This text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energy-efficient and profit-maximizing decisions must be made without knowing the future. Topics in the text include the following: - Queue stability theory - Backpressure, max-weight, and virtual queue methods - Primal-dual methods for non-convex stochastic utility maximization - Universal scheduling theory for arbitrary sample paths - Approximate and randomized scheduling theory - Optimization of renewal systems and Markov decision systems Detailed examples and numerous problem set questions are provided to reinforce the main concepts. Table of Contents: Introduction / Introduction to Queues / Dynamic Scheduling Example / Optimizing Time Averages / Optimizing Functions of Time Averages / Approximate Scheduling / Optimization of Renewal Systems / Conclusions

Stochastic Network Optimization with Application to Communication and Queueing Systems

In-band full-duplex (IBFD) operation has emerged as an attractive solution for increasing the throughput of wireless communication systems and networks. With IBFD, a wireless terminal is allowed to transmit and receive simultaneously in the same frequency band. This tutorial paper reviews the main concepts of IBFD wireless. One of the biggest practical impediments to IBFD operation is the presence of self-interference, i.e., the interference that the modem's transmitter causes to its own receiver. This tutorial surveys a wide range of IBFD self-interference mitigation techniques. Also discussed are numerous other research challenges and opportunities in the design and analysis of IBFD wireless systems.

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In-Band Full-Duplex Wireless: Challenges and Opportunities

In-band full-duplex (IBFD) operation has emerged as an attractive solution for increasing the throughput of wireless communication systems and networks. With IBFD, a wireless terminal is allowed to transmit and receive simultaneously in the same frequency band. This tutorial paper reviews the main concepts of IBFD wireless. Because one the biggest practical impediments to IBFD operation is the presence of self-interference, i.e., the interference caused by an IBFD node's own transmissions to its desired receptions, this tutorial surveys a wide range of IBFD self-interference mitigation techniques. Also discussed are numerous other research challenges and opportunities in the design and analysis of IBFD wireless systems.

We propose joint spatial division and multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base station while requiring reduced-dimensional channel state information at the transmitter (CSIT). JSDM achieves significant savings both in the downlink training and in the CSIT uplink feedback, thus making the use of large antenna arrays at the base station potentially suitable also for frequency division duplexing (FDD) systems, for which uplink/downlink channel reciprocity cannot be exploited. In the proposed scheme, the multiuser MIMO downlink precoder is obtained by concatenating a prebeamforming matrix, which depends only on the channel second-order statistics, with a classical multiuser precoder, based on the instantaneous knowledge of the resulting reduced dimensional “effective” channel matrix. We prove a simple condition under which JSDM incurs no loss of optimality with respect to the full CSIT case. For linear uniformly spaced arrays, we show that such condition is approached in the large number of antennas limit. For this case, we use Szego's asymptotic theory of Toeplitz matrices to show that a DFT-based prebeamforming matrix is near-optimal, requiring only coarse information about the users angles of arrival and angular spread. Finally, we extend these ideas to the case of a 2-D base station antenna array, with 3-D beamforming, including multiple beams in the elevation angle direction. We provide guidelines for the prebeamforming optimization and calculate the system spectral efficiency under proportional fairness and max-min fairness criteria, showing extremely attractive performance. Our numerical results are obtained via asymptotic random matrix theory, avoiding lengthy Monte Carlo simulations and providing accurate results for realistic (finite) number of antennas and users.

Joint Spatial Division and Multiplexing—The Large-Scale Array Regime

tions. Bootstrap has found many applications in engineering field, including artificial neural networks, biomedical engineering, environmental engineering, image processing, and radar and sonar signal processing. Basic concepts of the bootstrap are summarized in each section as a step-by-step algorithm for ease of implementation. Most of the applications are taken from the signal processing literature. The principles of the bootstrap are introduced in Chapter 2. Both the nonparametric and parametric bootstrap procedures are explained. Babu and Singh (1984) have demonstrated that in general, these two procedures behave similarly for pivotal (Studentized) statistics. The fact that the bootstrap is not the solution for all of the problems has been known to statistics community for a long time; however, this fact is rarely touched on in the manuscripts meant for practitioners. It was first observed by Babu (1984) that the bootstrap does not work in the infinite variance case. Bootstrap Techniques for Signal Processing explains the limitations of bootstrap method with an example. I especially liked the presentation style. The basic results are stated without proofs; however, the application of each result is presented as a simple step-by-step process, easy for nonstatisticians to follow. The bootstrap procedures, such as moving block bootstrap for dependent data, along with applications to autoregressive models and for estimation of power spectral density, are also presented in Chapter 2. Signal detection in the presence of noise is generally formulated as a testing of hypothesis problem. Chapter 3 introduces principles of bootstrap hypothesis testing. The topics are introduced with interesting real life examples. Flow charts, typical in engineering literature, are used to aid explanations of the bootstrap hypothesis testing procedures. The bootstrap leads to second-order correction due to pivoting; this improvement in the results due to pivoting is also explained. In the second part of Chapter 3, signal processing is treated as a regression problem. The performance of the bootstrap for matched filters as well as constant false-alarm rate matched filters is also illustrated. Chapters 2 and 3 focus on estimation problems. Chapter 4 introduces bootstrap methods used in model selection. Due to the inherent structure of the subject matter, this chapter may be difficult for nonstatisticians to follow. Chapter 5 is the most impressive chapter in the book, especially from the standpoint of statisticians. It provides real data bootstrap applications to illustrate the theory covered in the earlier chapters. These include applications to optimal sensor placement for knock detection and land-mine detection. The authors also provide a MATLAB toolbox comprising frequently used routines. Overall, this is a very useful handbook for engineers, especially those working in signal processing.

Probability and Random Processes

Full Duplex or Simultaneous transmission and reception (STR) in the same frequency at the same time can potentially double the physical layer capacity. However, high power transmit signal will appear at receive chain as echoes with powers much higher than the desired received signal. Therefore, in order to achieve the potential gain, it is imperative to cancel these echoes. As these high power echoes can saturate low noise amplifier (LNA) and also digital domain echo cancellation requires unrealistically high resolution analog-to-digital converter (ADC), the echoes should be cancelled or suppressed sufficiently before LNA. In this paper we present a closed-loop echo cancellation technique which can be implemented purely in analogue domain. The advantages of our method are multiple-fold: it is robust to phase noise, does not require additional set of antennas, can be applied to wideband signals and the performance is irrelevant to radio frequency (RF) impairments in transmit chain. Next, we study a few protocols for STR systems in carrier sense multiple access (CSMA) network and investigate MAC level throughput with realistic assumptions in both single cell and multiple cells. We show that STR can reduce hidden node problem in CSMA network and produce gains of up to 279% in maximum throughput in such networks. Moreover, at high traffic load, the gain of STR system can be tremendously large since the throughput of non-STR system is close to zero at heavy traffic due to severe collisions. Finally, we investigate the application of STR in cellular systems and study two new unique interferences introduced to the system due to STR, namely BS-BS interference and UE-UE interference. We show that these two new interferences will hugely degrade system performance if not treated appropriately. We propose novel methods to reduce both interferences and investigate the performances in system level. We show that BS-BS interference can be suppressed sufficiently enough to be less than thermal noise power, and with favorable UE-UE channel model, capacities close to double are observed both in downlink (DL) and uplink (UL). When UE-UE interference is larger than DL co-channel interferences, we propose a simple and "non-cooperative" technique in order to reduce UE-UE interference.

Simultaneous Transmission and Reception: Algorithm, Design and System Level Performance

Full Duplex or Simultaneous transmission and reception (STR) in the same frequency at the same time can potentially double the physical layer capacity. However, high power transmit signal will appear at receive chain as echoes with powers much higher than the desired received signal. Therefore, in order to achieve the potential gain, it is imperative to cancel these echoes. As these high power echoes can saturate low noise amplifier (LNA) and also digital domain echo cancellation requires unrealistically high resolution analog-to-digital converter (ADC), the echoes should be cancelled or suppressed sufficiently before LNA. In this paper we present a closed-loop echo cancellation technique which can be implemented purely in analogue domain. The advantages of our method are multiple-fold: it is robust to phase noise, does not require additional set of antennas, can be applied to wideband signals and the performance is irrelevant to radio frequency (RF) impairments in transmit chain. Next, we study a few protocols for STR systems in carrier sense multiple access (CSMA) network and investigate MAC level throughput with realistic assumptions in both single cell and multiple cells. We show that STR can reduce hidden node problem in CSMA network and produce gains of up to 279% in maximum throughput in such networks. Finally, we investigate the application of STR in cellular systems and study two new unique interferences introduced to the system due to STR, namely BS-BS interference and UE-UE interference. We show that these two new interferences will hugely degrade system performance if not treated appropriately. We propose novel methods to reduce both interferences and investigate the performances in system level.

Downlink scheduling schemes are well-known and widely investigated under the assumption that the channel state is perfectly known to the scheduler. In the multiuser MIMO (broadcast) case, downlink scheduling in the presence of non-perfect channel state information (CSI) is only scantly treated. In this paper we provide a general framework that addresses the problem systematically. Also, we illuminate the key role played by the channel state prediction error: our scheme treats in a fundamentally different way users with small channel prediction error ("predictable" users) and users with large channel prediction error ("non-predictable" users), and can be interpreted as a near-optimal opportunistic time-sharing strategy between MIMO downlink beamforming to predictable users and space-time coding to non-predictable users. Our results, based on a realistic MIMO channel model used in 3GPP standardization, show that the proposed algorithms can significantly outperform a conventional "mismatched" scheduling scheme that treats the available CSI as if it was perfect.

MIMO Downlink Scheduling with Non-Perfect Channel State Knowledge

A hybrid digital and analog beamforming device for a node operable with an antenna array is disclosed. In an example, the hybrid digital and analog beamforming device can include computer circuitry configured to: Segment antenna elements of an antenna array into at least two groups of antenna elements; map antenna ports for transmission chains to one group of the antenna elements; constrain digital precoding weights for a digital precoder for the antenna elements, where the digital precoding weight includes a digital phase and amplitude; and determine analog precoding weights for an analog precoder for the antenna elements, where the analog precoding weight includes an analog phase.

Hybrid digital and analog beamforming for large antenna arrays

Channel state feedback schemes for the MIMO broadcast downlink have been widely studied in the frequency flat case. This work focuses on the more relevant frequency selective case, where some important new aspects emerge. We consider a MIMO-OFDM broadcast channel and compare achievable ergodic rates under three channel state feedback schemes: analog feedback, direction quantized feedback and "time-domain" channel quantized feedback. The first two schemes are direct extensions of previously proposed schemes. The third scheme is novel, and it is directly inspired by rate-distortion theory of Gaussian correlated sources. For each scheme we derive the conditions under which the system achieves full multiplexing gain. The key difference with respect to the widely treated frequency-flat case is that in MIMO-OFDM the frequency domain channel transfer function is a Gaussian correlated source. The new time-domain quantization scheme takes advantage of the channel frequency correlation structure and outperforms the other schemes. Furthermore, it is by far simpler to implement than complicated spherical vector quantization. In particular, we observe that no structured codebook design and vector quantization is actually needed for efficient channel state information feedback.

Hooman Shirani-Mehr

Papers

Simultaneous Transmission and Reception: Algorithm, Design and System Level Performance

Simultaneous Transmission and Reception: Algorithm, Design and System Level Performance

MIMO Downlink Scheduling with Non-Perfect Channel State Knowledge

Hybrid digital and analog beamforming for large antenna arrays

Channel state feedback schemes for multiuser MIMO-OFDM downlink