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

Multiple Access for Massive Machine Type Communications

The internet we have known thus far has been an internet of people, as it has connected people with one another. However, these connections are forecasted to occupy only a minuscule of future communications. The internet of tomorrow is indeed: the internet of things. The Internet of Things (IoT) promises to improve all aspects of life by connecting everything to everything. An enormous amount of effort is being exerted to turn these visions into a reality. Sensors and actuators will communicate and operate in an automated fashion with no or minimal human intervention. In the current literature, these sensors and actuators are referred to as machines, and the communication amongst these machines is referred to as Machine to Machine (M2M) communication or Machine-Type Communication (MTC). As IoT requires a seamless mode of communication that is available anywhere and anytime, wireless communications will be one of the key enabling technologies for IoT. In existing wireless cellular networks, users with data to transmit first need to request channel access. All access requests are processed by a central unit that in return either grants or denies the access request. Once granted access, users' data transmissions are non-overlapping and interference free. However, as the number of IoT devices is forecasted to be in the order of hundreds of millions, if not billions, in the near future, the access channels of existing cellular networks are predicted to suffer from severe congestion and, thus, incur unpredictable latencies in the system. On the other hand, in random access, users with data to transmit will access the channel in an uncoordinated and probabilistic fashion, thus, requiring little or no signalling overhead. However, this reduction in overhead is at the expense of reliability and efficiency due to the interference caused by contending users. In most existing random access schemes, packets are lost when they experience interference from other packets transmitted over the same resources. Moreover, most existing random access schemes are best-effort schemes with almost no Quality of Service (QoS) guarantees. In this thesis, we investigate the performance of different random access schemes in different settings to resolve the problem of the massive access of IoT devices with diverse QoS guarantees. First, we take a step towards re-designing existing random access protocols such that they are more practical and more efficient. For many years, researchers have adopted the collision channel model in random access schemes: a collision is the event of two or more users transmitting over the same time-frequency resources. In the event of a collision, all the involved data is lost, and users need to retransmit their information. However, in practice, data can be recovered even in the presence of interference provided that the power of the signal is sufficiently larger than the power of the noise and the power of the interference. Based on this, we re-define the event of collision as the event of the interference power exceeding a pre-determined threshold. We propose a new analytical framework to compute the probability of packet recovery failure inspired by error control codes on graph. We optimize the random access parameters based on evolution strategies. Our results show a significant improvement in performance in terms of reliability and efficiency. Next, we focus on supporting the heterogeneous IoT applications and accommodating their diverse latency and reliability requirements in a unified access scheme. We propose a multi-stage approach where each group of applications transmits in different stages with different probabilities. We propose a new analytical framework to compute the probability of packet recovery failure for each group in each stage. We also optimize the random access parameters using evolution strategies. Our results show that our proposed scheme can outperform coordinated access schemes of existing cellular networks when the number of users is very large. Finally, we investigate random non-orthogonal multiple access schemes that are known to achieve a higher spectrum efficiency and are known to support higher loads. In our proposed scheme, user detection and channel estimation are carried out via pilot sequences that are transmitted simultaneously with the user's data. Here, a collision event is defined as the event of two or more users selecting the same pilot sequence. All collisions are regarded as interference to the remaining users. We first study the distribution of the interference power and derive its expression. Then, we use this expression to derive simple yet accurate analytical bounds on the throughput and outage probability of the proposed scheme. We consider both joint decoding as well as successive interference cancellation. We show that the proposed scheme is especially useful in the case of short packet transmission

Towards reliable communication in LTE-A connected heterogeneous machine to machine network

Machine to machine (M2M) communication is an emerging technology that enables heterogeneous devices to communicate with each other without human intervention and thus forming so-called Internet of Things (IoTs). Wireless cellular networks (WCNs) play a significant role in the successful deployment of M2M communication. Specially the ongoing massive deployment of long term evolution advanced (LTE-A) makes it possible to establish machine type communication (MTC) in most urban and remote areas, and by using LTE-A backhaul network, a seamless network communication is being established between MTC-devices and-applications. However, the extensive network coverage does not ensure a successful implementation of M2M communication in the LTE-A, and therefore there are still some challenges. Energy efficient reliable transmission is perhaps the most compelling demand for various M2M applications. Among the factors affecting reliability of M2M communication are the high endto-end delay and high bit error rate. The objective of the thesis is to provide reliable M2M communication in LTE-A network. In this aim, to alleviate the signalling congestion on air interface and efficient data aggregation we consider a cluster based architecture where the MTC devices are grouped into number of clusters and traffics are forwarded through some special nodes called cluster heads (CHs) to the base station (BS) using single or multi-hop transmissions. In many deployment scenarios, some machines are allowed to move and change their location in the deployment area with very low mobility. In practice, the performance of data transmission often degrades with the increase of distance between neighboring CHs. CH needs to be reselected in such cases. However, frequent re-selection of CHs results in counter effect on routing and reconfiguration of resource allocation associated with CH-dependent protocols. In addition, the link quality between a CH-CH and CH-BS are very often affected by various dynamic environmental factors such as heat and humidity, obstacles and RF interferences. Since CH aggregates the traffic from all cluster members, failure of the CH means that the full cluster will fail. Many solutions have been proposed to combat with error prone wireless channel such as automatic repeat request (ARQ) and multipath routing. Though the above mentioned techniques improve the communication reliability but intervene the communication efficiency. In the former scheme, the transmitter retransmits the whole packet even though the part of the packet has been received correctly and in the later one, the receiver may receive the same information from multiple paths; thus both techniques are bandwidth and energy inefficient. In addition, with retransmission, overall end to end delay may exceed the maximum allowable delay budget. Based on the aforementioned observations, we identify CH-to-CH channel is one of the bottlenecks to provide reliable communication in cluster based multihop M2M network and present a full solution to support fountain coded cooperative communications. Our solution covers many aspects from relay selection to cooperative formation to meet the user’s QoS requirements. In the first part of the thesis, we first design a rateless-coded-incremental-relay selection (RCIRS) algorithm based on greedy techniques to guarantee the required data rate with a minimum cost. After that, we develop fountain coded cooperative communication protocols to facilitate the data transmission between two neighbor CHs. In the second part, we propose joint network and fountain coding schemes for reliable communication. Through coupling channel coding and network coding simultaneously in the physical layer, joint network and fountain coding schemes efficiently exploit the redundancy of both codes and effectively combat the detrimental effect of fading conditions in wireless channels. In the proposed scheme, after correctly decoding the information from different sources, a relay node applies network and fountain coding on the received signals and then transmits to the destination in a single transmission. Therefore, the proposed schemes exploit the diversity and coding gain to improve the system performance. In the third part, we focus on the reliable uplink transmission between CHs and BS where CHs transmit to BS directly or with the help of the LTE-A relay nodes (RN). We investigate both type-I and type-II enhanced LTE-A networks and propose a set of joint network and fountain coding schemes to enhance the link robustness. Finally, the proposed solutions are evaluated through extensive numerical simulations and the numerical results are presented to provide a comparison with the related works found in the literature

逐次干渉除去を用いた多元接続システムのパワー割り当てに関する研究

In future wireless communication networks, the number of devices is likely to increase dramatically due to potential development of new applications such as the Internet of Things (IoT). Consequently, radio access network is required to support multiple access of massive users and achieve high spectral efficiency. From the information theoretic perspective, orthogonal multiple access protocols are suboptimal. To achieve the multiple access capacity, non-orthogonal multiple access protocols and multiuser detection (MUD) are required. For the non-orthogonal code-division multiple access (CDMA), several MUD techniques have been proposed to improve the spectrum efficiency. Successive interference cancellation (SIC) is a promising MUD techniques due to its low complexity and good decoding performance. Random access protocols are designed for the system with bursty traffic to reduce the delay, compared to the channelized multiple access. Since the users contend for the channel instead of being assigned by the base station (BS), collisions happen with a certain probability. If the traffic load becomes relatively high, the throughput of these schemes steeply falls down because of collisions. However, it has been well-recognized that more complex procedures can permit decoding of interfering signals, which is referred to as multi-packet reception (MPR). Also, an SIC decoder might decode more packets by successively subtracting the correctly decoded packets from the collision. Cognitive radio (CR) is an emerging technology to solve the problem of spectrum scarcity by dynamically sharing the spectrum. In the CR networks, the secondary users (SUs) are allowed to dynamically share the frequency bands with primary users (PUs) under primary quality-of-service (QoS) protection such as the constraint of interference temperature at the primary base station (PBS). For the uplink multiple access to the secondary base station (SBS), transmit power allocation for the SUs is critical to control the interference temperature at the PBS. Transmit power allocation has been extensively studied in various multiple access scenarios. The power allocation algorithms can be classified into two types, depending on whether the process is controlled by the base station (BS). For the centralized power allocation (CPA) algorithms, the BS allocates the transmit powers to the users through the downlink channels. For the random access protocols, there are also efforts on decentralized power allocation (DPA) that the users select transmit powers according to given distributions of power and probability, instead of being assigned the transmit power at each time slot by the BS. In this dissertation, the DPA algorithms for the random access protocols with SIC are investigated and new methods are proposed. First a decentralized multilevel power allocation algorithm to improve the MAC throughput performance is proposed, for the general SIC receiver that can decode multiple packets from one collision. Then an improved DPA algorithm to maximize the overall system sum rate is proposed, taking into account of both the MAC layer and PHY layer. Finally, a DPA algorithm for the CR secondary random access is proposed, considering the constraint of interference temperature and the practical assumption of imperfect cancellation. An opportunistic transmission protocol for the fading environment to further reduce the interference temperature is also proposed. For the future work, the optimal DPA for the random access with the SIC receiver is still an open problem. Besides, advanced multiple access schemes that aim to approach the multiple access capacity by combining the advantages of the network coded cooperation, the repetition slotted ALOHA, and the SIC receiver are also interesting.電気通信大学201

Coding in 802.11 WLANs

Forward error correction (FEC) coding is widely used in communication systems to correct transmis- sion errors. In IEEE 802.11a/g transmitters, convolutional codes are used for FEC at the physical (PHY) layer. As is typical in wireless systems, only a limited choice of pre-speci¯ed coding rates is supported. These are implemented in hardware and thus di±cult to change, and the coding rates are selected with point to point operation in mind. This thesis is concerned with using FEC coding in 802.11 WLANs in more interesting ways that are better aligned with application requirements. For example, coding to support multicast tra±c rather than simple point to point tra±c; coding that is cognisant of the multiuser nature of the wireless channel; and coding which takes account of delay requirements as well as losses. We consider layering additional coding on top of the existing 802.11 PHY layer coding, and investigate the tradeo® between higher layer coding and PHY layer modulation and FEC coding as well as MAC layer scheduling. Firstly we consider the joint multicast performance of higher-layer fountain coding concatenated with 802.11a/g OFDM PHY modulation/coding. A study on the optimal choice of PHY rates with and without fountain coding is carried out for standard 802.11 WLANs. We ¯nd that, in contrast to studies in cellular networks, in 802.11a/g WLANs the PHY rate that optimizes uncoded multicast performance is also close to optimal for fountain-coded multicast tra±c. This indicates that in 802.11a/g WLANs cross-layer rate control for higher-layer fountain coding concatenated with physical layer modulation and FEC would bring few bene¯ts. Secondly, using experimental measurements taken in an outdoor environment, we model the chan- nel provided by outdoor 802.11 links as a hybrid binary symmetric/packet erasure channel. This hybrid channel o®ers capacity increases of more than 100% compared to a conventional packet erasure channel (PEC) over a wide range of RSSIs. Based upon the established channel model, we further consider the potential performance gains of adopting a binary symmetric channel (BSC) paradigm for multi-destination aggregations in 802.11 WLANs. We consider two BSC-based higher-layer coding approaches, i.e. superposition coding and a simpler time-sharing coding, for multi-destination aggre- gated packets. The performance results for both unicast and multicast tra±c, taking account of MAC layer overheads, demonstrate that increases in network throughput of more than 100% are possible over a wide range of channel conditions, and that the simpler time-sharing approach yields most of these gains and have minor loss of performance. Finally, we consider the proportional fair allocation of high-layer coding rates and airtimes in 802.11 WLANs, taking link losses and delay constraints into account. We ¯nd that a layered approach of separating MAC scheduling and higher-layer coding rate selection is optimal. The proportional fair coding rate and airtime allocation (i) assigns equal total airtime (i.e. airtime including both successful and failed transmissions) to every station in a WLAN, (ii) the station airtimes sum to unity (ensuring operation at the rate region boundary), and (iii) the optimal coding rate is selected to maximise goodput (treating packets decoded after the delay deadline as losses)

Zero-padding Network Coding and Compressed Sensing for Optimized Packets Transmission

Ubiquitous Internet of Things (IoT) is destined to connect everybody and everything on a never-before-seen scale. Such networks, however, have to tackle the inherent issues created by the presence of very heterogeneous data transmissions over the same shared network. This very diverse communication, in turn, produces network packets of various sizes ranging from very small sensory readings to comparatively humongous video frames. Such a massive amount of data itself, as in the case of sensory networks, is also continuously captured at varying rates and contributes to increasing the load on the network itself, which could hinder transmission efficiency. However, they also open up possibilities to exploit various correlations in the transmitted data due to their sheer number. Reductions based on this also enable the networks to keep up with the new wave of big data-driven communications by simply investing in the promotion of select techniques that efficiently utilize the resources of the communication systems. One of the solutions to tackle the erroneous transmission of data employs linear coding techniques, which are ill-equipped to handle the processing of packets with differing sizes. Random Linear Network Coding (RLNC), for instance, generates unreasonable amounts of padding overhead to compensate for the different message lengths, thereby suppressing the pervasive benefits of the coding itself. We propose a set of approaches that overcome such issues, while also reducing the decoding delays at the same time. Specifically, we introduce and elaborate on the concept of macro-symbols and the design of different coding schemes. Due to the heterogeneity of the packet sizes, our progressive shortening scheme is the first RLNC-based approach that generates and recodes unequal-sized coded packets. Another of our solutions is deterministic shifting that reduces the overall number of transmitted packets. Moreover, the RaSOR scheme employs coding using XORing operations on shifted packets, without the need for coding coefficients, thus favoring linear encoding and decoding complexities. Another facet of IoT applications can be found in sensory data known to be highly correlated, where compressed sensing is a potential approach to reduce the overall transmissions. In such scenarios, network coding can also help. Our proposed joint compressed sensing and real network coding design fully exploit the correlations in cluster-based wireless sensor networks, such as the ones advocated by Industry 4.0. This design focused on performing one-step decoding to reduce the computational complexities and delays of the reconstruction process at the receiver and investigates the effectiveness of combined compressed sensing and network coding

A hybrid packet loss recovery technique in wireless ad hoc networks

TCP utilization in wireless networks poses certain problems due to its inability to distinguish packet losses caused by congestion from those caused by frequent wireless errors, leading to degraded network performance. To avoid these problems and to minimize the effect of intensive channel contention in wireless networks, this work presents a new Hybrid ARQ technique for reliable and efficient packets transfer in static wireless ad hoc network. It is a combination of recent FEC based Raptor coding technique with ARQ based selective retransmission method, which outperforms purely ARQ based method. In contrast to most Hybrid ARQ techniques, which usually employ a byte level FEC, we mostly use packet level FEC in our simulations for the data transfer, on top of less frequent ARQ to recover the residual errors. Existing packet level FEC methods are mostly based on simple parity check codes or Reed Solomon codes with erasure decoding; in this work we use the recent raptor codes. We also introduce the notion of adaptive redundancy which helps to achieve better average network performance and to further improve the redundancy efficiency