Diversity analysis, code design, and tight error rate lower bound for binary joint network-channel coding

Joint network-channel codes (JNCC) can improve the performance of communication in wireless networks, by combining, at the physical layer, the channel codes and the network code as an overall error-correcting code. JNCC is increasingly proposed as an alternative to a standard layered construction, such as the OSI-model. The main performance metrics for JNCCs are scalability to larger networks and error rate. The diversity order is one of the most important parameters determining the error rate. The literature on JNCC is growing, but a rigorous diversity analysis is lacking, mainly because of the many degrees of freedom in wireless networks, which makes it very hard to prove general statements on the diversity order. In this article, we consider a network with slowly varying fading point-to-point links, where all sources also act as relay and additional non-source relays may be present. We propose a general structure for JNCCs to be applied in such network. In the relay phase, each relay transmits a linear transform of a set of source codewords. Our main contributions are the proposition of an upper and lower bound on the diversity order, a scalable code design and a new lower bound on the word error rate to assess the performance of the network code. The lower bound on the diversity order is only valid for JNCCs where the relays transform only two source codewords. We then validate this analysis with an example which compares the JNCC performance to that of a standard layered construction. Our numerical results suggest that as networks grow, it is difficult to perform significantly better than a standard layered construction, both on a fundamental level, expressed by the outage probability, as on a practical level, expressed by the word error rate

Computationally Efficient Multi-Antenna Techniques for Multi-User Two-Way Wireless Relay Networks

In this work, we are interested in implementing, developing and evaluating multi-antenna techniques used for multi-user two-way wireless relay networks that provide a good tradeoff between the computational complexity and performance in terms of symbol error rate and achievable data rate. In particular, a variety of newly multi-antenna techniques is proposed and studied. Some techniques based on orthogonal projection enjoy low computational complexity. However, the performance penalty associated with them is high. Other techniques based on maximum likelihood strategy enjoy high performance, however, they suffer from very high computational complexity. The Other techniques based on randomization strategy provide a good trade-off between the computational complexity and performance where they enjoy low computational complexity with almost the same performance as compared to the techniques based on maximum likelihood strategy

Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey

Integrated sensing and communication (ISAC) has the advantages of efficient spectrum utilization and low hardware cost. It is promising to be implemented in the fifth-generation-advanced (5G-A) and sixth-generation (6G) mobile communication systems, having the potential to be applied in intelligent applications requiring both communication and high-accurate sensing capabilities. As the fundamental technology of ISAC, ISAC signal directly impacts the performance of sensing and communication. This article systematically reviews the literature on ISAC signals from the perspective of mobile communication systems, including ISAC signal design, ISAC signal processing algorithms and ISAC signal optimization. We first review the ISAC signal design based on 5G, 5G-A and 6G mobile communication systems. Then, radar signal processing methods are reviewed for ISAC signals, mainly including the channel information matrix method, spectrum lines estimator method and super resolution method. In terms of signal optimization, we summarize peak-to-average power ratio (PAPR) optimization, interference management, and adaptive signal optimization for ISAC signals. This article may provide the guidelines for the research of ISAC signals in 5G-A and 6G mobile communication systems.Comment: 25 pages, 13 figures, 8 tables. IEEE Internet of Things Journal, 202

Goodbye, ALOHA!

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The vision of the Internet of Things (IoT) to interconnect and Internet-connect everyday people, objects, and machines poses new challenges in the design of wireless communication networks. The design of medium access control (MAC) protocols has been traditionally an intense area of research due to their high impact on the overall performance of wireless communications. The majority of research activities in this field deal with different variations of protocols somehow based on ALOHA, either with or without listen before talk, i.e., carrier sensing multiple access. These protocols operate well under low traffic loads and low number of simultaneous devices. However, they suffer from congestion as the traffic load and the number of devices increase. For this reason, unless revisited, the MAC layer can become a bottleneck for the success of the IoT. In this paper, we provide an overview of the existing MAC solutions for the IoT, describing current limitations and envisioned challenges for the near future. Motivated by those, we identify a family of simple algorithms based on distributed queueing (DQ), which can operate for an infinite number of devices generating any traffic load and pattern. A description of the DQ mechanism is provided and most relevant existing studies of DQ applied in different scenarios are described in this paper. In addition, we provide a novel performance evaluation of DQ when applied for the IoT. Finally, a description of the very first demo of DQ for its use in the IoT is also included in this paper.Peer ReviewedPostprint (author's final draft

A Survey of Blind Modulation Classification Techniques for OFDM Signals

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed

Practical packet combining for use with cooperative and non-cooperative ARQ schemes in wireless sensor networks

Although it is envisaged that advances in technology will follow a "Moores Law" trend for many years to come, one of the aims of Wireless Sensor Networks (WSNs) is to reduce the size of the nodes as much as possible. The issue of limited resources on current devices may therefore not improve much with future designs as a result. There is a pressing need, therefore, for simple, efficient protocols and algorithms that can maximise the use of available resources in an energy efficient manner. In this thesis an improved packet combining scheme useful on low power, resource-constrained sensor networks is developed. The algorithm is applicable in areas where currently only more complex combining approaches are used. These include cooperative communications and hybrid-ARQ schemes which have been shown to be of major benefit for wireless communications. Using the packet combining scheme developed in this thesis more than an 85% reduction in energy costs are possible over previous, similar approaches. Both simulated and practical experiments are developed in which the algorithm is shown to offer up to approximately 2.5 dB reduction in the required Signal-to-Noise ratio (SNR) for a particular Packet Error Rate (PER). This is a welcome result as complex schemes, such as maximal-ratio combining, are not implementable on many of the resource constrained devices under consideration. A motivational side study on the transitional region is also carried out in this thesis. This region has been shown to be somewhat of a problem for WSNs. It is characterised by variable packet reception rate caused by a combination of fading and manufacturing variances in the radio receivers. Experiments are carried out to determine whether or not a spread-spectrum architecture has any effect on the size of this region, as has been suggested in previous work. It is shown that, for the particular setup tested, the transitional region still has significant extent even when employing a spread-spectrum architecture. This result further motivates the need for the packet combining scheme developed as it is precisely in zones such as the transitional region that packet combining will be of most benefit

Simultaneous wireless information and power transfer in full-duplex communication systems

As wireless devices are mostly constrained by their inability to operate independently infinitely away from centralised power sources, radio frequency (RF) energy harvesting (EH) has been identified as a promising technique for future wireless devices. For this reason, this thesis introduces a novelty in RF EH full-duplex (FD) wireless communication systems. Specifically, this thesis investigate the potentials of simultaneous wireless information and power transfer (SWIPT) in FD communication systems. This thesis firstly focuses on optimal transmit strategies, rate maximization and power minimizing approach for SWIPT in FD systems. Using the rate-split method, difference of convex programming, semi-definite programming technique and one-dimensional search, we reformulate complex optimization problems to yield problem formulations that can be efficiently solved, thus we develop rate maximization algorithm for SWIPT in a point-to-point FD system, SWIPT in FD multiple-input multiple-output (MIMO) two-way relay system and power minimization approach for SWIPT in a multiuser MIMO FD system. This thesis also presents research work carried out with the aim of maximising the secrecy sum-rate for SWIPT in FD systems. In this context, we employ the use of an amplify and forward (AF) relay to inject artificial noise (AN) in order to confuse the eavesdropper. Thus, we address the optimal joint design of the beamforming matrix and AN covariance matrix at the relay, and the transmit power at the sources. Comprehensively, we present extensive theoretical and computer simulations to corroborate the need for joint optimization