Automatic Secret Keys From Reciprocal MIMO Wireless Channels: Measurement and Analysis

Multipath fading is one of the primary factors for degrading the performance in a wireless network. Information theoretic and past research suggest the use various diversity techniques to combat fading in wireless networks. Antenna diversity, a form of diversity technique, when incorporated in a wireless transceiver increases the system capacity and is one of the effective methods to combat fading in wireless systems. Also, recent research by Laneman et.al., Sendonaris et.al. suggests that cooperation among users in a wireless networks is an effective approach for a better signal reception in multipath fading environments. The diversity gains obtained by cooperation among the users of a wireless network is termed as cooperative diversity . Although, prior research in cooperative diversity considers users equipped with single antenna, in practical scenarios users may be able to accommodate multiple antennas due to the recent advanced research in semiconductor industry. Hence, the primary purpose of this thesis is to design, simulate and analyze an end-end performance of multi-antenna wireless systems employing cooperative multi antenna relay nodes so as to exploit the cooperative diversity and antenna diversity simultaneously in a wireless networks. Three main contributions to the area of cooperative multiple-input multiple-output (MIMO) wireless systems is presented in this thesis. First, we perform information theoretic analysis to study the impact of antenna arrays on cooperative wireless networks and propose the best possible distribution of antenna arrays among the three terminals of a simple three terminal cooperative relay network. Second, we design, simulate, and analyze a cooperative multiple-input multiple-output (MIMO) wireless systems employing orthogonal space-time block codes as proposed by Alamouti in 1998 with a decode-and-forward (DF) relay terminal. We implement a maximal ratio combining receiver that provides almost twice the diversity gain with respect to point-point multiple input multiple output link. Finally, we implement a practical receiver for cooperative reception using multiple antennas at all nodes based on Bell-Labs Layered Space Time architecture (BLAST). We incorporate a practical adaptive decode-and-forward (DF) relaying technique for reliable signal retransmission for both Alamouti space-time coding and the BLAST schemes. Results presented in terms of bit error rates and throughput show that remarkable performance gains are achievable by combining the concepts drawn from space-time coding, cooperative relaying and array processing.

Ensuring reliable and secure communications in the increasingly pervasive beyond <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5{^{\text {th}}}$ </tex-math></inline-formula> generation (B5G) wireless networks is one of the key research challenges. Within the physical layer security (PLS) paradigm, the secret key generation (SKG) technique exploits the wireless channel’s randomness to generate symmetric secret keys for message encryption/decryption by legitimate communication nodes. The SKG procedure involves various steps such as wireless channel probing, quantization, information reconciliation, and privacy amplification to render effective symmetric secret key bits. This work proposes a novel multi-level channel quantization scheme, which for the given distribution of the channel envelopes’ gain, ensures an identical likelihood of the envelope samples falling into each quantization interval. Inspired by the classical companding transform (CT), the proposed probability integral transform (PIT)–based quantization scheme works in three sequential steps. First, average contiguous duration (ACD), a second-order fading statistics metric, is considered to select and bias the channel samples that are more likely to fall in the same quantization interval. Subsequently, by using an invertible transform the envelope values are transformed into samples drawn from a uniform distribution, which are then processed through a uniform quantizer. The proposed PIT-based transformation and quantization scheme aims to enhance the trade-offs between the SKG performance metrics namely the key generation rate (KGR), key disagreement rate (KDR), and the key randomness properties. A comprehensive performance analysis of the proposed PIT-based quantization scheme for generalized gamma (GG) fading channels is conducted and its performance is evaluated in relation to several channel and system parameters. Moreover, a comparative analysis of the proposed scheme with its counterparts in the literature is also provided to demonstrate its relative performance gains, where our proposed scheme is observed to outperform the existing schemes. Notably, when the correlation of the reciprocal channel is set to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\rho =0.8$ </tex-math></inline-formula>, the samples excursion qualification threshold is set to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$L=3$ </tex-math></inline-formula>, and GG fading conditions set as defined by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha =2$ </tex-math></inline-formula>, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\xi =1$ </tex-math></inline-formula>, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\upsilon =1$ </tex-math></inline-formula>, the proposed algorithm, which employs sample biasing and transformation, offers an average improvement of 0.02% in KGR and 0.15% in KDR performance compared to the conventional UQ scheme. Additionally, the algorithm demonstrates superior performance in all considered eight the National Institute of Standards and Technology (NIST) randomness tests, exemplified by an average P-value of 0.78 in the frequency monobit test. Furthermore, for the considered system and channel parameters the proposed algorithm provides an average improvement of 0.06% in KDR compared to cumulative distribution function (CDF)-based non-uniform quantization (CDF-NUQ).

Key generation rate and bit disagreement ratio are two main indicators to evaluate the performance of physical layer key generation (PLKG). This work explores the key generation performance in reconfigurable intelligent surface (RIS)-assisted PLKG, where a concrete scheme of key generation is proposed. Specifically, we first deduce the key generation rate expression based on estimation theory in RIS-assisted PLKG. Then we optimize the RIS reflecting coefficients with instantaneous channel state information to maximize the key generation rate. Finally, aiming at minimizing transmit power while guaranteeing key generation rate target, we formulate a power minimization problem in RIS-assisted PLKG. An alternating optimization algorithm is applied to solve the non-convex mixed-integer nonlinear programming. Simulation results demonstrate that the key generation rate of the proposed scheme is up to 197.5% higher than the existing relay-assisted scheme, and we successfully reduce the required transmit power by at least 6.6 dBm than without power minimization scheme.

Accurate channel state information (CSI) is a prerequisite for diversity and multiplexing gains in multiple-input multiple-output (MIMO) wireless systems. More refined CSI can be attained by bootstrapping channel estimation techniques. We propose adaptive filtering-based iterative channel estimators with the incorporation of an iterative receiver over a flat-fading MIMO wireless link. The performance of three different algorithms with the aid of hard decision feedback is evaluated and compared through simulations. We show that the least-mean-square algorithm is a reasonable choice among the other considered algorithms in terms of performance and feasibility.

The use of multiple antennas at both ends of a wireless link such as multiple-input multiple-output (MIMO) systems are now expected to hold the potential to drastically improve the spectral efficiency and link reliability in the future wireless communications. This is due to the fact that a MIMO channel can offer a capacity gain over a traditional single-input single-output (SISO) channel. These spectral efficiency gains often require accurate knowledge of the channel at the receiver, and some times at the transmitter as well. In this paper, we present the concept and discuss some ongoing research directions on the channel capacity of a MIMO wireless system. Preliminary simulations show linear increasing results in spectral efficiency of MIMO with an arbitrary number of transmit or receive antennas.

Received signal strength as one of the physical layer characteristics has been proven to be extracted as a secret key to secure communications carried out by two legitimate parties. Some of the previous secret key generation systems had low key generation speed and were indicated by the key generation value parameter and high bit difference indicated by the key disagreement value parameter. This paper proposes a system that can improve the similarity of RSS between legitimate parties by adding the Kalman Filter pre-process method. The increase in the similarity of received signal strength will be followed by a decrease in the difference in bits obtained so that it will reduce the number of bits wasted in the error-correcting component and will automatically increase the key generation value. The performance evaluation of the built system will be tested in an indoor environment with several scenarios and conditions. There are 2 scenarios used, namely the scenario in the classroom and laboratory and each of them has 2 conditions, namely static and dynamic. The test results show that the best performance is obtained when the Cl scenario and static condition with the key disagreement value of 0.41 and key generation value of 6.48 bps. The proposed system also shows better performance in terms of key disagreement value and key generation value compared to the previous system.

Multiple-input multiple-output (MIMO) wireless communication systems can achieve higher throughput through interference alignment. For a small number of users, determining the maximum possible degrees of freedom as well as the feasibility of interference alignment in MIMO systems is well studied. However, the issues of scheduling in systems employing interference alignment and serving a large number of users have received little attention so far. In this paper, we study the problem of joint scheduling, interference alignment, and packet admission control in MIMO wireless systems with the goal of maximizing system throughput subject to stability constraints. We formulate a stochastic network optimization problem and propose a scheduling and interference alignment (SIA) algorithm. In each time slot, SIA schedules some users among many competing ones to transmit data, and determines encoding and decoding matrices for the selected users. Packet admission control is performed in each time slot. In addition, we propose a heuristic semi-distributed algorithm (SDSIA), which has a lower computational complexity than the SIA algorithm. Via simulation, we evaluate the performance of SIA and SDSIA for different algorithm parameters and different numbers of users. We also compare the performance of SDSIA with other approaches which do not simultaneously exploit interference alignment and scheduling and find that the combination of these two techniques increases the achievable data rate dramatically.

Multiple transmit-receive antenna based wireless communication system is a well investigated area in the literature. However, within the scope of author’s knowledge there are few analytical frameworks which facilitate communication system design engineers to select the required transmit-receive antenna combination for a given quality of service (QoS) in terms of Bit Error Rate (BER) or Symbol Error Rate (SER). Most of such frameworks for Multiple-Input Multiple-Output (MIMO) wireless systems in the existing literature are lacking tightness between theoretical approximation and actual simulation results. The aim of investigation in this study is to provide theoretical expectation of receiver performance with MIMO wireless communication system within a given channel. In this study, new analytical performance bound frameworks with tighter lower bounds have been presented for different receivers for MIMO systems. On the basis of the presented analytical framework, a simulation platform has been established. The channel state information as well as expected quality of service is assumed to be known for simplicity. Rayleigh fading channel has been considered within simulation platform. Simulation results show that the proposed frameworks provide degree of tightness up to 100 times at Signal to Noise Ratio (SNR) 20 dB for (2x2) MIMO system in comparison to the existing frameworks. Few other MIMO antenna combinations have been considered in the evaluation process of the proposed framework.

Channel reciprocity is a very crucial component in establishing a secret key generation scheme. Non-simultaneous measurement conditions and noise cause low channel reciprocity, which is indicated by measurements of channel parameters that are not perfectly identical in both users. The stages of the secret key generation scheme that directly quantifies the channel parameters will have an impact on the high difference in the bits produced. In this paper, we propose the use of Modified Polynomial Regression methods to enhance channel reciprocity that would lower the rate of key disagreement between two users. We also propose a combination of the Modified Polynomial Regression method with multilevel quantization to overcome the trade-off between performance parameters, i.e. the key disagreement rate and key generation rate. The test results conducted in an indoor wireless environment show that our proposed scheme has better performance compared to the existing scheme in terms of increasing reciprocity, key generation rate and decreasing key disagreement rate. The resulting secret key has also fulfilled the randomness requirements set by the National Institutes of Standards and Technology statistical suite.

We present an algorithm that allows two users to establish a symmetric cryptographic key by incorporating the most important features of the wireless channel in vehicle-to-vehicle (V2V) communication. Non-reciprocity compensation is combined with turbo codes (TCs) for error reconciliation purposes. For fair comparisons, the indexing technique is applied in conjunction with the non-reciprocity compensation technique. A series of simulations are run to calculate key performance indicators (KPIs). High entropy values are obtained throughout all rounds of simulation during the key extraction process. Furthermore, simulation results indicate a significant improvement in bit mismatch rate (BMR) and key generation rate (KGR) when TCs are used. Increasing the number of iterations in the TC can significantly improve the Bit Error Rate (BER), thus generating more symmetric keys. The key generation rate was reported high ranging from 17 to 19 for the 256-bit symmetric keys per minute with TCs, while it is ranging from 2 to 5 when compared with a sample indexing technique published in the public domain. Finally, simulations proved also improvements for different key lengths as part of the error reconciliation process when TCs are used with an almost regular permutation (ARP) instead of a random permutation.

This chapter is attempted to provide a survey of the advanced concepts and related issues involved in Multiple Input Multiple Output (MIMO) systems. MIMO system technology has been considered as a really significant foundation on which to build the next and future generations of wireless networks. The chapter addresses advanced MIMO techniques such as polarization diversity and antenna selection. We gradually provide an overview of the MIMO features from basic to more advanced topics. The first sections of this chapter start by introducing the key aspects of theMIMO theory. TheMIMO systemmodel is first presented in a genericway. Then, we proceed to describe diversity schemes used in MIMO systems. MIMO technology could exploit several diversity techniques beyond the spatial diversity. These techniques essentially cover frequency diversity, time diversity and polarization diversity. We further provide the reader with a geometrically based models for MIMO systems. The virtue of this channel modeling is to adopt realisticmethods for modeling the spatio-temporal channel statistics from a physical wave-propagation viewpoint. Two classes for MIMO channel modeling will be described. These models involve the Geometry-based Stochastic ChannelModels (GSCM) and the Stochastic channel models. Besides the listedMIMO channel models already described, we derive and discuss capacity formulas for transmission over MIMO systems. The achieved MIMO capacities highlight the potential of spatial diversity for improving the spectral efficiency of MIMO channels. When Channel State Information (CSI) is available at both ends of the transmission link, the MIMO system capacity is optimally derived by using adaptive power allocation based on water-filling technique. The chapter continues by examining the combining techniques for multiple antenna systems. Combining techniques are motivated for MIMO systems since they enable the signal to noise ratio (SNR) maximization at the combiner output. The fundamental combing techniques are the Maximal Ratio Combining (MRC), the Selection Combining (SC) and the Equal Gain Combining(EGC). Once the combining techniques are analyzed, the reader is introduced to the beamforming processing as an optimal strategy for combining. The use of multiple antennas significantly improves the channel spectral efficiency. Nevertheless, this induces higher system complexity of the communication system and the communication system performance is effected due to correlation between antennas that need to be deployed at the same terminal. As such, the antenna selection algorithm for MIMO systems is presented. To elaborate on this point, we introduce Space time coding techniques for MIMO systems and we evaluate by simulation the performance of the communication system. Next, we emphasis on multi polarization techniques for MIMO systems. As a background, we presume that the reader has a thorough understanding of antenna theory. We recall the basic antenna theory and concepts that are used throughout the rest of the chapter. We rigorously introduce the 3D channel model over the Non-Line of Sight (NLOS) propagation channel for MIMO system with polarized antennas. We treat the depolarization phenomena and we study its effect on MIMO system capacity. The last section of the chapter provides a scenario for collaborative sensor nodes performing distributed MIMO system model which is devoted to sensor node localization in Wireless Sensor Networks. The localization algorithm is based on beamforming processing and was tested by simulation. Our chapter provides the reader by simulation examples for almost all the topics that have been treated for MIMO system development and key issues affecting achieved performance.

This paper discusses radiation pattern selection in multiple-input multiple-output (MIMO) wireless systems. Each receive antenna can be reconfigured to P distinct radiation patterns. We select radiation patterns in order to maximize instantaneous channel capacity. And we prove that for arbitrary correlation the maximum achievable diversity order of the pattern selection MIMO (PS-MIMO) system equals to the rank of the total correlation matrix of its full system so that the link reliability can be significantly improved. We propose a fast selection algorithm as the suboptimal solution for channel capacity maximization. For PS-MIMO systems over spatially correlated channels, we propose to use only a part of available radiation patterns based on the estimation of the correlation before performing the pattern search. Simulations are used to validate the theoretical results and illustrate the performances of proposed algorithms.

This paper considers a robust FIR precoder design problem for frequency-selective multiple-input multiple-output (MIMO) wireless systems under transmit power constraints with imperfect channel knowledge at the transmitter. The robust design problem requires finding the optimal power constrained FIR precoder for the worst-case channel model within a neighborhood of the estimated channel. The neighborhood is formed by placing a bound on Kullback-Leibler (KL) divergence between the actual and estimated channels. We show that the optimal power constrained FIR precoder designed for the estimated channel under the assumption of perfect channel knowledge is robust when channel uncertainties are measured by the KL divergence metric.

Internet-of-Things (IoT) networks generally contain resource-constrained devices that require an energy-efficient key generation procedure to producing secure keys at a faster rate. The physical characteristics of the wireless channel can be exploited to secure communication within IoT networks. In particular, secret keys can be generated by leveraging on the randomness of the wireless physical channel between two communicating parties. The conventional mechanism of generating keys at the physical layer, i.e., using channel probing, quantization, information reconciliation, and privacy amplification, may not be preferable for IoT devices. In addition, in some cases IoT devices may be deployed in static environments, wherein the channel coherence time is too high to generate keys at a faster rate and with the desired randomness. This study proposes a mapping table-based key distribution scheme for IoT environments, wherein multiple characteristics of the random channel are combined to improve not only the key generation rate (KGR) but also the key agreement rate (KAR) and bit error rate (BER). In the proposed scheme, both the channel magnitude and the phase are exploited in the key generation process. The proposed scheme is immune to channel estimation errors while providing sufficient randomness in the static environment. Additionally, the scheme is thoroughly investigated for different scenarios including the case of a smarter eavesdropper, which attempts to estimate the channel between the legitimate nodes. This case verifies the robustness of the proposed scheme in different settings and attack models.

In conventional ways of fast responding and high performing model predictive control using Field Programmable Gate Arrays (FPGA), the approaches developed are applicable only to Single Input Single Output System (SISO). Many real time systems are Multiple Input Multiple Output (MIMO) systems and loop interaction is a major concern and has to be reduced in control of MIMO systems. Also, direct digital control with ability to solve the Quadratic Programming (QP) problem online, which can be applied to complex systems with fast response time and/or embedded applications and with limited computational resource for supervisory control approach, is required in many complex industrial MIMO systems. A novel direct digital control of Model predictive controller with FPGA for a MIMO system which considers and reduces loop interaction and which can also be implemented with very less investment is proposed here. The system was modeled from first principles and then simulated in Labview environment for MIMO system. Implementation of the system and response was verified for a stirred tank system. The proposed system has good performance in terms of reduction in loop interaction which is a major concern in implementation of controller for MIMO systems. Also, direct digital control of MIMO system instead of supervisory control was accomplished.