Energy Optimization for Hybrid ARQ

Hybrid automatic repeat request (HARQ) \cite{costello1983error} plays an important role in providing reliable and efficient data transmission. In wireless communications, the wireless channel may vary fast, due to the mobility of the transmitter/receiver and the channel. Forward error correction (FEC) and automatic repeat request (ARQ) are two basic techniques to control errors. FEC employs error correction coding, by adding parity bits to the information bits, to combat channel errors. ARQ allows the receiver to request a retransmission of the packet when an error is detected in the received packet. HARQ gives protection to the wireless transmission by combining FEC and ARQ. In typical HARQ systems, redundancy is added to the information bits, and a retransmission is performed until either the packet is successfully decoded, or a maximum number of transmissions is reached.The motivation to optimize the energy consumption of HARQ is the high energy consumption of wireless communications on mobile devices. Wireless devices usually have a limited battery life, and wireless communications consume the majority of the battery energy of mobile devices. One example is that 3G and Wifi units consume more than 50\% of the energy for some smart phones \cite{tawalbeh2016studying}. Another example is that battery depletion has been identified as one of the primary factors that limit the lifetime of wireless sensor networks \cite{verdone2010wireless}.Previous works on HARQ mainly use information-theoretic approach, which assumes that the number of bits in each transmission round is sufficiently large. This assumption does not necessarily hold for actual codes with finite length. Therefore, in this dissertation, we consider HARQ with actual codes. We use turbo-coded HARQ, since turbo codes are well-known capacity-approaching codes \cite{berrou1993near} and widely used in standards such as 3GPP Long-Term Evolution (LTE) \cite{3gpp2007mulltiplexing}. We study the energy optimization for HARQ in two scenarios: the energy optimization for incremental redundancy (IR) HARQ, and the energy optimization for HARQ in wireless video transmission. For IR HARQ, each retransmission contains additional parity bits beyond those of the previous transmissions. For the first scenario, we consider different cases of channel state information (CSI) at the transmitter: the transmitter has no knowledge of any CSI, or knows the CSI in previous transmission rounds through a perfect feedback channel, or knows both current and previous CSI. The transmitter decides the forward error correction code rate based on the CSI it has. We minimize the energy consumption of turbo-coded HARQ, subject to a packet loss rate constraint. Numerical results show that the energy consumption of HARQ decreases when more CSI information is available at the transmitter. We also compare IR combining with both Chase combining and the system without combining, and IR combining yields the least energy consumption.For the second scenario, we formulate the problem as maximizing the video quality, subject to a constraint on the wireless transmission energy consumption. We consider multiple parameters in multiple layers in a wireless video transmission system: transmit power, alphabet size, FEC code rate, maximum number of transmissions and unequal video data importance. An analytical framework is proposed to include these parameters, which allows us to divide this problem into two sub-problems: data transmission and unequal error protection (UEP) for video content. The problem is tackled by solving the two sub-problems, which are done by exhaustive search and convex optimization, respectively. Simulations of different videos show that the proposed scheme outperforms methods using conventional data transmission and/or unequal error protection. For example, in the low SNR region, there is a total gain of 4.8 to 5.6dB on the peak signal-to-noise ratio of the received video compared to video transmission using conventional HARQ without any video UEP

Optimum hybrid error correction scheme under strict delay constraints

In packet-based wireless networks, media-based services often require a multicast-enabled transport that guarantees quasi error free transmission under strict delay constraints. Furthermore, both multicast and delay constraints deeply influence the architecture of erasure error recovery (EER). Therefore, we propose a general architecture of EER and study its optimization in this thesis. The architecture integrates overall existing important EER techniques: Automatic Repeat Request, Forward Error Correction and Hybrid ARQ techniques. Each of these EER techniques can be viewed as a special case of Hybrid Error Correction (HEC) schemes. Since the Gilbert-Elliott (GE) erasure error model has been proven to be valid for a wide range of packet based wireless networks, in this thesis, we present the general architecture and its optimization based on the GE channel model. The optimization target is to satisfy a certain target packet loss level under strict delay constraints efficiently. Through the optimization for a given real-time multicast scenario, the total needed redundancy information can be minimized by choosing the best HEC scheme automatically among the entire schemes included in the architecture. As a result, the performance of the optimum HEC scheme can approach the Shannon limit as closely as possible dynamically according to current channel state information.In Paket-basierten drahtlosen Netzwerken benötigen Medien-basierte Dienste oft Multicast-fähigen Transport, der quasi-fehlerfreie Übertragung unter strikten Zeitgrenzen garantiert. Außerdem beeinflussen sowohl Multicast als auch Zeitbegrenzungen stark die Architektur von Auslöschungs-Fehlerschutz (Erasure Error Recovery, EER). Daher stellen wir eine allgemeine Architektur der EER vor und untersuchen ihre Optimierung in dieser Arbeit. Die Architektur integriert alle wichtigen EER-Techniken: Automatic Repeat Request, Forward Error Correction und Hybrid ARQ. Jede dieser EER-Techniken kann als Spezialfall der Hybrid Error Correction (HEC) angesehen werden. Da das Gilbert-Elliot (GE) Auslöschungs-Fehler-Modell für einen weiten Bereich von Paket-basierten drahtlosen Netzwerken als gültig erwiesen wurde, präsentieren wir in dieser Arbeit die allgemeine Architektur und deren Optimierung basierend auf dem GE Kanalmodell. Zweck der Optimierung ist es, eine gewisse Ziel-Paketfehlerrate unter strikten Zeitgrenzen effizient zu erreichen. Durch die Optimierung für ein gegebenes Echtzeit-Mutlicast-Szenario kann die insgesamt benötigte Redundanz-Information minimiert werden. Dies erfolgt durch automatische Auswahl des optimalen HEC Schemas unter all den Schemata, die in die Architektur integriert sind. Das optimale HEC-Schema kann die Shannon Grenze so nahe wie möglich, dynamisch, entsprechend dem derzeitigen Kanalzustand, erreichen

Adaptive Resource Allocation for Statistical QoS Provisioning in Mobile Wireless Communications and Networks

Due to the highly-varying wireless channels over time, frequency, and space domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has become a recognized feature in the next-generation wireless networks. In this dissertation, we study the adaptive wireless resource allocation problems for statistical QoS provisioning, such as guaranteeing the specified delay-bound violation probability, upper-bounding the average loss-rate, optimizing the average goodput/throughput, etc., in several typical types of mobile wireless networks. In the first part of this dissertation, we study the statistical QoS provisioning for mobile multicast through the adaptive resource allocations, where different multicast receivers attempt to receive the common messages from a single base-station sender over broadcast fading channels. Because of the heterogeneous fading across different multicast receivers, both instantaneously and statistically, how to design the efficient adaptive rate control and resource allocation for wireless multicast is a widely cited open problem. We first study the time-sharing based goodput-optimization problem for non-realtime multicast services. Then, to more comprehensively characterize the QoS provisioning problems for mobile multicast with diverse QoS requirements, we further integrate the statistical delay-QoS control techniques — effective capacity theory, statistical loss-rate control, and information theory to propose a QoS-driven optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS requirements, sustainable traffic load, and the average loss rate through the adaptive resource allocations and queue management. Furthermore, we study the adaptive resource allocation problems for multi-layer video multicast to satisfy diverse statistical delay and loss QoS requirements over different video layers. In addition, we derive the efficient adaptive erasure-correction coding scheme for the packet-level multicast, where the erasure-correction code is dynamically constructed based on multicast receivers’ packet-loss statuses, to achieve high error-control efficiency in mobile multicast networks. In the second part of this dissertation, we design the adaptive resource allocation schemes for QoS provisioning in unicast based wireless networks, with emphasis on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and power allocation schemes for multi-user downlink transmissions (with independent messages) in cellular networks to maximize the delay-QoS-constrained sum system throughput. Second, we propose the delay-QoS-aware base-station selection schemes in distributed multiple-input-multiple-output systems. Third, we study the queueaware spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning. Analyses and simulations are presented to show the advantages of our proposed schemes and the impact of delay-QoS requirements on adaptive resource allocations in various environments