Iterative Equalization and Interference Alignment for Multiuser MIMO HetNets with Imperfect CSI

In this paper we consider a scenario, where several small-cells work under the same coverage area and spectrum of a macrocell. The signals stemming from the small-cell (macrocell) users if not carefully dealt with will generate harmful interference into the macrocell (small-cell). To tackle this problem interference alignment and iterative equalization techniques are considered. By using IA all interference generated by the small-cell (macrocell) users is aligned along a low dimensional subspace, at the macrocell (small-cells). This reduces considerably the amount of resources allocated, to enable the coexistence of the two systems. However, perfect IA requires the availability of error-free channel state information (CSI) at the transmitters. Due to CSI errors one can have substantial performance degradation due to imperfect alignments. Since in this work the IA precoders are based on imperfect CSI, an efficient iterative space-frequency equalization is designed at the receiver side to cope with the residual aligned interference.The results demonstrate that iterative equalization is robust to imperfect CSI and removes efficiently the interference generated by the poorly aligned interference. Close to matched filter bound performance is achieved, with a very few number of iterations

D13.2 Techniques and performance analysis on energy- and bandwidth-efficient communications and networking

Deliverable D13.2 del projecte europeu NEWCOM#The report presents the status of the research work of the various Joint Research Activities (JRA) in WP1.3 and the results that were developed up to the second year of the project. For each activity there is a description, an illustration of the adherence to and relevance with the identified fundamental open issues, a short presentation of the main results, and a roadmap for the future joint research. In the Annex, for each JRA, the main technical details on specific scientific activities are described in detail.Peer ReviewedPostprint (published version

Nonorthogonal Multiple Access for 5G and Beyond

This work was supported in part by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/N029720/1 and Grant EP/N029720/2. The work of L. Hanzo was supported by the ERC Advanced Fellow Grant Beam-me-up

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

D13.1 Fundamental issues on energy- and bandwidth-efficient communications and networking

Deliverable D13.1 del projecte europeu NEWCOM#The report presents the current status in the research area of energy- and bandwidth-efficient communications and networking and highlights the fundamental issues still open for further investigation. Furthermore, the report presents the Joint Research Activities (JRAs) which will be performed within WP1.3. For each activity there is the description, the identification of the adherence with the identified fundamental open issues, a presentation of the initial results, and a roadmap for the planned joint research work in each topic.Preprin

Adjustable dynamic range for paper reduction schemes in large-scale MIMO-OFDM systems

In a multi-input-multi-output (MIMO) communication system there is a necessity to limit the power that the output antenna amplifiers can deliver. Their signal is a combination of many independent channels, so the demanded amplitude can peak to many times the average value. The orthogonal frequency division multiplexing (OFDM) system causes high peak signals to occur because many subcarrier components are added by an inverse discrete Fourier transformation process at the base station. This causes out-of-band spectral regrowth. If simple clipping of the input signal is used, there will be in-band distortions in the transmitted signals and the bit error rate will increase substantially. This work presents a novel technique that reduces the peak-to-average power ratio (PAPR). It is a combination of two main stages, a variable clipping level and an Adaptive Optimizer that takes advantage of the channel state information sent from all users in the cell. Simulation results show that the proposed method achieves a better overall system performance than that of conventional peak reduction systems in terms of the symbol error rate. As a result, the linear output of the power amplifiers can be minimized with a great saving in cost

MIMO-based Friendly Jamming and Interference Management Techniques for Secure Wireless Communications

The ever-increasing growth of wireless systems has made them an essential part of our daily life. People rely heavily on wireless networks for communications and to conduct critical transactions from their mobile devices, including financial transactions, access to health records, etc. The proliferation of wireless communication devices opens the door for many security breaches, ranging from eavesdropping to jamming attacks. Such a disadvantage stems from the broadcast nature of wireless transmissions, which creates an exposed environment. In this dissertation, we focus on eavesdropping attacks. While cryptographic techniques can be used to thwart eavesdropping attacks and enable secure wireless communications, they are not sufficient to protect the lower-layer headers of a packet (i.e., PHY and MAC headers). Hence, even though the secret message is encrypted, these unencrypted headers can be exploited by an adversary to extract invaluable information and initiate malicious attacks (e.g., traffic classification). Physical-layer (PHY-layer) security has been introduced as a promising candidate to prevent attacks that exploit unencrypted lower layer headers. PHY-layer security techniques typically rely on injecting an intentional interference into the medium so as to confuse nearby eavesdroppers (Eve). Specifically, a legitimate transmit-receive (Alice-Bob) pair generates a bogus signal, namely friendly jamming (FJ), along with the information signal, to increase interference at Eve(s) but without affecting the legitimate receiver (Bob). Depending on which end of a legitimate link is responsible for generating the FJ signal, two types of FJ techniques exist: transmitter-based (TxFJ) and receiver-based (RxFJ). In this dissertation, we propose to advance the state-of-art in PHY-layer security by considering multi-link scenarios, including multi-user multiple-input multiple-output (MU-MIMO) and peer-to-peer (P2P) networks. Specifically, we consider a scenario where one or more external Eve(s) attempt to snoop on communications of various links. In such networks, transmission of one link may be interfered with neighboring links' transmissions. Thus, special care must be dedicated to handling interference. In our first contribution in this dissertation, we consider a P2P network tapped by external Eve(s) in which each Alice-Bob pair conceals its communications using TxFJ. TxFJ is realized at Alice side using MIMO precoding. The goal is to design the precoders for both information and TxFJ signals at all Alices so as to maximize a given utility (e.g., sum of communication rates) while preventing eavesdropping elsewhere. Because legitimate links do not cooperate with each other and there is no centralized authority to perform optimization, every link selfishly aims at maximizing its secrecy rate. Using non-cooperative game theory, we design a distributed method for maximizing the sum of secrecy rates. Under the exact knowledge of eavesdropping channels, we show that our distributed method has a comparable secrecy sum-rate to a centralized approach. In our next contribution, we focus on employing practical precoders in our design for a P2P network. Specifically, we employed a zero-forcing-based (ZF-based) precoder for the TxFJ of each Alice-Bob pair in a P2P network. We also assume that each link has a certain rate demand to be satisfied. In such a scenario, even though the non-cooperative game designed for this P2P network is shown to be convergent to its unique Nash Equilibrium (NE), there is still no guarantee that the resulting NE is Pareto-optimal. Hence, we propose a modified price-based game, in which each link is penalized for generating interference on other legitimate links. We show that the price-based game converges to the Pareto-optimal point of secrecy rate region. We then leverage mixed-strategy games to provide solutions that are robust to uncertainties in knowledge of eavesdropping channels. The proposed ZF-based design of precoders is also implemented on software-defined radios to assess its performance on a single link in real-world scenarios. In another contribution of this dissertation, we consider to further enhance the secrecy of each link in a P2P network by equipping each receiver with RxFJ. Hence, in addition to the power allocation between TxFJ and information signals, we optimize RxFJ power as well. We show that by using RxFJ at each Bob, we could leverage the well-established concept of concave games, which compared to non-convex games enjoy more simplified game-theoretic analysis. We derive sufficient conditions under which the game admits a unique NE. We also propose another version of our power control algorithm that can be implemented asynchronously, making it robust to transmission delays in the network. In our last contribution, we consider the downlink of a MU-MIMO network in the presence of an external Eve. No knowledge of Eve's location is assumed at the access point. The network is studied in underloaded and overloaded conditions. In an underloaded (overloaded) network, the number of antennas at the access point is larger (smaller) than the total number of downlink users' antennas. In the overloaded setting, traditional methods of creating TxFJ, such as ZF-based methods, are infeasible. We propose a linear precoding scheme that relaxes such infeasibility in overloaded MU-MIMO networks. In the worst-case scenario where Eve has knowledge of the channels between access point and downlink users, we show that our method imposes the most stringent condition on the number of antennas required at Eve to cancel out TxFJ signals. We also show that choosing the number of independent streams to be sent to downlink users has an important role in achieving a tradeoff between security, reliability, and the achievable rate