A Time-Efficient Strategy For Relay Selection and Link Scheduling In Wireless Communication Networks

Despite the unprecedented success and proliferation of wireless communication, sustainable reliability and stability among wireless users are still considered important issues in the underlying link protocols. Existing link-layer protocols, like ARQ [44] or HARQ [57,67] approaches are designed to achieve this goal by discarding a corrupted packet at the receiver and performing one or more retransmissions until the packet is successfully decoded or a maximum number of retransmission attempts is reached. These strategies suffer from degradation of throughput and overall system instability since packets need to be en/decode in every hop, leading to high burden for relay nodes especially when the traffic load is high. On the other hand, due to the broadcast nature of wireless communication, when a relay transmits a packet to a specific receiver, it could become interference to other receivers. Thus, rather than activating all the relays simultaneously, we can only schedule a subset of relays in each time slot such that the interference among the links will not cause some transmissions to fail. Accordingly, in this dissertation, we mainly address the following two problems: 1) Relay selection: given a route (i.e., a sequence of relays), how to select the relays to en/decode packets to minimize the latency to reach the destination? 2) Link scheduling: how to schedule relays such that the interference among the relays will not cause transmission failure and the throughput is maximized? Relay Selection Problem. To solve the relay selection problem, we propose a Code Embedded Distributed Adaptive and Reliable (CEDAR) link-layer framework that targets low latency. CEDAR is the first theoretical framework for selecting en/decoding relays to minimize packet latency in wireless communication networks. It employs a theoretically-sound framework for embedding channel codes in each packet and performs the error correcting process in selected intermediate nodes in packet\u27s route. To identify the intermediate relay nodes for en/decoding to minimize average packet latency, we mathematically analyze the average packet delay, using Finite State Markovian Channel model and priority queuing model, and then formalize the problem as a non-linear integer programming problem. To solve this problem, we design a scalable and distributed scheme which has very low complexity. The experimental results demonstrate that CEDAR is superior to the schemes using hop-by-hop decoding and destination-decoding in terms of both packet delay and throughput. In addition, the simulation results show that CEDAR can achieve the optimal performance in most cases. Link Scheduling Problem. As for the link scheduling problem, we formulate a new problem called Fading-Resistant Link Scheduling (Fadin-R-LS) problem, which aims to maximize the throughput (the sum data rate) for all the links in a single time slot. The problem is different from the existing link scheduling problems by incorporating the Rayleigh-fading model to describe the interference. This model extends the deterministic interference model based on the Signal-to-Interference Ratio (SIR) using stochastic propagation to address fading effects in wireless networks. Based on the geometric structure of Fadin-R-LS, we then propose three centralized schemes for Fadin-R-LS, with O(g(L)), O(g(L)), and O(1) performance guarantee for packet latency, where g(L) is the number of length magnitudes of link set L. Furthermore, we propose a completely distributed approach based on game theory, which has O(g(L)^2\alpha) performance guarantee. Furthermore, we incorporate a cooperative communication (CC) technique, e.g., maximum ratio combining (MRC), into our system to further improve the throughput, in which receivers are allowed to combine messages from different senders to combat transmission errors. In particular, we formulate two problems named cooperative link scheduling problem (CLS) and one-shot cooperative link scheduling problem (OCLS). The first problem aims to find a schedule of links that uses the minimum number of time slots to inform all the receivers. The second problem aims to find a set of links that can inform the maximum number of receivers in one time slot. We prove both problems to be NP-hard. As a solution, we propose an algorithm for both CLS and OCLS with g(K) approximation ratio, where g(K) is so called the diversity of key links. In addition, we propose a greedy algorithm with O(1) approximation ratio for OCLS when the number of links for each receiver is upper bounded by a constant. In addition, we consider a special case for the link scheduling problem, where there is a group of vehicles forming a platoon and each vehicle in the platoon needs to communicate with the leader vehicle to get the leader vehicle\u27s velocity and location. By leveraging a typical feature of a platoon, we devise a link scheduling algorithm, called the Fast and Lightweight Autonomous link scheduling algorithm (FLA), in which each vehicle determines its own time slot simply based on its distance to the leader vehicle. Finally, we conduct a simulation on Matlab to evaluate the performance of our proposed methods. The experimental results demonstrate the superior performance of our link scheduling methods over the previous methods

Low Density Graph Codes And Novel Optimization Strategies For Information Transfer Over Impaired Medium

Effective methods for information transfer over an imperfect medium are of great interest. This thesis addresses the following four topics involving low density graph codes and novel optimization strategies.Firstly, we study the performance of a promising coding technique: low density generator matrix (LDGM) codes. LDGM codes provide satisfying performance while maintaining low encoding and decoding complexities. In the thesis, the performance of LDGM codes is extracted for both majority-rule-based and sum-product iterative decoding algorithms. The ultimate performance of the coding scheme is revealed through distance spectrum analysis. We derive the distance spectral for both LDGM codes and concatenated LDGM codes. The results show that serial-concatenated LDGM codes deliver extremely low error-floors. This work provides valued information for selecting the parameters of LDGM codes. Secondly, we investigate network-coding on relay-assisted wireless multiple access (WMA) networks. Network-coding is an effective way to increase robustness and traffic capacity of networks. Following the framework of network-coding, we introduce new network codes for the WMA networks. The codes are constructed based on sparse graphs, and can explore the diversities available from both the time and space domains. The data integrity from relays could be compromised when the relays are deployed in open areas. For this, we propose a simple but robust security mechanism to verify the data integrity.Thirdly, we study the problem of bandwidth allocation for the transmission of multiple sources of data over a single communication medium. We aim to maximize the overall user satisfaction, and formulate an optimization problem. Using either the logarithmic or exponential form of satisfaction function, we derive closed-form optimal solutions, and show that the optimal bandwidth allocation for each type of data is piecewise linear with respect to the total available bandwidth. Fourthly, we consider the optimization strategy on recovery of target spectrum for filter-array-based spectrometers. We model the spectrophotometric system as a communication system, in which the information content of the target spectrum is passed through distortive filters. By exploiting non-negative nature of spectral content, a non-negative least-square optimal criterion is found particularly effective. The concept is verified in a hardware implemen

Reliable Physical Layer Network Coding

When two or more users in a wireless network transmit simultaneously, their electromagnetic signals are linearly superimposed on the channel. As a result, a receiver that is interested in one of these signals sees the others as unwanted interference. This property of the wireless medium is typically viewed as a hindrance to reliable communication over a network. However, using a recently developed coding strategy, interference can in fact be harnessed for network coding. In a wired network, (linear) network coding refers to each intermediate node taking its received packets, computing a linear combination over a finite field, and forwarding the outcome towards the destinations. Then, given an appropriate set of linear combinations, a destination can solve for its desired packets. For certain topologies, this strategy can attain significantly higher throughputs over routing-based strategies. Reliable physical layer network coding takes this idea one step further: using judiciously chosen linear error-correcting codes, intermediate nodes in a wireless network can directly recover linear combinations of the packets from the observed noisy superpositions of transmitted signals. Starting with some simple examples, this survey explores the core ideas behind this new technique and the possibilities it offers for communication over interference-limited wireless networks.Comment: 19 pages, 14 figures, survey paper to appear in Proceedings of the IEE

Capacity Approaching Coding Strategies for Machine-to-Machine Communication in IoT Networks

Radio access technologies for mobile communications are characterized by multiple access (MA) strategies. Orthogonal MA techniques were a reasonable choice for achieving good performance with single user detection. With the tremendous growth in the number of mobile users and the new internet of things (IoT) shifting paradigm, it is expected that the monthly mobile data traffic worldwide will exceed 24.3 exabytes by 2019, over 100 billion IoT connections by 2025, and the financial impact of IoT on the global economy varies in the range of 3.9 to 11.1 trillion dollars by 2025. In light of the envisaged exponential growth and new trends, one promising solution to further enhance data rates without increasing the bandwidth is by increasing the spectral efficiency of the channel. Non-orthogonal MA techniques are potential candidates for future wireless communications. The two corner points on the boundary region of the MA channel are known to be achievable by single user decoding followed by successive decoding (SD). Other points can also be achieved using time sharing or rate splitting. On the other hand, machine-to-machine (M2M) communication which is an enabling technology for the IoT, enables massive multipurpose networked devices to exchange information among themselves with minor or no human intervention. This thesis consists of three main parts. In the first part, we propose new practical encoding and joint belief propagation (BP) decoding techniques for 2-user MA erasure channel (MAEC) that achieve any rate pair close to the boundary of the capacity region without using time sharing nor rate splitting. While at the encoders, the corresponding parity check matrices are randomly built from a half-rate LDPC matrix, the joint BP decoder employs the associated Tanner graphs of the parity check matrices to iteratively recover the erasures in the received combined codewords. Specifically, the joint decoder performs two steps in each decoding iteration: 1) simultaneously and independently runs the BP decoding process at each constituent sub-graph to recover some of the common erasures, 2) update the other sub-graph with newly recovered erasures and vice versa. When the number of erasures in the received combined codewords is less than or equal to the number of parity check constraints, the decoder may successfully decode both codewords, otherwise the decoder declares decoding failure. Furthermore, we calculate the probability of decoding failure and the outage capacity. Additionally, we show how the erasure probability evolves with the number of decoding iterations and the maximum tolerable loss. Simulations show that any rate pair close to the capacity boundary is achievable without using time sharing. In the second part, we propose a new cooperative joint network and rateless coding strategy for machine-type communication (MTC) devices in the multicast settings where three or more MTC devices dynamically form a cluster to disseminate messages between themselves. Specifically, in the basic cluster, three MTC devices transmit their respective messages simultaneously to the relay in the first phase. The relay broadcasts back the combined messages to all MTC devices within the basic cluster in the second phase. Given the fact that each MTC device can remove its own message, the received signal in the second phase is reduced to the combined messages coming from the other two MTC devices. Hence, this results in exploiting the interference caused by one message on the other and therefore improving the bandwidth efficiency. Furthermore, each group of three MTC devices in vicinity can form a basic cluster for exchanging messages, and the basic scheme extends to N MTC devices. Furthermore, we propose an efficient algorithm to disseminate messages among a large number of MTC devices. Moreover, we implement the proposed scheme employing practical Raptor codes with the use of two relaying schemes, namely amplify and forward (AF) and de-noise and forward (DNF). We show that with very little processing at the relay using DNF relaying scheme, performance can be further enhanced. We also show that the proposed scheme achieves a near optimal sum rate performance. In the third part, we present a comparative study of joint channel estimation and decoding of factor graph-based codes over flat fading channels and propose a simple channel approximation scheme that performs close to the optimal technique. Specifically, when channel state information (CSI) is not available at the receiver, a simpler approach is to estimate the channel state of a group of received symbols, then use the approximated value of the channel with the received signal to compute the log likelihood ratio. Simulation results show that the proposed scheme exhibits about 0.4 dB loss compared to the optimal solution when perfect CSI is available at the receiver

Coding for Cooperative Communications

The area of cooperative communications has received tremendous research interest in recent years. This interest is not unwarranted, since cooperative communications promises the ever-so-sought after diversity and multiplexing gains typically associated with multiple-input multiple-output (MIMO) communications, without actually employing multiple antennas. In this dissertation, we consider several cooperative communication channels, and for each one of them, we develop information theoretic coding schemes and derive their corresponding performance limits. We next develop and design practical coding strategies which perform very close to the information theoretic limits. The cooperative communication channels we consider are: (a) The Gaussian relay channel, (b) the quasi-static fading relay channel, (c) cooperative multiple-access channel (MAC), and (d) the cognitive radio channel (CRC). For the Gaussian relay channel, we propose a compress-forward (CF) coding strategy based on Wyner-Ziv coding, and derive the achievable rates specifically with BPSK modulation. The CF strategy is implemented with low-density parity-check (LDPC) and irregular repeataccumulate codes and is found to operate within 0.34 dB of the theoretical limit. For the quasi-static fading relay channel, we assume that no channel state information (CSI) is available at the transmitters and propose a rateless coded protocol which uses rateless coded versions of the CF and the decode-forward (DF) strategy. We implement the protocol with carefully designed Raptor codes and show that the implementation suffers a loss of less than 10 percent from the information theoretical limit. For the MAC, we assume quasi-static fading, and consider cooperation in the low-power regime with the assumption that no CSI is available at the transmitters. We develop cooperation methods based on multiplexed coding in conjunction with rateless codes and find the achievable rates and in particular the minimum energy per bit to achieve a certain outage probability. We then develop practical coding methods using Raptor codes, which performs within 1.1 dB of the performance limit. Finally, we consider a CRC and develop a practical multi-level dirty-paper coding strategy using LDPC codes for channel coding and trellis-coded quantization for source coding. The designed scheme is found to operate within 0.78 dB of the theoretical limit. By developing practical coding strategies for several cooperative communication channels which exhibit performance close to the information theoretic limits, we show that cooperative communications not only provide great benefits in theory, but can possibly promise the same benefits when put into practice. Thus, our work can be considered a useful and necessary step towards the commercial realization of cooperative communications

Near-capacity fixed-rate and rateless channel code constructions

Fixed-rate and rateless channel code constructions are designed for satisfying conflicting design tradeoffs, leading to codes that benefit from practical implementations, whilst offering a good bit error ratio (BER) and block error ratio (BLER) performance. More explicitly, two novel low-density parity-check code (LDPC) constructions are proposed; the first construction constitutes a family of quasi-cyclic protograph LDPC codes, which has a Vandermonde-like parity-check matrix (PCM). The second construction constitutes a specific class of protograph LDPC codes, which are termed as multilevel structured (MLS) LDPC codes. These codes possess a PCM construction that allows the coexistence of both pseudo-randomness as well as a structure requiring a reduced memory. More importantly, it is also demonstrated that these benefits accrue without any compromise in the attainable BER/BLER performance. We also present the novel concept of separating multiple users by means of user-specific channel codes, which is referred to as channel code division multiple access (CCDMA), and provide an example based on MLS LDPC codes. In particular, we circumvent the difficulty of having potentially high memory requirements, while ensuring that each user’s bits in the CCDMA system are equally protected. With regards to rateless channel coding, we propose a novel family of codes, which we refer to as reconfigurable rateless codes, that are capable of not only varying their code-rate but also to adaptively modify their encoding/decoding strategy according to the near-instantaneous channel conditions. We demonstrate that the proposed reconfigurable rateless codes are capable of shaping their own degree distribution according to the nearinstantaneous requirements imposed by the channel, but without any explicit channel knowledge at the transmitter. Additionally, a generalised transmit preprocessing aided closed-loop downlink multiple-input multiple-output (MIMO) system is presented, in which both the channel coding components as well as the linear transmit precoder exploit the knowledge of the channel state information (CSI). More explicitly, we embed a rateless code in a MIMO transmit preprocessing scheme, in order to attain near-capacity performance across a wide range of channel signal-to-ratios (SNRs), rather than only at a specific SNR. The performance of our scheme is further enhanced with the aid of a technique, referred to as pilot symbol assisted rateless (PSAR) coding, whereby a predetermined fraction of pilot bits is appropriately interspersed with the original information bits at the channel coding stage, instead of multiplexing pilots at the modulation stage, as in classic pilot symbol assisted modulation (PSAM). We subsequently demonstrate that the PSAR code-aided transmit preprocessing scheme succeeds in gleaning more information from the inserted pilots than the classic PSAM technique, because the pilot bits are not only useful for sounding the channel at the receiver but also beneficial for significantly reducing the computational complexity of the rateless channel decoder

Distributed Turbo Product Coding Techniques Over Cooperative Communication Systems

In this dissertation, we propose a coded cooperative communications framework based on Distributed Turbo Product Code (DTPC). The system uses linear block Extended Bose-Chaudhuri-Hochquenghem (EBCH) codes as component codes. The source broadcasts the EBCH coded frames to the destination and nearby relays. Each relay constructs a product code by arranging the corrected bit sequences in rows and re-encoding them vertically using EBCH as component codes to obtain an Incremental Redundancy (IR) for source\u27s data. Under this frame, we have investigated a number of interesting and important issues. First, to obtain, independent vertical parities from each relay in the same code space, we propose circular interleaving of the decoded EBCH rows before reencoding vertically. We propose and derive a novel soft information relay for the DTPC over cooperative network based on EBCH component codes. The relay generates Log-Likelihood Ratio (LLR) values for the decoded rows are used to construct a product code by re-encoding the matrix along the columns using a novel soft block encoding technique to obtain soft parity bits with different reliabilities that can be used as soft IR for source\u27s data which is forwarded to the destination. To minimize the overall decoding errors, we propose a power allocation method for the distributed encoded system when the channel attenuations for the direct and relay channels are known. We compare the performance of our proposed power allocation method with the fixed power assignments for DTPC system. We also develop a power optimization algorithm to check the validity of our proposed power allocation algorithm. Results for the power allocation and the power optimization prove on the potency of our proposed power allocation criterion and show the maximum possible attainable performance from the DTPC cooperative system. Finally, we propose new joint distributed Space-Time Block Code (STBC)-DTPC by generating the vertical parity on the relay and transmitting it to the destination using STBC on the source and relay. We tested our proposed system in a fast fading environment on the three channels connecting the three nodes in the cooperative network

Physical Layer Cooperation:Theory and Practice

Information theory has long pointed to the promise of physical layer cooperation in boosting the spectral efficiency of wireless networks. Yet, the optimum relaying strategy to achieve the network capacity has till date remained elusive. Recently however, a relaying strategy termed Quantize-Map-and-Forward (QMF) was proved to achieve the capacity of arbitrary wireless networks within a bounded additive gap. This thesis contributes to the design, analysis and implementation of QMF relaying by optimizing its performance for small relay networks, proposing low-complexity iteratively decodable codes, and carrying out over-the-air experiments using software-radio testbeds to assess real-world potential and competitiveness. The original QMF scheme has each relay performing the same operation, agnostic to the network topology and the channel state information (CSI); this facilitates the analysis for arbitrary networks, yet comes at a performance penalty for small networks and medium SNR regimes. In this thesis, we demonstrate the benefits one can gain for QMF if we optimize its performance by leveraging topological and channel state information. We show that for the N-relay diamond network, by taking into account topological information, we can exponentially reduce the QMF additive approximation gap from $\Theta(N)$ bits/s/Hz to $\Theta(\log N)$ bits/s/Hz, while for the one-relay and two-relay networks, use of topological information and CSI can help to gain as much as $6$ dB. Moreover, we explore what benefits we can realize if we jointly optimize QMF and half-duplex scheduling, as well as if we employ hybrid schemes that combine QMF and Decode-and-Forward (DF) relay operations. To take QMF from being a purely information-theoretic idea to an implementable strategy, we derive a structure employing Low-Density-Parity-Check (LDPC) ensembles for the relay node operations and message-passing algorithms for decoding. We demonstrate through extensive simulation results over the full-duplex diamond network, that our designs offer a robust performance over fading channels and achieves the full diversity order of our network at moderate SNRs. Next, we explore the potential real-world impact of QMF and present the design and experimental evaluation of a wireless system that exploits relaying in the context of WiFi. We deploy three main competing strategies that have been proposed for relaying, Amplify-and-Forward (AF), DF and QMF, on the WarpLab software radio platform. We present experimental results--to the best of our knowledge, the first ones--that compare QMF, AF and DF in a realistic indoor setting. We find that QMF is a competitive scheme to the other two, offering in some cases up to 12% throughput benefits and up to 60% improvement in frame error-rates over the next best scheme. We then present a more advanced architecture for physical layer cooperation (termed QUILT), that seamlessly adapts to the underlying network configuration to achieve competitive or better performance than the best current approaches. It combines on-demand, opportunistic use of DF or QMF followed by interleaving at the relay, with hybrid decoding at the destination that extracts information from even potentially undecodable received frames. We theoretically quantify how our design choices affect the system performance. We also deploy QUILT on WarpLab and show through over-the-air experiments up to $5$ times FER improvement over the next best cooperative protocol