose a nonlinear adaptive filter. In addition, we investigate the performance of the nonlinear adaptive filter when the ICI effects are magnified by some residual nonlinear distortion. Moreover, we present a blind estimation scheme of frequency offset based on the nonlinear adaptive filter for channel efficiency. Our simulation results confirm that the nonlinear adaptive filter is superior to the conventional linear filter in canceling the ICI effects and especially more suitable for the blind estimation of frequency offset under a nonlinear channel than the linear filter. Finally, we propose a new estimation scheme oftiming offset as well as frequency offset in OFDM systems. For complexity reduction we separately estimate timing and frequency offsets. For estimation of frequency offset we utilize an ambiguity function. In addition, for estimation of timing offset we propose a standard mimization method. Our simulation results show that the offsets are separately and exactly estimated using our presented schemes.
Designing medium access control protocols for multiple-input-multiple-output wireless networks
(2005) Park, Minyoung; Nettles, Scott M.
CarrierSenseMultipleAccesswithCollisionAvoidance(CSMA/CA)andtherequestto-send(RTS)/clear-to-send(CTS)controlpacketexchangemechanismbasedmedium access control (MAC) protocols, such as the IEEE 802.11 MAC protocol, are extremely successful in single-hop environments. Unfortunately, in multi-hop environments, they suﬀer from unfair access to the channel due to a side eﬀect of carrier sense and do not perfectly address the hidden node problem and thus degrade network performance. Fortunately, Multiple-Input-Multiple-Output (MIMO) technologies, which employ multiple antennas on both the transmitter and the receiver, provide capabilities to mitigate interference from neighboring nodes, to mitigate fading, and to increase the capacity of a link. We claim that designing MAC protocols jointly with ﬂexible MIMO physical layer technologies can address the problems of conventional MACs and higher layer protocols for multi-hop wireless networks. To show this, we ﬁrst propose a MAC protocol, Mitigating Interference using Multiple Antennas MAC (MIMA-MAC), which mitigates interference from neighboring nodes by using MIMO in its spatial multiplexing mode. We show that the MIMA-MAC can address the problems caused by neighboring interference and can also increase the utilization of network resources. We further enhance the MIMAMAC and propose the Mitigating Interference using Multiple Antennas with Antenna Selection diversity MAC (MIMA/AS-MAC), which fully utilizes multiple antennas by employing antenna selection diversity together with spatial multiplexing to mitigate fading as well as to suppress interference from neighboring nodes. For a multi-hop network, we show that the MIMA-MAC can improve TCP performance by mitigating neighboring interference. We further enhance the MIMA/AS-MAC and propose the TCP enhanced MIMA/AS-MAC, which increases the eﬃciency of small packet transmission. Finally, we explore ways of designing cross-layer MAC protocols that can address the problems of a system using reactive ad hoc routing protocols by controlling transmission modes based on the type of packets and channel conditions.
Downlink beamforming for mobile communications
(2001-12) Arredondo, Alberto; Ling, Hao; Xu, Guanghan
This dissertation introduces modeling and prediction of the downlink (transmission from base station to mobile user) spatial signature (the vector channel). The primary application of this technique is to time-division duplex wireless communications systems. In these systems, downlink beamforming performance based on spatial signatures suffers when the mobile user is truly mobile and not in line-of-sight with the base station. In these cases, the uplink spatial signature no longer resembles the downlink spatial signature. Chapter 2 shows that the spatial signature behavior with mobile movement can be modeled as an autoregressive process. The coefficients derived from observations of the uplink spatial signatures can be used to predict the downlink spatial signatures that follow. The predictions increase the downlink received power or signal-tonoise ratio, depending on the downlink beamforming method used, by as much as viii 10 dB in comparison to beamforming without prediction. These predictions can be used instead of channel coding to double the data throughput and allow reliable communication to two co-channel users traveling as fast as 105 km/h. This dissertation also includes a chapter that considers issues necessary for the practical implementation of downlink beamforming with prediction in frequencydivision duplex systems.
Frequency allocation, transmit power control, and load balancing with site specific knowledge for optimizing wireless network performance
(2007-05) Chen, Jeremy Kang-pen; Rappaport, Theodore S., 1960-; Veciana, Gustavo de
This dissertation is the first analytical and algorithmic work to exhibit the substantial gains that result from applying site specific knowledge to frequency allocation, transmit power control, and load balancing in wireless networks. Site specific knowledge refers to the use of knowledge of the surrounding propagation environment, building layouts, the locations of access points (APs) and clients, and the locations and electrical properties of physical objects. We assume a central network controller communicates with all APs, and has site specific knowledge which enables the controller to differentiate the sources of RF interference at every AP or user. By predicting the power from each interference source, the controller can allocate frequency channels, adjust transmit power levels, and balance loads among APs and clients in order to optimize throughput of the network. When site specific knowledge is not available, measurement-based algorithms may be used; we present three measurement-based frequency allocation algorithms that outperform the best published work by 18% for median user throughput. Then we present two site-specific knowledge-based frequency allocations that outperform the proposed measurement-based algorithms particularly for uplifting throughputs of the users who suffer low throughputs, e.g., we have gains of 3.75%, 11.8%, 10.2%, 18.2%, 33.3%, and 459% for 50, 25, 20, 15, 10, and 5 percentiles of user throughputs, respectively, over the proposed measurement-based algorithms. Furthermore, we employ transmit power control to further improve clients’ throughputs achieved by optimal site-specific knowledgebased frequency allocations; transmit power control can improve the 25, 10, 5, and 3 percentiles of users’ throughputs by up to 4.2%, 9.9%, 38%, and 110%, and save power by 20%. Finally, a load balancing algorithm is proposed as an add-on that works seamlessly with frequency allocation and transmit power control algorithms. The load-balancing algorithm can improve median user throughput by about 26%. The work in this dissertation shows that site specific knowledge is an important means for optimizing performance of wireless networks.
Grassmann quantization for precoded MIMO systems
(2006) Mondal, Bishwarup; Heath, Robert W., Jr, 1973-
It is projected that future mobile cellular networks will carry traffic that is Internet intensive and capacity hungry. A bottleneck in providing such capacity is the limited availability of spectrum and power along with the random fluctuations in the propagation medium. Using antenna arrays at the transmitter and at the receiver and creating a multiple-input multiple-output (MIMO) wireless channel for data transmission has emerged as a candidate for improving the performance of wireless networks. The wireless propagation medium for a signal transmitted from an antenna array may be modelled as a matrix, called the channel matrix. The knowledge of the channel matrix may be used at the transmitter to signifi- cantly improve system performance. Unfortunately, in many wireless systems, the transmitter may not have access to this channel knowledge and will rely on feedback of quantized channel information from the receiver. This feedback consumes a part of the capacity available for data transmission from the receiver, thereby assigning a cost to the system performance. The objective of this dissertation is to analytically quantify the system performance as a function of this feedback cost. This dissertation formulates the problem of quantization of channel information in a non-Euclidean space called the complex Grassmann manifold. This formulation is novel and traditional signal processing tools and techniques do not extend naturally to the Grassmann manifold since it is not a vector space. The fidelity of channel information is then characterized as a function of the number of quantization levels. Using these results, the achievable signal-to-noise ratio and the outage probability of a MIMO beamforming system are expressed in terms of the feedback rate. In the general case of a precoded spatial multiplexing system or a space-time block coded system, the received signal strength is quantified as a function of the feedback rate. The bounds and approximations derived herein are validated to be tight under practical circumstances using simulation results, thus providing a performance benchmark. A sufficient condition is derived that will guarantee no loss in the diversity performance of precoded MIMO systems due to quantization of channel information.
I/O test methods in high-speed wireline communication systems
(2008-08) Dou, Qingqi; Abraham, Jacob A.
The advent of serial tera-bit telecommunication and multi-gigahertz I/O interfaces is posing challenges on the semiconductor and ATE industries. There is a gap in signal integrity testing between what has been specified in serial link standards and what can be practically tested in production. A thorough characterization and a more cost-effective test of the signal integrity, such as BER, jitter, and eye margin, are critical to identify and isolate the root cause of the system degradation and to the binning in production. In this dissertation, measurement and testing schemes on signal integrity are explored. A solution for diagnosing jitter and predicting the range of consequent BER is proposed. This solution is applicable to decomposition of correlated and uncorrelated jitter in both clock and data signals. The statistical information of jitter is estimated using TLC functions. TLC treats jitter in its original form, as a time series, resulting in good accuracy in the decomposition. Hardware results in a PLL indicate that the approach is still valid when the traditional histogram-based method fails. This approach can be implemented using only one-shot capture instead of multiple captures to average out the uncorrelated jitter from the correlated jitter. Therefore, the TLC functions enable test time reduction in jitter decomposition compared to traditional averaging methods. Hardware measurements on stressed data signals are presented to validate the proposed technique. We have also explored low cost, high bandwidth techniques using Built In Self Test(BIST) for on-chip jitter measurement. Undersampling provides a lowcost test solution for on-chip jitter measurement. However, it suffers from sampling clock phase error and time quantization noise. These timing uncertainties on the test accuracy of the traditional technique using a single channel structure can be alleviated by extracting the correlation between two channels using a single reference clock. Simulation results indicate that the proposed approach can achieve a better measurement accuracy and a higher degree of tolerance to sampling clock uncertainty and quantization error than does the single-channel structure, with little additional test overhead. TIADCs provide an attractive solution to the realization of analog front ends in high speed communication systems,such as 10GBASE-T and 10GBASEFiber. However, gain mismatch, offset mismatch, and sampling time mismatch between time-interleaved channels limit the performance of TIADCs. A low-cost test scheme is developed to measure timing mismatch using an undersampling clock. This method is applicable to an arbitrary number of channels, achieving picosecond resolution with low power consumption. Simulation results and hardware measurements on a 10GSps TIADC are presented to validate the proposed technique.
Interference suppression in wireless ad hoc networks
(2006) Hasan, Aamir; Andrews, Jeffrey G.
Wireless ad hoc networks are infrastructure-free self-organizing networks formed by cooperating nodes. They are highly desirable for various emerging applications and to extend the range and capacity of infrastructure-based wireless networks. Scheduling algorithms in ad hoc networks allow nodes to share the wireless channel so that concurrent transmissions can be decoded successfully. On one hand, scheduling needs to be eﬃcient to maximize the spatial reuse. But on the other hand the scheduling algorithm needs to be easily implementable with little, if any, coordination between nodes in the network. The goal of this dissertation is to propose and evaluate a simple scheduling technique that suppresses transmissions by nodes around the desired receiver in order to achieve successful communication. This minimum separation, the guard zone, has important implications on the network performance and impacts the MAC design. In particular, using stochastic geometry, a near-optimal guard zone for spread spectrum ad hoc networks is derived – narrow-band transmission (spreading gain of unity) is a special case. In ad hoc networks employing a Direct-Sequence Code Division Multiple Access (DS-CDMA), the guard zone can easily be realized in a distributed manner, and oﬀers a 2−100 fold increase in capacity as compared to an ALOHA network; the capacity increase depending primarily on the required outage probability, as higher required QoS increasingly rewards scheduling. By implementing guard zone-based scheduling, the attained performance is about 70− 80% of a well-known near-optimal (and practically infeasible) centralized scheme. One major advantage of DS-CDMA is its ability to reduce the required guard zone size compared to a narrow-band system. A guard zone smaller than transmission range ensures that nodes that can potentially cause an outage are within the decoding range of a receiver. This lowers the complexity of scheduling algorithms as smaller area, which lies with in the transmission range of the receiver, needs to be managed by the MAC protocol. The dissertation considers primarily a physical and MAC layer view of the network to investigate and deﬁne what is optimal at the physical/MAC layer.
Joint diversity combining technique and adaptive modulation in wireless communications
(2006) Nam, Haewoon; Womack, Baxter F., 1930-
Wireless communications has become a major economic sector with an unprecedented growth rate over the past decade. This phenomenal growth rate has increased even faster in the 21st century due to the success of wireless cellular systems and wireless local area networks. Furthermore, a variety of applications for high quality media content running on mobile devices have also fueled this phenomenon. In order to maintain the rapid growth rate and satisfy such a high demand from users, the next generation communication systems must achieve both reliability and high data rate using a limited spectrum, power, and complexity budget. Unfortunately, a harsh and unpredictable wireless radio propagation environment, with issues such as multipath, shadowing effects, and frequency selectivity, makes this goal very challenging. There are several techniques in wireless communication systems to combat, or even exploit, such a detrimental effect of fading channels. The most popular technique is the diversity combining technique, where multiple replicas of the same signal are used to reduce the amount of fading. By coherently combining these multiple copies of the transmitted signal, this technique provides reliability of the communication link and offers a higher dynamic range. Among other techniques is adaptive modulation, which attempts not to mitigate the fading effect but to take advantage of it by adaptively adjusting the modulation constellation to the instantaneous channel quality. Thus, this technique aims at achieving a high spectral efficiency given a certain level of bit error rate (BER). This dissertation examines diversity combining techniques and adaptive modulation with an emphasis on how these two different techniques can jointly operate in various wireless systems to achieve both reliability and high spectral efficiency. After a brief introduction to the conventional diversity combining schemes, the adaptive diversity combining schemes are first discussed including a performance analyis. Embedded with a target signal-to-noise ratio (SNR), which may be pre-determined based on the quality of service (QoS) for an application, the adaptive diversity combining schemes achieve a reduced complexity while satisfying the target performance. Second, a joint diversity combining and adaptive modulation technique in multi-carrier systems is proposed and presented with analytical results. Since the fourth generation (4G) wireless cellular system standards adopt orthogonal frequency division multiplexing (OFDM) as a basic transmission technology, techniques to improve the performance at the cell edge in such multi-carrier systems are becoming very important. Exploiting a diversity combining technique, the proposed scheme offers an improved spectral effi- ciency in the low SNR region. Finally, a simple and practical system based on a switched diversity scheme with adaptive modulation is presented. This system provides a reduced number of channel estimation while satisfying the optimum spectral efficiency compared to a selection diversity system. In addition, the switching threshold is easily manipulated so as to make an efficient use of the trade-off between spectral efficiency and the number of channel estimation. An extension of this scheme into a multiuser scenario is considered. This switch-based multiuser access scheme results in an average feedback load that is lower than using the optimal selection-based multiuser scheme. Numerical results show we can obtain a trade-off between spectral efficiency and the feedback load by choosing the switching threshold appropriately.
MIMO networking with imperfect channel state information
(2008-05) Huang, Kaibin; Andrews, Jeffrey G.; Heath, Robert W., Jr, 1973-
The shortage of radio spectrum has become the bottleneck of achieving broadband wire-less access. Overcoming this bottleneck in next-generation wireless networks hinges on successful implementation of multiple-input-multiple-output (MIMO) technologies, which use antenna arrays rather than additional bandwidth for multiplying data rates. The most efficient MIMO techniques require channel state information (CSI). In practice, such information is usually inaccurate due to overhead constraints on CSI acquisition as well as mobility and delay. CSI inaccuracy can potentially reduce the performance gains provided by MIMO. This dissertation investigates the impact of CSI inaccuracy on the performance of increasing complex MIMO networks, starting with a point-to-point link, continuing to a multiuser MIMO system, and ending at a mobile ad hoc network. Furthermore, this dissertation contributes algorithms for efficient CSI acquisition, and its integration with beamforming and scheduling in multiuser MIMO, and with interference cancelation in ad hoc networks. First, this dissertation presents a design of a finite-rate CSI feedback link for point-to-point beamforming over a temporally correlated channel. We address various important design issues omitted in prior work, including the feedback delay, protocol, bit rate, and compression in time. System parameters such as the feedback bit rate are derived as functions of channel coherence time based on Markov chain theory. In particular, the capacity gain due to beamforming is proved to decrease with feedback delay at least at an exponential rate, which depends on channel coherence time. This work provides an efficient way of implementing beamforming in practice for increasing transmission range and throughput. Second, several algorithms for multiuser MIMO systems are proposed, including CSI quantization, joint beamforming and scheduling, and distributed feedback scheduling. These algorithms enable spatial multiple access and multiuser diversity in a cellular system under the practical constraint of finite-rate multiuser CSI feedback. Moreover, this dissertation shows analytically that the throughput of the MIMO uplink and downlink using the proposed algorithms scales optimally as the number of users increases. Finally, the transmission capacity of a MIMO ad hoc network is analyzed for the case where spatial interference cancelation is applied at receivers. Most important, this dissertation shows that this MIMO technique contributes significant network capacity gains even if the required CSI is inaccurate. In addition, opportunistic CSI estimation is shown to provide a tradeoff between channel training overhead and CSI accuracy.
Multiuser resource allocation in multichennel wireless communication systems
(2006) Shen, Zukang; Andrews, Jeffrey G.; Evans, Brian L. (Brian Lawrence), 1965-
A downlink wireless system features a centralized basestation communicating to a number of users physically scattered around the basestation. The purpose of resource allocation at the basestation is to intelligently allocate the limited resources, e.g. total transmit power and available frequency bandwidth, among users to meet users’ service requirements. Channel-aware adaptive resource allocation has been shown to achieve higher system performance than static resource allocation, and is becoming more critical in current and future wireless communication systems as the user data rate requirements increase. Adaptive resource allocation in a multichannel downlink system is more challenging because of the additional degree of freedom for resources, but offers the potential to provide higher user data rates. Multiple channels can be created in the frequency domain using multiple carrier frequencies, a.k.a. multicarrier modulation (MCM), or in the spatial domain with multiple transmit and receive antennas, a.k.a. multiple-input multiple-output (MIMO) systems. This dissertation aims to study the system performance, e.g. total throughput and/or fairness, in multiuser multicarrier and multiuser MIMO systems with adapvii tive resource allocation, as well as low complexity algorithms that are suitable for cost-effective real-time implementations in practical systems. The first contribution of this dissertation is a general framework for adaptive resource allocation in multiuser multicarrier systems that maximizes the total throughput subject to fairness constraints to enforce arbitrary proportional data rates among users. Whereas the global optimality is computationally intensive to obtain, a low complexity algorithm that decouples the subchannel and power allocation is proposed. The second contribution concerns precoding using block diagonalization (BD) for single-carrier downlink multiuser MIMO systems. The contribution is twofold. First, it is shown that BD, as a practically realizable precoding technique, can achieve a significant part of the sum capacity achieved by dirty paper coding (DPC), which is optimal. Practical coding schemes that approach the DPC sum capacity, however, are still largely unknown. Second, an upper bound on the ergodic sum capacity gain of DPC over BD in Rayleigh fading channels is derived. The third contribution concerns low-complexity BD precoding algorithms. Due to the zero inter-user interference requirement imposed by BD, the maximum number of simultaneously supportable users is limited. The brute-force search for the optimal user set, however, is computationally prohibitive for systems with a large number of users. The dissertation proposes two suboptimal user selection algorithms for BD that have linear complexity in the number of users, yet achieve total throughput close to the optimal. A common characteristic of the resource allocations for multiuser multicarrier and multiuser MIMO systems is that the limited resources shall be allocated among multiple users as well as multiple parallel subchannels. As MCM and MIMO have been widely adopted in various standards, the research in this dissertation contributes to a better understanding of the system performance, and bridges the theory to practical implementations with the proposed low complexity algorithms.
Network coding for next-generation networks
(2008-05) Bhadra, Sandeep; Shakkottai, Sanjay
As a discipline at the intersection of information theory and classical stochastic network analysis, network coding promises interesting future applications, and hence presents newer fundamental theoretical problems in the field of network engineering and design. While much research on network coding is concerned with the analysis and construction of capacity achieving codes, our focus in this proposal will be on the impact of Random Linear Coding (RLC) in next generation wireline and wireless networks. We consider two techniques of coding for networks: one where coding is performed at every intermediate node of a network, and the other where only source nodes encode across packets. For either case, we present scenarios where network coding offers significant performance gains. Under network coding at every intermediate node, the previously intractable min-cost multicast problem has been formulated in terms of a convex optimization. Recent work has focused on cooperative decentralized algorithms to solve this, most using primal-dual techniques. Instead, here we formulate a decentralized non-cooperative version of the problem where each user routes greedily to minimize its own cost and study how the resulting user-equilibrium cost compares to the global (social) optimum. Based on our results, simple greedy decentralized algorithms are proposed for distributed min- cost flow adaptation at nodes in the network. In the context of wireless networks, achieving unicast capacity is complicated by wireless broadcast and interference. We note that while much of extant network coding research has been on wireline networks, our understanding of network codes applied to wireless networks is still limited. We abstract broadcast and interference properties in the wireless channel by a finite field addition channel, to arrive at a Broadcast and Additive Interference Network (BAIN) and show that there exists a graph transformation, and a corresponding sample path coupling, to model a BAIN as a regular wireline network with network coding at intermediate nodes. Based on this analysis, we leverage existing results from network coding for wireline networks to arrive at asymptotically tight bounds on unicast capacity for BAINs. Next, we consider network coding at the source, with no buffers at intermediate nodes, as an alternative to traditional buffering of transient packets at intermediate nodes in multi-hop networks, thereby virtually sharing memory between links on a flow path. We call this spatial buffer multiplexing: where buffering and coding implemented at the source alone compensates for packet loss at any downstream bufferless link. Using many-sources large deviations analysis, we show that network coding promises dramatic improvements in resource allocation and buffer sizing in large scale networks with large diameters (such as spatial networks) under comparable network-wide packet drop probabilities (QoS). However, using large buffer large deviations analysis, we show that network coding performs poorly against traditional queueing when it is not possible to have stochastic multiplexing with many other sources at intermediate nodes. Finally, since network coding at the source may be used to dynamically buffer dropped packets at each fixed capacity link due to bursty fixed-rate arrivals at each source, we would like to also examine the dual scenario where the source rate (TCP window size) is controlled to deliver the maximum average throughput in a time-varying noisy wireless link (with varying information theoretic capacity) shared by many TCP connections. We show that network coding at the source promises an orderwise improvement in the mean TCP window size distribution as compared to the case where network coding is not used.
Networked control and efficient transmission in sensor networks
(2007) Wu, Wei, doctor of electrical and computer engineering; Arapostathis, Ari, 1954-
Enabling "intelligent environments" that are effortlessly automated is a key promise of sensor networks of the future. These networks have a wide range of domains in which they can be effectively deployed, including health-care, emergency response, manufacturing and surveillance. Unlike the majority of existing (and perhaps better-understood) network configurations, wireless-implemented sensor networks suffer from extremely stringent constraints in terms of scalability and end-goal of deployment. Thus, it is imperative that we determine solutions that are tailored to the constraints and goals of these systems, by bringing together ideas in the domains of control, computing and communications to a common analytical platform. In this dissertation, we build a theoretical framework that uses system theory, stochastic control, queuing theory and information theory to determine the following: 1. A characterization of the stability and optimal control policies with sensor querying (i.e. which set of sensors must be queried and when) using system theory and stochastic control; 2. A delay-optimal energy efficient transmission scheme for these networks (i.e. with what power level must they communicate) using heavy traffic limits and stochastic control; and 3. A cooperative transmission strategy for maximizing capacity of these networks (i.e. how they should encode their data to send the most through) using network information theory.
Opportunistic scheduling and resource allocation among heterogeneous users in wireless networks
(2006) Patil, Shailesh; De Veciana, Gustavo
This dissertation studies and proposes new methods to perform opportunistic scheduling in different scenarios for centralized wireless networks. We first study the performance of measurement-based opportunistic scheduling strategies in practical scenarios where users’ heterogenous capacity distributions are unknown. We make the case for using maximum quantile scheduling, i.e., scheduling a user whose current rate is in the highest quantile relative to its current empirical distribution. Under fast fading, we prove a bound on the relative penalty associated with such empirical estimates, showing that the number of independent samples need only grow linearly with the number of active users. Furthermore, we show several desirable properties of maximum quantile scheduling for the saturated regime, and give bounds on performance under the dynamic regime. Next we propose a novel class of opportunistic scheduling disciplines to handle mixes of real-time and best effort traffic at a base station. The objective is to support probabilistic service rate guarantees to real-time sessions while still achieving opportunistic throughput gains across users and traffic types. Under fast fading and maximum quantile scheduling, we are able to show a stochastic lower bound on the service a real-time session would receive. Such bounds are critical to enabling predictable quality of service and thus the development of complementary resource management and admission control strategies. Our simulation results show that the scheme can achieve more than 90% of the maximum system throughput capacity while satisfying the QoS requirements for real-time traffic. Finally, we propose methods to reduce the feedback overhead for users’ channel state information needed for opportunistic scheduling at a base station. We first propose a contention based scheme known as ‘static splitting’ for a best effort traffic only scenario. Next we consider reducing feedback overhead in a system supporting a mixture of best effort and real-time traffic. We argue that one needs to combine contention based schemes with polling subsets of users to reduce the amount of feedback needed to exploit opportunism, and yet meet real-time users’ QoS guarantees. Based on this argument we propose a joint polling and opportunistic scheduling (JPOS) scheme.
Rate-robustness tradeoffs in multicarrier wireless communications
(2006) Kim, Tae Yoon; Andrews, Jeffrey G.
Emerging wireless communication systems exploit various resources to increase their robustness and data rate. Since these resources are limited, there is a tradeoff between the need for robust communication and the desire for high throughput. The aim of this dissertation is to study and optimally balance this tradeoff for a few important cases in multicarrier communications. First, multi-code code division multiple access (CDMA) techniques tradeoff the number of supportable subscribers with the per subscriber data rate. However, the interference scales linearly with the data rate of each user since they use multiple codes. To resolve this interference problem, a novel multi-code multicarrier CDMA system is proposed, and this system clearly outperforms previous systems in terms of bit error probability and user capacity. This shows that flexible data rates can be successfully balanced with robustness in a multiuser multi-rate CDMA system by carefully choosing the data rates number of subcarriers. Second, in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM), pilots are used to estimate the channel, but in addition to consuming bandwidth, they reduce the transmitted energy for data symbols under a fixed transmit power constraint. This suggests a tradeoff between the power allowed to data symbols and the accuracy of channel estimation. The optimal pilot-to-data power ratio (PDPR) for maximizing a capacity lower bound is formulated and derived for four likely pilot patterns and two different channel conditions. The optimal PDPR shows about 10%∼30% higher capacity lower bound than equal power allocation. Third, and closely related to the second contribution, adaptive M-QAM, spectral efficiency, and symbol error rate (SER) are considered since these are respectively the dominant modulation type and quality metrics in emerging standards. The effect of the system structure on the PDPR is analytically shown, and the optimal PDPR for minimizing the average SER and maximizing the spectral efficiency is derived for two well-known linear receivers; zero-forcing and minimum meansquare error. The distributions of the SNR (including channel estimation error) for these receivers are derived and used to find the optimal PDPR. Exact guidelines are provided for the power allocation between data and pilot symbols for these cases.
Relay-assisted communication : fundamental limits and selection strategies
(2008-12) Lo, Caleb K., 1981-; Heath, Robert W., Jr, 1973-; Vishwanath, Sriram
Wireless communication continues to make a profound impact upon our daily lives. The oft-touted benefits of high data rates and improved reliability via wireless communication are limited by its inherent drawbacks, including path loss, fading and interference. One promising strategy for overcoming these problems is to deploy nodes in the region between a transmitter and its intended receiver. These intermediate nodes can improve communication for this transmitter-receiver pair by receiving a transmitted message, processing it and relaying the processed output to the receiver. This transmission strategy, known as relay-assisted communication, can be especially beneficial when the transmitter-receiver pair are either separated by a large distance or when a large obstruction blocks the path between them. In a reasonably dense network, several relays may be available to assist a particular transmitter-receiver pair. Deciding which relays should forward the transmitted message is actually quite difficult. For example, the relay with the best physical-layer channel gain to the destination may also be running low on battery power. Another relay may have a good physical-layer channel gain to the destination and a reasonable amount of remaining battery power, but its queue may be full of messages from other transmitters, so it cannot forward a newly arrived message within a given delay constraint. Thus, optimal relay selection entails carefully balancing all system parameters, which is prohibitively complex in current wireless systems. This dissertation provides novel results for dealing with the relay selection problem in two distinct types of wireless systems. First, several selection algorithms are designed for single-antenna wireless networks, including a decentralized random access-based strategy and centralized methods that are based on throughput maximization and downlink user scheduling. Second, selection algorithms based on transmission hop length are designed for multipleantenna wireless networks. The presented strategies for both single-antenna and multiple-antenna relaying are highly intuitive, as they allow for concise descriptions, making them amenable to practical implementation. Also, the presented strategies illustrate the importance of application-specific design, since each of them yields good performance by focusing on a small set of system parameters. For example, observed latency is of paramount importance for wireless networks that support a significant level of video traffic.
Routing and broadcasting over sensor networks
(2008-08) Subramanian, Sundar, 1981-; Shakkottai, Sanjay
Advances in micro-embedded computing systems, coupled with developments in wireless technology have enabled the deployment of large scale wireless and sensor networks for many important applications. These networks are characterized by local geographic connectivity among nodes and by very little computational and storage capabilities at each node. Moreover, data transfer is mainly through packet forwarding by intermediary nodes. Due to the nature of their connectivity, nodes may have extremely limited information about their network, possibly only of their one-hop neighbors. In such a scenario where the nodes may have limited/erroneous network state information, we study the two basic network primitives: (i) point-to-point routing and (ii) broadcasting. First, we study the problem of point-to-point routing in a network of nodes where each node has a corresponding destination to send/receive data. We consider geographic routing (routing based on the position of the nodes), as this routing scheme is scalable and of low complexity and well suited to operate over sensor networks. We study the effect of imperfect routing information on the path lengths of the individual routes. We provide error models for the routing errors and demonstrate routing strategies that achieve order-wise optimal delays even when only a small fraction of the nodes have any (possibly imperfect) geographic information. We characterize the throughput capacity of the network and show that for a class of progressive routing strategies with limited routing data, the throughput capacity is order-wise optimal. While much of the current research focuses on greedy routing in uniform sensor networks, we study routing in imperfect (anisotropic) networks where greedy geographic forwarding fails due to holes (nodes without any neighbors that are closer to the destination). We develop routing strategies in such networks that operate with geographic location at the nodes to achieve order-wise optimal delays while maximizing the network throughput capacity. These algorithms inherit the beneficial properties of geographic routing algorithms such as scalability and low complexity while providing near-optimal throughput and delay in a robust manner. We also study routing strategies in networks where the traffic demand may be non-uniform. Routing schemes such as geographic routing that minimize some metric of routing distance cause local points of congestion as they do not consider the traffic demands across different parts of the network and may concentrate traffic along some paths that lie across regions of higher demand. We design randomized routing schemes based on geographic routing that are shown to be able to support any traffic demand that is achievable (i.e. achievable by any other scheme). Second, we study the issue of broadcasting in networks with limited local information. We analyze broadcast schemes where nodes have little geographic information or state information (memory of transmitted packets). We demonstrate randomized broadcast algorithms that utilize the limited information and perform broadcasting with minimal transmission overheads. Further, we also study branching random walks in R[superscript d], in the context of broadcasting a message over a spatial network to understand the asymptotic distribution of the broadcast. We derive analytic results on the density of these branching processes
A software architecture for cross-layer wireless networks
(2008-05) Choi, Soon Hyeok, 1972-; Nettles, Scott M.
Conventional data networks are based on a layered architecture, in which a layer implements some aspect of the network while hiding the detailed implementation from the other layers. The introduction of wireless networks has created a need to violate this layered discipline to create cross-layer designs or adaptations. Such cross-layer adaptations optimize the performance of wireless networks by using information from any layer in the network. The key problem is that ad-hoc implementations of cross-layer adaptations introduce complex interactions between layers and thus reduce the level of modularity and abstraction in the network's implementation. This gives rise to a significant increase in complexity. We demonstrate that a new software architecture is able to provide a systematic framework that helps us to implement a wide variety of cross-layer adaptations while preserving to a significant degree the modularity found in the existing network's implementation. To develop such an architecture, we first create a taxonomy of possible cross-layer adaptations. The taxonomy allows a precise description of a wide variety of cross-layer adaptations. Thus our taxonomy can serve as a framework for developing a cross-layer architecture. We develop the software architecture by creating two architectures, a conceptual one and a concrete one. We first develop a conceptual architecture, which shows the key mechanisms that are required to implement cross-layer adaptations. This architecture helps us to understand how we can implement cross-layer adaptations by using our architectural framework. We then develop a concrete architecture, which shows how we can implement such a conceptual architecture on real wireless systems. This architecture addresses more detailed implementation issues. We design the concrete architecture for Hydra, which is a flexible wireless network testbed. We then show that our architecture is generic enough to allow us to support a wide set of cross-layer architectures. We evaluate the proposed architecture by performing three case studies, each of which implements a cross-layer adaptation within Hydra based on the concrete architecture. The case studies allow us to implement and evaluate the key mechanisms provided by our architectural framework. We also implement each cross-layer adaptation by using a conventional approach, in which one layer performs the cross-layer adaptation directly communicating with other layers and other nodes. Comparing both the implementation techniques allows us to evaluate how our architectural framework supports a wide variety of cross-layer adaptations while reducing the complexity of implementation of cross-layer adaptations.