We study differentially private data release, where a database is accessed through successive, possibly adaptive queries and mechanisms. Existing composition theorems and privacy filters almost always combine worst case per-round privacy parameters, leaving room for more refined accounting based on realised leakage, which we term realisation-level accounting. We present a realisation-level filtering approach to determine stopping times for data releases, and design one such filter. Despite technical challenges arising from conditioning on realisations and stopping time, we prove that the filter guarantees $(ε, δ)$-differential privacy, with $ε$ and $δ$ chosen by the data handler. Through numerical evidence, we demonstrate that realisation-level filtering provides a path to better utility beyond mechanism-level methods. Furthermore, our proposed filter applies to arbitrary mechanisms, including those that are badly behaved under Rényi differential privacy.

In this paper, we study the entropy of a hard random geometric graph (RGG), a commonly used model for spatial networks, where the connectivity is governed by the distances between the nodes. Formally, given a connection range $r$, a hard RGG $G_m$ on $m$ vertices is formed by drawing $m$ random points from a spatial domain, and then connecting any two points with an edge when they are within a distance $r$ from each other. The two domains we consider are the $d$-dimensional unit cube $[0,1]^d$ and the $d$-dimensional unit torus $\mathbb{T}^d$. We derive upper bounds on the entropy $H(G_m)$ for both these domains and for all possible values of $r$. In a few cases, we obtain an exact asymptotic characterization of the entropy by proving a tight lower bound. Our main results are that $H(G_m) \sim dm \log_2m$ for $0 < r \leq 1/4$ in the case of $\mathbb{T}^d$ and that the entropy of a one-dimensional RGG on $[0,1]$ behaves like $m\log m$ for all $0

Information leakage metrics quantify the amount of information about a private random variableXthat is leaked through a correlated variableY. They can be used to evaluate the privacy of a system in which an adversary, from whomXshould be kept private, observesY. Global information leakage metrics quantify the overall information leaked upon observing Y , whilst their pointwise counterparts define leakage as a function of the particular realisationY=y, and thus can be viewed as random variables. We consider an adversary who observes many conditionally independent identically distributed realisations ofY. We formalise the essential asymptotic behaviour of an information leakage metric, considering in turn what this means for pointwise and global metrics. With these requirements in mind, we take an axiomatic approach to defining a set of pointwise leakage metrics, and a set of global leakage metrics constructed from them. The global set encompasses many known measures including mutual information, Sibson mutual information, Arimoto mutual information, maximal leakage, min entropy leakage,f-divergence metrics, and g-leakage. We prove that both sets follow the desired asymptotic behaviour. Finally, we derive composition theorems quantifying the rate of privacy degradation as an adversary is given access to many conditionally independent observations ofY. We find that, for pointwise and global metrics, privacy degrades exponentially with increasing observations, at a rate governed by the minimum Chernoff information. This extends the work of Wu et al. (2024), who derived this result for certain known metrics, including some from our global set.

In this paper, we consider the rate-distortion-perception (RDP) trade-off for the lossy compression of a Bernoulli vector source, which is a finite collection of independent binary random variables. The RDP function quantifies in a way the efficient compression of a source when we impose a distortion constraint that limits the dissimilarity between the source and the reconstruction and a perception constraint that restricts the distributional discrepancy of the source and the reconstruction. In this work, we obtain an exact characterization of the RDP function of a Bernoulli vector source with the Hamming distortion function and a single-letter perception function that measures the closeness of the distributions of the components of the source using the total variation distance. The solution can be described by partitioning the set of distortion and perception levels$(D, P)$into three regions, where in each region the optimal distortion and perception levels we allot to the components have a similar nature. Finally, we introduce the RDP function for graph sources and apply our result to the Erdős-Rényi graph model.

We consider a two-ray channel model in which the distance between transmitter and receiver is only known up to an interval. Due to the unknown distance, destructive interference might occur which significantly reduces the receive power. To mitigate this problem, multiple frequencies can be used in parallel. In this work, we consider a worst-case design approach which allows maximizing the guaranteed quality of service (QoS) despite the uncertainty about the channel. First, we derive the worst-case receive power within the uncertainty region. Next, we compare different approaches to assign frequencies to the user such that the worst-case is maximized. We propose a greedy algorithm, which significantly outperforms standard baseline schemes while also being resource efficient. With this, the communication system can be designed such that a certain performance can always be guaranteed, and ultra-reliability is practically achieved.

Internet of Things (IoT) is an emerging next-generation technology in the fourth industrial revolution. The Industrial IoT is required to transmit the collected data in a timely manner to support real-time monitoring, control and automation. In such systems, the timeliness of information is very important, and meanwhile, different physical processes have different requirements on the accuracy of timeliness. However, existing performance metrics, such as the Age of Information (AoI), are unable to fully evaluate the timeliness of information with heterogeneous physical processes. Recently, we proposed an information-theoretic metric named the “Value of Information” (VoI) to measure the usefulness of information in the context of a heterogeneous and noisy environment. In this work, we study a joint path planning of the mobile robot and user scheduling optimization problem in Industrial IoT networks with the aim of maximizing the minimum VoI among all users under mobility and communication constraints. We formulate this optimization problem as a Markov decision process, and propose a reinforcement learning-based algorithm to find the VoI-aware mobility and communication strategy efficiently. Through numerical results, we show that the proposed method can capture the impact of data freshness, inherent correlation characteristics of underlying data sources and noise on the usefulness of information. Compared with the existing AoI-aware strategy, the proposed VoI-aware strategy achieves better performance by exploiting the heterogeneity of data sources especially when the wireless resource is limited.

In this paper, we address the lossy compression of spatial networks, namely random geometric graphs, where two nodes are connected by an edge with a probability that depends on the distance between the nodes. We carry out this study by considering the$n\mathbf{th}$order information-distortion function, which quantifies the complexity of a random graph under a distortion criterion. Our main result is a partial characterization of the information-distortion function for a random geometric graph with the Hamming distortion measure.

Building on recent trends in multiple-input multiple-output and reconfigurable intelligent surfaces, where densely spaced element arrays are considered, this paper focuses on con-tinuous antenna systems where the receive antenna is modelled as a continuous line (in the one-dimensional case) or a continuous surface (in the two-dimensional case). Considering a spatially-correlated Rayleigh process for the communication channel, we conduct an analytical investigation based on matched filtering. More specifically, we derive an approximated distribution for the instantaneous received signal-to-noise ratio (SNR) at the continuous surface. Furthermore, we derive approximations to the achievable rate, average symbol error rate for Mary phase shift keying (MPSK) and an upper bound for the achievable rate. We use extensive numerical examples to illustrate the accuracy of our approximation to the SNR distribution as well as the performance analysis.

Joint sensing and communication (JSAC) is regarded as a promising technology for future networks, which can reuse most devices of the systems in sensing and communication (S&C) and reduces the cost in terms of power and spectrum (P&S) critically. The current research considers the P&S allocation of S&C separately and then discusses the performance from different aspects. However, as an integrated system, the allocation strategy of P&S allocation affects the joint performance significantly. In this article, we use tools from stochastic geometry to study the coverage performance considering the trade-off of P&S allocation for JSAC with the principle requirements of small distance resolution (SDR) in sensing and high data rate (HDR) in communication. In particular, we model the locations of user equipment (UE) and base stations (BSs) as two different Poisson Point Processes and allocate P&S at BSs with two independent ratios. The sensing system will detect the surrounding environment and obtain UE positions. After that, an adaptive beamwidth for beamforming technology is applied in communication, which can save energy effectively. First, we introduce the distance resolution in sensing and special channel models in S&C with a high frequency. Then, considering the proposed system model, we separately model the interference in S&C. Further, the joint coverage probability (CP) of JSAC is derived as a function of densities of UE and BSs, required HDR and SDR, and allocation ratios of P&S. Finally, We draw multiple valuable system-level insights from the proposed analysis. For instance, we show that the SDR and HDR are the two main constraints to the maximum achievable CP with optimized allocations of P&S. Furthermore, we show that different densities of BSs should be considered in various scenarios. The revealed relationship between the densities of UE and BSs can be taken as a reference in practical applications.

Ensuring a reliable and simultaneously secure transmission of data is one of the major challenges for wireless communication systems. This is especially difficult when no perfect channel state information (CSI) at the transmitter is available. In this work, we consider a two-ray ground reflection scenario with a passive eavesdropper. At the transmitter, there only exists limited knowledge about the channels to both the legitimate receiver and the eavesdropper. We propose a simple frequency diversity scheme which maximizes the worst-case secrecy capacity for the considered scenario. In particular, we show how to optimally adjust the frequency spacing between the used frequencies. Thereby, we can guarantee a certain secrecy rate at which data can be transmitted both reliably and securely for all locations of the receivers.

We study the richness of the ensemble of graphical structures (i.e., unlabeled graphs) of the one-dimensional random geometric graph model defined by$n$nodes randomly scattered in [0, 1] that connect if they are within the connection range$r\in [{0,1}]$. We provide bounds on the number of possible structures which give universal upper bounds on the structural entropy that hold for any$n$,$r$and distribution of the node locations. For fixed$r$, the number of structures is$\Theta (a^{2n})$with$a=a(r)=2 \cos {\left ({\frac {\pi }{\lceil 1/r \rceil +2}}\right)}$, and therefore the structural entropy is upper bounded by$2n\log _{2} a(r) + O(1)$. For large$n$, we derive bounds on the structural entropy normalized by$n$, and evaluate them for independent and uniformly distributed node locations. When the connection range$r_{n}$is$O(1/n)$, the obtained upper bound is given in terms of a function that increases with$n r_{n}$and asymptotically attains 2 bits per node. If the connection range is bounded away from zero and one, the upper and lower bounds decrease linearly with$r$, as$2(1-r)$and$(1-r)\log _{2} e$, respectively. When$r_{n}$is vanishing but dominates$1/n$(e.g.,$r_{n} \propto \ln n / n$), the normalized entropy is between$\log _{2} e \approx 1.44$and 2 bits per node. We also give a simple encoding scheme for random structures that requires 2 bits per node. The upper bounds in this paper easily extend to the entropy of the labeled random graph model, since this is given by the structural entropy plus a term that accounts for all the permutations of node labels that are possible for a given structure, which is no larger than$\log _{2}(n!) = n \log _{2} n {-} n + O(\log _{2} n)$.

In this paper, we investigate the performance of a reconfigurable intelligent surface (RIS) assisted large-scale network by characterizing the coverage probability and the average achievable rate using stochastic geometry. Considering the spatial correlation between transmitters (TXs) and RISs, their locations are jointly modelled by a Gauss-Poisson process (GPP). Two association strategies, i.e., nearest association and fixed association, are both discussed. For the RIS-aided transmission, the signal power distribution with a direct link is approximated by a gamma random variable using a moment matching method, and the Laplace transform of the aggregate interference power is derived in closed form. Based on these expressions, we analyze the channel hardening effect in the RIS-assisted transmission, the coverage probability, and the average achievable rate of the typical user. We derive the coverage probability expressions for the fixed association strategy and the nearest association strategy in an interference-limited scenario in closed form. Numerical results are provided to validate the analysis and illustrate the effectiveness of RIS-assisted transmission with passive beamforming in improving the system performance. Furthermore, it is also unveiled that the system performance is independent of the density of TXs with the nearest association strategy in the interference-limited scenario.

Routing tables in ad hoc and wireless routing protocols can be represented using rooted trees. The constant need for communication and storage of these trees in routing protocols demands an efficient rooted tree coding algorithm. This efficiency is defined in terms of the average code length, and the optimality of the algorithm is measured by comparing the average code length with the entropy of the source. In this work, TreeExplorer is introduced as an easy-to-implement and nearly optimal algorithm for coding rooted tree structures. This method utilizes the number of leaves of the tree as an indicator for choosing the best method of coding. We show how TreeExplorer can improve existing routing protocols for ad hoc and wireless systems, which normally entails a significant communication overhead.

The freshness and usefulness of information play an important role in offering ubiquitous connectivity for time-critical control applications. A concept named value of information (VoI) is proposed based on the field of information theory to quantity the usefulness of data for sensor-assisted Internet of Things (IoT) networks in the presence of transmission noise. In this work, we focus on general Gaussian random process models and study the rate of change of the VoI when generating more data samples and increasing the signal-to-noise ratio (SNR). We further look at Gauss-Markov random process models, and investigate the impact of the number of observations and the SNR on the VoI performance. It is interesting to find that using more data samples is effective to improve the VoI only in the low SNR regime, while it yields zero rate of change of the VoI in the high SNR regime. Moreover, the VoI can be improved by increasing the SNR in both high and low SNR regimes regardless of how many samples are used. We also find a trade-off between the SNR and the number of observations, and scale back SNR to achieve the same VoI improvement by adding one extra observation. The results illustrated in this work can be used in the design of practical real-time IoT networks.

In this paper, we analyze the coverage probability of a reconfigurable intelligent surface (RIS) aided cellular network with the theory of stochastic geometry. A Poisson cluster process (PCP) is applied to model the positions of transmitters (TXs) and RISs, capturing their spatial correlations. Considering the general Nakagami-m fading channel model, we derive the approximate distributions of the composite channel gains with RIS-assisted transmission, representing the desired signal channel and the interference channel, respectively. The coverage probability of the typical user is then obtained. The derived coverage probability is in a closed form, which can be evaluated efficiently. Simulation results are presented to show that the presented analysis is effective, demonstrate the significant performance gains brought by the passive beamforming of a RIS with a large number of elements, and show the impact of TX density on the performance of the proposed system.

Due to dependence between codeword elements, index modulation (IM) and related modulation techniques struggle to provide simple solutions for practical problems such as Gray coding between information bits and constellation points; and low-complexity log-likelihood ratio (LLR) calculations for channel-encoded information bits. In this paper, we show that a modulation technique based on a simple maximum distance separable (MDS) code, in other words, MDS modulation, can provide simple yet effective solutions to these problems, rendering the MDS techniques more beneficial in the presence of coding. We also compare the coded error performance and complexity of the MDS methods with those of the IM methods and demonstrate that MDS modulation outperforms IM.

We consider a multi-user two-ray ground reflection scenario with unknown distances between transmitter and receivers. By using two frequencies per user in parallel, we can mitigate possible destructive interference and ensure ultra-reliability with only very limited knowledge at the transmitter. In this work, we consider the problem of assigning two frequencies to each receiver in a multi-user communication system such that the average minimum receive power is maximized. In order to solve this problem, we introduce a generalization of the quadratic multiple knapsack problem to include heterogeneous profits and develop an algorithm to solve it. Compared to random frequency assignment, we report a gain of around 6dB in numerical simulations.

In this paper, we propose two novel modulation concepts based on a simple maximum distance separable (MDS) code and show that these concepts can achieve better error performance than index modulation (IM) and related schemes. In the first concept, we use amplitude and phase levels to form a simple MDS code, whereas, in the second one, in-phase and quadrature components of codeword elements are used to construct the MDS code. We depict practical schemes for using the proposed concepts with orthogonal frequency division multiplexing (OFDM). We analyze the performance in terms of the minimum Euclidean distance and bit error rate. We also show that the proposed techniques exhibit desirable properties such as efficient low-complexity detection, very simple bits-to-symbols, and symbols-to-bits mappings, and a better error performance when compared to the OFDM-IM and related schemes. More importantly, contrary to the vast majority of IM studies that focus on showing the superiority of the IM techniques against conventional modulation techniques, we show that modulation concepts based on a well-known MDS code can achieve better error performance than the IM and related schemes while exhibiting a structure as simple as these schemes.

In this paper, a general framework is formalised to characterise the value of information (VoI) in hidden Markov models. Specifically, the VoI is defined as the mutual information between the current, unobserved status at the source and a sequence of observed measurements at the receiver, which can be interpreted as the reduction in the uncertainty of the current status given that we have noisy past observations of a hidden Markov process. We explore the VoI in the context of the noisy Ornstein-Uhlenbeck process and derive its closed-form expressions. Moreover, we investigate the effect of different sampling policies on VoI, deriving simplified expressions in different noise regimes and analysing statistical properties of the VoI in the worst case. We also study the optimal sampling policy to maximise the average information value under the sampling rate constraint. In simulations, the validity of theoretical results is verified, and the performance of VoI in Markov and hidden Markov models is also analysed. Numerical results further illustrate that the proposed VoI framework can support timely transmission in status update systems, and it can also capture the correlation properties of the underlying random process and the noise in the transmission environment.

In this paper, we derive closed-form expressions for significant statistical properties of the link signal-to-noise ratio (SNR) and the separation distance in mobile ad hoc networks subject to Ornstein-Uhlenbeck (OU) mobility and Rayleigh fading. In these systems, the SNR is a critical parameter as it directly influences link performance. In the absence of signal fading, the distribution of the link SNR depends exclusively on the squared distance between nodes, which is governed by the mobility model. In our analysis, nodes move randomly according to an Ornstein-Uhlenbeck process, using one tuning parameter to control the temporal dependency in the mobility pattern. We derive a complete statistical description of the squared distance and show that it forms a stationary Markov process. Then, we compute closed-form expressions for the probability density function (pdf), the cumulative distribution function (cdf), the bivariate pdf, and the bivariate cdf of the link SNR. Next, we introduce small-scale fading, modeled by a Rayleigh random variable, and evaluate the pdf of the link SNR for rational path loss exponents. The validity of our theoretical analysis is verified by extensive simulation studies. The results presented in this work can be used to quantify link uncertainty and evaluate stability in mobile ad hoc wireless systems.

This article proposes zero-forcing (ZF) beamforming strategies that can simultaneously deal with active and passive eavesdroppers in visible light communication (VLC) systems. First, we propose a ZF beamforming scheme that steers a transmission beam to the null space of active eavesdroppers' (AEDs) channel, while simultaneously considering the SNRs for a legitimate user (UE) and passive eavesdroppers (PEDs) residing at unknown locations. To find an eigenmode related to the optimal beamforming vector, we adopt an inverse free preconditioned Krylov subspace projection method. For unfavorable VLC secrecy environments, the proposed ZF beamformer appears to be incapable of effectively coping with the PEDs due to the strict condition that the data transmission must be in the null space of the AEDs' channel matrix. Hence, an alternative beamforming scheme is proposed by relaxing the constraint on the SNRs of the AEDs. The related optimization problem is formulated to reduce the secrecy outages caused by PEDs, while simultaneously satisfying the target constraints on the SNRs of the UE and the AEDs. To simplify the mathematical complexity of the approach, Lloyd's algorithm is employed to sample the SNR field, which in turn discretizes the problem, thus making it tractable for practical implementation. The numerical results show that both the exact and relaxed ZF beamforming methods achieve superior performance in the sense of secrecy outage relative to a benchmark ZF scheme. Moreover, the proposed relaxed ZF beamforming method is shown to cope with PEDs better than the exact ZF beamforming approach for unfavorable VLC environments.

This paper proposes a novel zero-forcing (ZF) beamforming strategy that can simultaneously cope with active and passive eavesdroppers (EDs) in visible light communication systems. A related optimization problem is formulated to maximize the signal-to-noise ratio (SNR) of the legitimate user (UE) while suppressing the SNR of active ED to zero and constraining the average SNR of passive EDs. The proposed beamforming directs the transmission along a particular eigenmode related to the null space of the active ED channel and the intensity of the passive ED point process. An inverse free preconditioned Krylov subspace projection method is used to find the eigenmode. The numerical results show that the proposed ZF beamforming scheme yields better performance relative to a traditional ZF beamforming scheme in the sense of increasing the SNR of the UE and reducing the secrecy outage probability.

In this paper, a general value of information (VoI) framework is formalised for latent variable models. In particular, the mutual information between the current status at the source node and the observed noisy measurements at the destination node is used to evaluate the information value, which gives the theoretical interpretation of the reduction in uncertainty in the current status given that we have measurements of the latent process. Moreover, the VoI expression for a hidden Markov model is obtained in this setting. Numerical results are provided to show the relationship between the VoI and the traditional age of information (AoI) metric, and the VoI of Markov and hidden Markov models are analysed for the particular case when the latent process is an Ornstein-Uhlenbeck process. While the contributions of this work are theoretical, the proposed VoI framework is general and useful in designing wireless systems that support timely, but noisy, status updates in the physical world.

We analyse the performance of a communication link assisted by an intelligent reflective surface (IRS) positioned in the far field of both the source and the destination. A direct link between the transmitting and receiving devices is assumed to exist. Perfect and imperfect phase adjustments at the IRS are considered. For the perfect phase configuration, we derive an approximate expression for the outage probability in closed form. For the imperfect phase configuration, we assume that each element of the IRS has a one-bit phase shifter (0°,180°) and an expression for the outage probability is obtained in the form of an integral. Our formulation admits an exact asymptotic (high SNR) analysis, from which we obtain the diversity orders for systems with and without phase errors. We show these are N+1 and 1/2 (N+3), respectively. Numerical results confirm the theoretical analysis and verify that the reported results are more accurate than methods based on the central limit theorem (CLT).

We present a flexible family of 3D mobility models suitable for unmanned aerial vehicles (UAV). Based on stochastic differential equations, the models offer a unique property of explicitly incorporating the mobility control mechanism and environmental perturbation, while enabling tractable steady state solutions for properties such as position and connectivity. Specifically, motivated by UAV flight data, for a symmetric mobility model with an arbitrary control mechanism, we derive the steady state distribution of the distance from the target position. We provide closed form expressions for the special cases of the Ornstein-Uhlenbeck (OU) process and on-off control (OC). We extend the model to incorporate imperfect positioning and asymmetric control. For a practically relevant scenario of partial symmetry (such as in the x-y plane), we present steady state position results for the OU control. Building on these results, we derive UAV connectivity probability results based on a SNR criterion in a Rayleigh fading environment.

Multi-hop route optimization in large-scale inhomogeneous networks is typically NP-hard, for most problem formulations, requiring the application of heuristics which, despite their relatively low processing complexity, find suboptimal solutions. Where optimal solutions can be determined by Lagrangian based constrained optimization techniques for example, the processing complexity typically scales like O(N3), N being the number of relays employed. Here, we propose an alternative approach to route optimization by considering the limit of infinite relay node density to develop a continuum model, which yields an optimized equivalent continuous relay path. The model is carefully constructed to maintain a constant connection density even though the node density scales without bound. This leads to a formulation for minimizing the end-to-end outage probability that can be solved using methods from the calculus of variations. With the continuum model, we show that the processing complexity scales linearly with the number of points that sample the continuous path, which can be lower than the number of relay nodes in a large scale network. We demonstrate the effectiveness of this new approach and its potential by considering a network subjected to point sources of interference.

In this paper, we propose an enhanced Huffman coded orthogonal frequency-division multiplexing with index modulation (EHC-OFDM-IM) scheme. The proposed scheme is capable of utilizing all legitimate subcarrier activation patterns (SAPs) and adapting the bijective mapping relation between SAPs and leaves on a given Huffman tree according to channel state information (CSI). As a result, a dynamic codebook update mechanism is obtained, which can provide more reliable transmissions. We take the average block error rate (BLER) as the performance evaluation metric and approximate it in closed form when the transmit power allocated to each subcarrier is independent of channel states. Also, we propose two CSI-based power allocation schemes with different requirements for computational complexity to further improve the error performance. Subsequently, we carry out numerical simulations to corroborate the error performance analysis and the proposed dynamic power allocation schemes. By studying the numerical results, we find that the depth of the Huffman tree has a significant impact on the error performance when the SAP-to-leaf mapping relation is optimized based on CSI. Meanwhile, through numerical results, we also discuss the trade-off between error performance and data transmission rate and investigate the impacts of imperfect CSI on the error performance of EHC-OFDM-IM.

This paper proposes a secrecy enhancement mechanism for multiuser visible light communication (VLC) systems. Thanks to the inherent advantages of visible light that it cannot penetrate opaque walls and its channel gain largely depends on the distance, VLC systems can serve multiple users at a time with high security and dense spatial reuse. Nevertheless, in the presence of multiple users, the interference caused by other users' signals should be carefully considered when analyzing the secrecy rate and data rate performance measures. By employing a continuous LED model, we formulate an optimization problem to find the optimal set of LEDs that should be used for communication such that the average secrecy rate for the secured user is maximized while satisfying data rate requirements for the other ordinary users. Numerical results are provided to verify that the relative locations of multiple users, the spatial distribution of a random eavesdropper, and the required data rates are significant factors that affect the secrecy performance in multiuser VLC systems.

In this paper, we propose a secure visible light communication (VLC) system with a novel spatial jamming scheme, which is inspired by practical observations of indoor VLC environments. In reality, probable and approximate locations of VLC users can be anticipated by analyzing the user behavior characteristic and the layout of the room. Based on the available location knowledge of a legitimate user (UE) and an eavesdropper (ED), an LED transmitter can choose to convey data or a jamming signal. We call this strategy spatial jamming. By employing a continuous LED model, the related optimization problems are formulated and analyzed based on the signal-to-interference-plus-noise ratio and the secrecy rate, respectively. The numerical results are provided to validate the prediction that the proposed spatial jamming scheme can effectively secure a VLC transmission even when the LEDs do not know the exact location of the ED.

The performance of mobile ad hoc networks in general and that of the routing algorithm, in particular, can be heavily affected by the intrinsic dynamic nature of the underlying topology. In this paper, we build a new analytical/numerical framework that characterizes nodes' mobility and the evolution of links between them. This formulation is based on a stationary Markov chain representation of link connectivity. The existence of a link between two nodes depends on their distance, which is governed by the mobility model. In our analysis, nodes move randomly according to an Ornstein-Uhlenbeck process using one tuning parameter to obtain different levels of randomness in the mobility pattern. Finally, we propose an entropy-rate-based metric that quantifies link uncertainty and evaluates its stability. Numerical results show that the proposed approach can accurately reflect the random mobility in the network and fully captures the link dynamics. It may thus be considered a valuable performance metric for the evaluation of the link stability and connectivity in these networks.

In this paper, a novel modulation scheme called set partition modulation (SPM) is proposed. In this scheme, set partitioning and ordered subsets in the set partitions are used to form codewords. We define different SPM variants and depict a practical model for using SPM with orthogonal frequency division multiplexing (OFDM). For the OFDM-SPM schemes, different constellations are used to distinguish between different subsets in a set partition. To achieve good distance properties as well as better error performance for the OFDM-SPM codewords, we define a codebook selection problem and formulate such a problem as a clique problem in graph theory. In this regard, we propose a fast and efficient codebook selection algorithm. We analyze error and achievable rate performance of the proposed schemes and provide asymptotic results for the performance. It is shown that the proposed SPM variants are general schemes, which encompass multi-mode OFDM with index modulation (MM-OFDM-IM) and dual-mode OFDM with index modulation (DM-OFDM-IM) as special cases. It is also shown that OFDM-SPM schemes are capable of exhibiting better error performance and improved achievable rate than conventional OFDM, OFDM-IM, DM-OFDM-IM, and MM-OFDM-IM.

Multihop relaying is a fundamental technology that will enable connectivity in large-scale networks such as those encounted in Internet of Things applications. However, the end-to-end transmission rate decreases dramatically as the number of hops increases when half-duplex (HD) relaying is employed. In this paper, we investigate the outage probability and symbol-error rate for both HD and full-duplex (FD) transmission schemes in multihop networks subject to interference from randomly distributed third-party devices. We model the locations of the interfering devices as a Poisson point process. We derive a closed-form expression for the outage probability and approximations for the symbol-error rate for HD and FD transmissions employing BPSK and QPSK. The symbol-error rate results are obtained by using a Markov chain model for the multihop decode-and-forward links. This model accurately accounts for the nonlinear dynamical nature of the network, whereby erroneous symbol decoding can be “corrected” by a second erroneous decoding operation later in the network. We verify the analytical results through simulations and show the HD and FD schemes can be utilized to reduce the error-rate and outage probability of the system according to different residual self-interference levels and interferer densities. The results provide clear guidelines for implementing HD and FD in multihop networks.

This paper considers physical layer security enhancement mechanisms that utilize simultaneous beamforming and jamming in visible light communication systems with a randomly located eavesdropper under the assumption that there are multiple light-emitting diode (LED) transmitters and one intended user. When an eavesdropper with an augmented front-end receiver is present, the jamming is very useful for preventing the eavesdropper from wiretapping the information since it is not possible to extract only the information component from the received signal if the jamming signal is random. Thus, in this paper, an optimization problem is formulated with a focus on the signal-to-interference-plus-noise ratio for the legitimate link, and it is solved by a heuristic method called the concave-convex procedure. Then, a ternary scheme is proposed, which is less complicated than the full (joint) scheme, and it is optimized by adopting a formulation based on an assignment problem, the solution of which is effectively obtained by the so-called tabu search procedure. In addition, the problem of maximizing the average secrecy rate is investigated by utilizing a continuous LED model, which significantly relaxes the complication that rises from calculating the expectation with respect to the location of the eavesdropper. Our analysis and simulation results show that the proposed simultaneous beamforming and jamming strategies (both joint and ternary) are good proxies for maximizing the average secrecy rate by utilizing the statistical information on the eavesdropper's random location.

Unmanned aerial vehicles (UAVs) have been undergoing fast development for providing broader signal coverage and more extensive surveillance capabilities in military and civilian applications. Due to the broadcast nature of the wireless signal and the openness of the space, UAV eavesdroppers (UEDs) pose a potential threat to ground communications. In this paper, we consider the communications of a legitimate ground link in the presence of friendly jamming and UEDs within a finite area of space. The spatial distribution of the UEDs obeying a uniform binomial point process (BPP) is used to characterize the randomness of the UEDs. The ground link is assumed to experience log-distance path loss and Rayleigh fading, while free space path loss with/without the averaged excess path loss due to the environment is used for the air-to-ground/air-to-air links. A piecewise function is proposed to approximate the line-of-sight (LoS) probability for the air-to-ground links, which provides a better approximation than using the existing sigmoid-based fitting. The analytical expression for the secure connection probability (SCP) of the legitimate ground link in the presence of non-colluding UEDs is derived. The analysis reveals some useful trends in the SCP as a function of the transmit signal to jamming power ratio, the locations of the UAV jammer, and the height of UAVs.

In this paper, we present a detailed framework to analyze the evolution of the random topology of a time-varying wireless network via the information theoretic notion of entropy rate. We consider a propagation channel varying over time with random node positions in a closed space and Rayleigh fading affecting the connections between nodes. The existence of an edge between two nodes at given locations is modeled by a Markov chain, enabling memory effects in network dynamics. We then derive a lower and an upper bound on the entropy rate of the spatiotemporal network. The entropy rate measures the shortest per-step description of the stationary stochastic process defining the state of the wireless system and depends both on the maximum Doppler shift and the path loss exponent. It characterizes the topological uncertainty of the wireless network and quantifies how quickly the underlying topology is varying with time.

Connectivity questions for mobile D2D networks are often approached by considering steady state performance metrics. This is due to the difficulty in handling a finite time horizon with random mobility. Hence, in this paper we create a framework to evaluate connectivity time in closed form over a finite time horizon for mobile devices. The basic metric is the mean proportion of time devices are connected over a finite period. The methodology is shown to deliver closed form results for a variety of deterministic and random mobility models in both fading and non-fading scenarios. This allows a comparison of mobility types and an understanding of the underlying parameters. In addition, an approach is developed which allows different mobility types to be compared on the basis of a single 'equivalent' speed and also the overall framework allows the energy requirements of certain mobility control mechanisms to be evaluated.

Random geometric graphs (RGGs) are commonly used to model networked systems that depend on the underlying spatial embedding. We concern ourselves with the probability distribution of an RGG, which is crucial for studying its random topology, properties (e.g., connectedness), or Shannon entropy as a measure of the graph's topological uncertainty (or information content). Moreover, the distribution is also relevant for determining average network performance or designing protocols. However, a major impediment in deducing the graph distribution is that it requires the joint probability distribution of the n (n -1)/2 distances between n nodes randomly distributed in a bounded domain. As no such result exists in the literature, we make progress by obtaining the joint distribution of the distances between three nodes confined in a disk in \mathbbR2. This enables the calculation of the probability distribution and entropy of a three-node graph. For arbitrary n, we derive a series of upper bounds on the graph entropy; in particular, the bound involving the entropy of a three-node graph is tighter than the existing bound which assumes distances are independent. Finally, we provide numerical results on graph connectedness and the tightness of the derived entropy bounds.

Considering reflected light in physical layer security (PLS) is very important because a small portion of reflected light enables an eavesdropper (ED) to acquire legitimate information. Moreover, it would be a practical strategy for an ED to be located at an outer area of the room, where the reflection light is strong, in order to escape the vigilance of a legitimate user. Therefore, in this paper, we investigate the impact of multipath reflections on PLS in visible light communication in the presence of randomly located eavesdroppers. We apply spatial point processes to characterize randomly distributed EDs. The generalized error in signal-to-noise ratio that occurs when reflections are ignored is defined as a function of the distance between the receiver and the wall. We use this error for quantifying the domain of interest that needs to be considered from the secrecy viewpoint. Furthermore, we investigate how the reflection affects the secrecy outage probability (SOP). It is shown that the effect of the reflection on the SOP can be removed by adjusting the light emitting diode configuration. Monte Carlo simulations and numerical results are given to verify our analysis.

The characterization of topological uncertainty in wireless networks using the formalism of graph entropy has received interest in the spatial networks community. In this paper, we develop lower bounds on the entropy of a wireless network by conditioning on potential network observables. Two approaches are considered: 1) conditioning on subgraphs, and 2) conditioning on node positions. The first approach is shown to yield a relatively tight bound on the network entropy. The second yields a loose bound, in general, but it provides insight into the dependence between node positions (modelled using a homogenous binomial point process in this work) and the network topology.

With the development of wireless communications and the intellectualization of machines, the Internet of Things (IoT) has been of interest to both industry and academia. Multihop routing and relaying are key technologies that will underpin IoT mesh networks in the future. This paper investigates optimal routing based on the trusted connectivity probability (T-CP) for multihop, underlay, device-to-device (D2D) communications with decode-and-forward relaying. Both random and fixed locations for base stations (BSs) are considered, where the former case assumes that the locations of the BSs are modeled as a Poisson point process (PPP). First, we derive two expressions for the connectivity probability (CP): 1) a tight lower bound and 2) an exact closed-form. Analysis is carried out for the cases where the channel state information (CSI) between BSs and the D2D transmitter is known (CSI-aware) and unknown (noCSI). Interference from active cellular user equipments (CUEs) is characterized by modeling CUE locations as a PPP. Moreover, motivated by results that have shown that social behavior leads to D2D devices communicating with nearby neighbors, we derive the trust probability for D2D connections by using a rank-based model. Finally, we propose a novel routing algorithm that can achieve the highest T-CP for any pair of D2D devices in a distributed manner. The derived analytical results are verified by Monte Carlo simulations. We show that the proposed routing algorithm achieves almost the same performance as that attained through an exhaustive search. When BSs are located randomly, the optimal path based on the CP is the shortest path between the D2D transmitter and receiver. However, for fixed BSs, the optimal path selection depends on the locations of the BSs, which provides a very useful insight in designing the multihop D2D system for 5G IoT.

This paper considers secrecy enhancement mechanisms in visible light communication (VLC) systems with spatially distributed passive eavesdroppers (EDs) under the assumption that there are multiple LED transmitters and one legitimate user equipment. Based on certain amplitude constraints, we propose a beamforming scheme to improve secrecy performance. Contrary to the case where null-steering is made possible by using knowledge of the ED locations, the proposed beamforming when only statistical information about ED locations is available directs the transmission along a particular eigenmode related to the intensity of the ED process and the intended channel. Then, a LED selection scheme that is less complicated than beamforming is provided to reduce the secrecy outage probability (SOP). An approximate closed-form for the SOP is derived by using secrecy rate bounds. All the analysis is numerically verified by Monte-Carlo simulations. The analysis shows that the beamformer yields superior performance to LED selection. However, LED selection is still a highly efficient alternative scheme due to the complexity associated with the use of multiple transmitters in the full beamforming approach. These performance trends and exact relations between system parameters can be used to develop a secure VLC system in the presence of randomly distributed EDs.

In this paper, we propose an adaptive orthogonal frequency-division multiplexing with index modulation (OFDM-IM) for two-hop relay networks. In contrast to the traditional OFDM-IM with a deterministic and fixed mapping scheme, in this proposed adaptive OFDM-IM, the mapping schemes between a bit stream and indices of active subcarriers for the first and second hops are adaptively selected by a certain criterion. As a result, the active subcarriers for the same bit stream in the first and second hops can be varied in order to combat slow frequency-selective fading. In this way, the system reliability can be enhanced. In addition, considering the fact that a relay device is normally a simple node, which may not always be able to perform mapping scheme selection due to limited processing capability, we also propose an alternative adaptive methodology in which the mapping scheme selection is only performed at the source and the relay will simply utilize the selected mapping scheme without changing it. The analyses of average outage probability, network capacity, and symbol error rate are given in closed form for decode-and-forward relaying networks and are substantiated by numerical results generated by Monte Carlo simulations.

In this paper, we propose a novel codebook design scheme for orthogonal frequency-division multiplexing with index modulation (OFDM-IM) to improve system performance. The optimization process can be implemented efficiently by the lexicographic ordering principle. By applying the proposed codebook design, all subcarrier activation patterns with a fixed number of active subcarriers will be explored. Furthermore, as the number of active subcarriers is fixed, the computational complexity for estimation at the receiver is reduced and the zero-active subcarrier dilemma is solved without involving complex higher layer transmission protocols. It is found that the codebook design can potentially provide a tradeoff between diversity and transmission rate. We investigate the diversity mechanism and formulate three diversity-rate optimization problems for the proposed OFDM-IM system. Based on the genetic algorithm, the method of solving these formulated optimization problems is provided and verified to be effective. Then, we analyze the average block error rate and bit error rate of the OFDM-IM systems applying the codebook design. Finally, all analyses are numerically verified by the Monte Carlo simulations. In addition, a series of comparisons are provided, by which the superiority of the codebook design is confirmed.

The performance of distributed wireless communication systems is dictated by the system boundaries and the interference regimes. In this paper, we present a novel coverage and connectivity analysis of a wireless system within confined domains. Specifically, a system where the receiver connects to the nearest transmitter is analyzed. Using tools from stochastic geometry, we derive general expressions quantifying the dependence of the system performance on the location of the receiver for general geometries, inclusive of circles and rectangles. The developed theory and expressions provide new insights on where additional nodes must be deployed in an existing network in order to maximize a desired quality of service. We further extend the analysis to networks with multiple collaborating transmitters which use maximum ratio transmission (MRT) or joint transmission such as in CoMP and other distributed antenna systems. Our results indicate that while having more collaborating transmitters can improve the performance of the system, artefacts due to the domain geometries cannot be eliminated. We corroborate our analysis through simulations.

We analyze topological entropy in wireless networks that are subject to local scattering and macroscopic shadowing effects. To this end, we model a network as a random geometric graph with probabilistic pair connections (due to channel randomness) and define uncertainty as the Shannon entropy of the underlying graph ensemble. We present new bounds on topological entropy that are functionals of the underlying composite fading distributions and use these to show that different fading models lead to very different network entropies under certain conditions, a result that has significant implications for self-organization and storage of the network state. We also study the behavior of the entropy bounds as the number of nodes n in the network grows large while the typical connection range r0varies monotonically with n. This analysis leads to two key results that quantify the rate of growth or decay of r0, as a function of the number of nodes n, that must be obeyed in order for the entropy bounds to converge to a positive limit. Although the contributions of this paper are theoretical, they have applications in systems such as ad hoc networks employing opportunistic routing and device-to-device (D2D) networks for future cellular communication.

We study amplify-and-forward (AF) relay networks operating with source and relay amplifier distortion, where the distortion dominates the noise power. The diversity order is shown to be 0 for fixed-gain (FG) and 1 for variable-gain (VG) if distortion occurs at the relay; if distortion occurs only at the source, the diversity order will be 1 for both. With εβ= N0/ηβ(N0the noise power, ηβthe distortion power at node β ϵ {S, R}, the source or relay), we demonstrate the emergence of what we call an ε-critical signal-to-noise plus distortion ratio (SNDR) threshold (a threshold that emerges when min{εβ} becomes small) for both forwarding protocols. We show that crossing this threshold in distortion limited regions will cause a phase transition (a dramatic drop) in the network's outage probability. Thus, small reductions in the required end-to-end transmission rate can have significant reductions in the network's outage probability.

In this paper, we analyze capacity and power scaling in multihop cooperative AF relay networks. An analytical framework for this task is developed by drawing a correspondence between random Fibonacci sequences and the end-to-end multihop system model. It turns out, the exponential growth rate of these interesting sequences can be employed to establish scaling laws, from which we conclude that it is possible to construct multihop cooperative AF networks that simultaneously avoid 1) exponential capacity decay and 2) exponential transmit power growth across the network. This is done by ensuring the network's Lyapunov exponent (a key observable studied in random dynamical system theory) is zero, which can be achieved by appropriately selecting the amplification factors at each of the relay nodes. Our results apply to both fixed-gain and variable-gain relaying. To conclude our work, we demonstrate the presented theory through numerical simulations.

In recent years, Bussgang's theorem has proven useful when studying and optimizing peak-power constrained OFDM-based amplify-and-forward (AF) networks. For the variable-gain (VG) scenario, Bussgang's theorem can be applied at the relay without taking into consideration the instantaneous behavior of the channel. This significantly improves the mathematical tractability of performance evaluation. For fixed-gain (FG) relaying, this is not necessarily the case, and we must also ensure that a sufficient number of significant channel taps are present in the channel response if we wish to ignore the channel's instantaneous behavior. In this paper, we determine conditions that the power-decay profile of the channel's l tap response must satisfy so that, in the limit of large l the FG Bussgang parameters become independent of the channel's instantaneous behavior. We conclude our analysis by considering some examples (exponential and power-law decay profiles). For exponential profiles we find that exact calculation of the Bussgang parameters always requires instantaneous channel knowledge, regardless of the number of channel taps present; while for power-law profiles this is not necessarily the case, provided the decay is not too steep.

In this work, we analyze the distance statistics corresponding to points in a Matern cluster (offspring points) and points that do not belong to that cluster (non-offspring points). We first derive the probability density function (PDF) of the distance between an offspring point and a non-offspring point of a Matern cluster. We then formulate the probability generating functional based on this PDF. Since many wireless networks (e.g., device-to-device (D2D) networks and cognitive radio systems) exhibit device clustering, this formalism enables us to efficiently formulate and evaluate expressions that describe the interference statistics and connection probability in clustered networks. We validate our theoretical analysis with numerical simulations, and illustrate that traditional methods of evaluating similar performance metrics (based on point process statistics instead of distance statistics) are unsuitable for use in such complex scenarios.

We consider an underlay cognitive network with secondary users that support full-duplex communication. In this context, we propose the application of antenna selection at the secondary destination node to improve the secondary user secrecy performance. Antenna selection rules for cases where exact and average knowledge of the eavesdropping channels are investigated. The secrecy outage probabilities for the secondary eavesdropping network are analyzed, and it is shown that the secrecy performance improvement due to antenna selection is due to coding gain rather than diversity gain. This is very different from classical antenna selection for data transmission, which usually leads to a higher diversity gain. Numerical simulations are included to verify the performance of the proposed scheme.

In this paper, we analyze the outage performance of two multicarrier relay selection schemes, i.e. bulk and per-subcarrier selections, for two-hop orthogonal frequency-division multiplexing (OFDM) systems. To provide a comprehensive analysis, three forwarding protocols: decode-and-forward (DF), fixed-gain (FG) amplify-and-forward (AF) and variable-gain (VG) AF relay systems are considered. We obtain closed-form approximations for the outage probability and closed-form expressions for the asymptotic outage probability in the high signal-to-noise ratio (SNR) region for all cases. Our analysis is verified by Monte Carlo simulations, and provides an analytical framework for multicarrier systems with relay selection.

We study the effect of anisotropic radiation on wireless network complexity. To this end, we model a wireless network as a random geometric graph where nodes have random antenna orientations as well as random positions, and communication is affected by Rayleigh fading. Complexity is quantified by computing the Shannon entropy of the underlying graph model. We use this formalism to develop analytic scaling results that describe how complexity can be controlled by varying key system parameters such as the transmit power and the directivity of transmissions in large-scale networks. Our results point to striking contrasts between power scaling and directivity scaling in the large connection range regime.

We present a novel data programming scheme for flash memory. In each word-line, exactly k out of n memory cells are programmed while the rest are kept in the erased state. Information is then conveyed by the index set of the k programmed cells, of which there are (kn) possible choices k (also called activation patterns). In the case of multi-level flash, additional information is conveyed by the threshold-voltage levels of the k programmed cells (similar to traditional programming). We derive the storage efficiency of the new scheme as a function of the fraction of programmed cells and determine the fraction that maximizes it. Then, we analyze the effect of this scheme on cell-to-cell interference and derive the conditions that ensure its reduction compared with the traditional programming. Following this, we analyze the performance of our new scheme using two detection methods: fixed reference detection and dynamic reference detection, and conclude that using dynamic reference detection will result in page error performance improvements that can reach orders of magnitude compared with that attainable by the fixed reference approach. We then discuss how logical pages can be constructed in the index programming similarly to traditional programming. Finally, we discuss the results and tradeoffs between storage efficiency and error resilience proposed by the scheme along with some future directions.

We analyze the secrecy outage probability in the downlink for wireless networks with spatially (Poisson) distributed eavesdroppers (EDs) under the assumption that the base station employs transmit antenna selection (TAS) to enhance secrecy performance. We compare the cases, where the receiving user equipment (UE) operates in half-duplex (HD) mode and full-duplex (FD) mode. In the latter case, the UE simultaneously receives the intended downlink message and transmits a jamming signal to strengthen secrecy. We investigate two models of (semi)passive eavesdropping: 1) EDs act independently and 2) EDs collude to intercept the transmitted message. For both of these models, we obtain expressions for the secrecy outage probability in the downlink for the HD and FD UE operation. The expressions for the HD systems have very accurate approximate or exact forms in terms of elementary and/or special functions for all path loss exponents. Those related to the FD systems have exact integral forms for general path loss exponents, while exact closed forms are given for specific exponents. A closed-form approximation is also derived for the FD case with colluding EDs. The resulting analysis shows that the reduction in the secrecy outage probability is logarithmic in the number of antennas used for TAS and identifies conditions, under which HD operation should be used instead of FD jamming at the UE. These performance trends and exact relations between system parameters can be used to develop adaptive power allocation and duplex operation methods in practice. Examples of such techniques are alluded to herein.

This paper investigates the secrecy connectivity probability for wireless networks with transmit antenna selection in the presence of randomly located eavesdroppers. Firstly, we propose an antenna selection scheme for use at the base station with a half-duplex receiver to enhance secrecy connectivity performance. Then in order to further improve the secrecy connectivity, a full-duplex (FD) receiver, which broadcasts a jamming signal while receiving the downlink message, is considered in this work. The probabilities of secrecy connectivity are given in the closed form and integral form for half-duplex and full-duplex receivers, respectively. The derived analytical results are verified by Monte Carlo simulations. The resulting analysis shows that the application of antenna selection at the transmitting base station and full-duplex communication at the receiving terminal leads to significant improvements in secrecy connectivity.

This work provides an analysis of topological uncertainty in wireless networks. Here, we model a wireless network as a random geometric graph (RGG) and quantify topological uncertainty in terms of the Shannon entropy of the underlying graph model. Direct pairwise connections between nodes are probabilistic in general, and thus our analysis covers cases where channel randomness contributes to uncertainty in the network topology. We derive a simple bound on RGG entropy. We then consider a pairwise connection model based on small-scale Rayleigh fading and study the behavior of the entropy bound as the number of nodes n in the network grows large while the typical connection range r_0 increases or decreases. We present three key results that quantify the rate of growth or decay of r_0, as a function of the number of nodes n, that must be obeyed in order for the entropy bound to converge to a positive limit. Although the contributions of this paper are theoretical, they have applications in systems such as ad hoc networks employing opportunistic routing and device-to-device (D2D) networks for future cellular communication (5G and beyond).

Efficient transmission power control is indispensable for cellular networks. It not only provides a high energy efficiency, but also maintains reliable connections. With the emergence of 5G mobile technology, the presence of device-to-device (D2D) communications within the cellular network has stimulated research on radio resource sharing. In this paper, we consider an underlay D2D network operating in a Rayleigh fading channel and propose a power allocation method that assigns transmit power levels to D2D UEs (DUEs) and cellular UEs (CUEs) such that the joint connection probability of DUEs and CUEs is maximized. The approach is formulated as a optimization problem, and we prove that the problem is log concave. Hence, the optimum powers for active UEs can be found easily using modern computational methods. Both the theoretical and simulated results show that the joint connectivity probability is improved by one to two orders of magnitude by applying the optimization procedure compared to conventional LTE open loop power allocation. This dramatic improvement comes at the cost of an increase in UE average transmit power. Thus, the proposed technique is well suited to 5G public safety and disaster relief communication modes where enhanced connectivity is the top priority.

The underlying models of sources of noise in flash memory are exploited to compute an accurate distribution of the threshold voltage of a cell after cancelling cell to cell interference (CCI). We analytically express the mean and variance of this voltage solely as a function of number of P/E cycles, retention time and data eliminating the read overhead of the adaptive estimation methods. To reduce the computational difficulty in hardware, we approximate the accurate distribution by a moment matched Gaussian mixture and we validate this approximation by comparing the soft decision decoding performance of both models. To gain more error correction advantage, we model the residual CCI as an additional Gaussian noise term.

A novel framework is presented that can be used to study the capacity and power scaling of linear multiple-input multiple-output (MIMO) d×d antenna amplify-and-forward (AF) relay networks. In particular, we model these networks as random dynamical systems (RDS) and calculate their d Lyapunov exponents. Our framework can be applied to systems with any per-hop channel fading distribution provided the expected logarithm of the channel matrices' norms are finite; in this contribution all of our results relate specifically to Rayleigh fading. Our main results are twofold: 1) the total transmit power at the nth node will follow a deterministic trajectory through the network governed by the network's maximum Lyapunov exponent, 2) the capacity of the ith eigenchannel at the nth node will follow a deterministic trajectory through the network governed by the network's ith Lyapunov exponent. Before concluding, we present some numerical examples to highlight the theory.

We study the hybrid classical-quantum version of the channel coding problem for the famous Gel'fand-Pinsker channel. In the classical setting for this channel the conditional distribution of the channel output given the channel input is a function of a random parameter called the channel state. We study this problem when a rate limited version of the channel state is available at the encoder for the classical-quantum Gel'fand-Pinsker channel. We establish the capacity region for this problem in the information-spectrum setting. The capacity region is quantified in terms of spectral-sup classical mutual information rate and spectral-inf quantum mutual information rate.

In this paper, we apply the concept of combined bulk/per-subcarrier selection to two-hop relay selection systems employing OFDM. The outage probability of the proposed strategy is analyzed in the high SNR regime when decode-and-forward, fixed-gain amplify-and-forward and variable-gain amplify-and-forward are employed at the relays. Meanwhile, a generalized situation without specifying the relaying protocol is also analyzed. We mathematically prove that the combined selection strategy is able to achieve an optimal outage probability equivalent to conventional per- subcarrier selection in the high SNR regime without using the full set of available relays for selection. Moreover, we demonstrate through numerical simulations that this performance advantage holds when channels are spatially correlated.

In this paper, we present a novel framework that can be used to study the capacity and power scaling properties of linear multiple-input multiple-output d×d antenna amplify-and-forward relay networks. In particular, we model these networks as random dynamical systems and calculate their d Lyapunov exponents. Our analysis can be applied to systems with any perhop channel fading distribution; although in this contribution, we focus on Rayleigh fading. Our main results are twofold: 1) the total transmit power at the nth node will follow a deterministic trajectory through the network governed by the network's maximum Lyapunov exponent and 2) the capacity of the ith eigenchannel at the nth node will follow a deterministic trajectory through the network governed by the network's ith Lyapunov exponent. Before concluding, we concentrate on some applications of our results. In particular, we show how the Lyapunov exponents are intimately related to the rate at which the eigenchannel capacities diverge from each other, and how this relates to the amplification strategy and the number of antennas at each relay. We also use them to determine the extra cost in power associated with each extra multiplexed data stream.

We study wireless ad hoc networks in the absence of any channel contention or transmit power control and ask how antenna directivity affects network connectivity in the interference limited regime. We answer this question by deriving closed-form expressions for the outage probability, capacity and mean node degree of the network using tools from stochastic geometry. These novel results provide valuable insights for the design of future ad hoc networks. Significantly, our results suggest that the more directional the interfering transmitters are, the less detrimental are the effects of interference to individual links. We validate our analytical results through computer simulations.

We describe a novel technique that can be used to allow two parties to exchange a secret key over an orthogonal frequency division multiplexing (OFDM) channel with perfect secrecy, provided subcarriers are subject to independent fading and a malicious attacker is passively eavesdropping. Our approach is shown to be robust against the eavesdropper's channel being correlated with that of the legitimate users, and also active attacks in which the eavesdropper injects fraudulent messages into the system. For the active attack, we show that when the eavesdropper injects fraudulent messages into the system, they will also inadvertently allow the legitimate users to calculate a lower bound on the secrecy capacity of the channel. This allows them to establish whether secrecy has been achieved. A consequence of our approach is that the degrees of freedom within the channel are halved.

Wireless networks are fundamentally limited by the intensity of the received signals and by their inherent interference. It is shown here that in finite ad hoc networks where node placement is modelled according to a Poisson point process and no carrier sensing is employed for medium access, the SINR received by nodes located at the border of the network deployment/operation region is on average greater than the rest. This is primarily due to the uneven interference landscape of such networks which is particularly kind to border nodes giving rise to all sorts of performance inhomogeneities and access unfairness. Using tools from stochastic geometry we quantify these spatial variations and provide closed form communication-theoretic results showing why the receiver's location is so important.

We study the effect of stochastic wireless channel models on the connectivity of ad hoc networks. Unlike in the deterministic geometric disk model where nodes connect if they are within a certain distance from each other, stochastic models attempt to capture small-scale fading effects due to shadowing and multipath received signals. Through analysis of local and global network observables, we present conclusive evidence suggesting that network behaviour is highly dependent upon whether a stochastic or deterministic connection model is employed. Specifically we show that the network mean degree is lower (higher) for stochastic wireless channels than for deterministic ones, if the path loss exponent is greater (lesser) than the spatial dimension. Similarly, the probability of forming isolated pairs of nodes in an otherwise dense random network is much less for stochastic wireless channels than for deterministic ones. The latter realisation explains why the upper bound of k-connectivity is tighter for stochastic wireless channels. We obtain closed form analytic results and compare to extensive numerical simulations.

In this paper, we present a rate-optimization procedure for the transmission of scalable video sequences (e.g., the scalable extension of the H.264/AVC standard), over wireless channels. In particular, we propose a method of specifying the extractable rate points in the scalable bit stream such that the expected transmission rate is increased and the probability of not transmitting any video layer is reduced. The problem is formulated as an optimization problem. Although the problem is non-linear and non-convex, we show through simulations that it is possible to converge to the global optimal solution using numerical methods provided adequate initialization points are chosen. The low complexity of the numerical methods make such approaches suitable for rapidly changing environments. It is further demonstrated through simulations that, for given channel conditions, a limit on the level of granularity of the scalable video stream exists, beyond which the increase in the expected transmission rate is minimal, but a reduction in the compression efficiency is inevitable.

In this paper, we present the end-to-end performance analysis of a dual-hop amplify-and-forward (AF) relay system. In particular, the outage performance of a system which employs maximum ratio combining (MRC) and transmit antenna selection at the relay is analyzed. We consider systems which operate over heterogeneous channels, where the channels in the first and second hops can either follow a Rayleigh or Rician distribution. Closed-form expressions are derived for the outage probability in the high SNR regime. We further demonstrate through simulations that for a specific configuration, the Rice factor of the first channel does not have a significant impact on the end-to-end outage performance. We corroborate our derivations through simulation results.

We consider the probability that a dense wireless network confined within a given convex geometry is fully connected. We exploit a recently reported theory to develop a systematic methodology for analytically characterizing the connectivity probability when the network resides within a convex right prism, a polyhedron that accurately models many geometries that can be found in practice. To maximize practicality and applicability, we adopt a general point-to-point link model based on outage probability, and present example analytical and numerical results for a network employing 2 × 2 multiple-input multiple-output (MIMO) maximum ratio combining (MRC) link level transmission confined within particular bounding geometries. Furthermore, we provide suggestions for extending the approach detailed herein to more general convex geometries.

Nodes in ad hoc networks with randomly oriented directional antenna patterns typically have fewer short links and more long links which can bridge together otherwise isolated subnetworks. This network feature is known to improve overall connectivity in 2D random networks operating at low channel path loss. To this end, we advance recently established theoretical results to obtain analytic expressions for the mean degree of 3D networks for simple but practical anisotropic gain profiles, including those of patch, dipole and end-fire array antennas. Our analysis reveals that for homogeneous systems (i.e, neglecting boundary effects) directional radiation patterns are superior to the isotropic case only when the path loss exponent is less than the spatial dimension. Moreover, we establish that ad hoc networks utilizing directional transmit and isotropic receive antennas (or vice versa) are always sub-optimally connected regardless of the environment path loss. We extend our analysis to investigate inhomogeneous systems, and study the geometrical reasons why boundary effects cause directional radiating nodes to be at a disadvantage to isotropic ones. Finally, we discuss multi-directional gain patterns consisting of many equally spaced lobes which could be used to mitigate boundary effects and improve overall network connectivity.

We present a new means of implementing distributed space-time block codes (STBC) for wireless amplify-and-forward (AF) relay networks. In the proposed method, each source antenna transmits one column of an STBC matrix derived from a generalized complex orthogonal design (GCOD). Such designs were originally intended for single hop environments. At each relay antenna, a precoding matrix and a fixed gain amplification factor are applied before the resulting signal is forwarded to the next set of nodes. The precoding operation at the relays rearranges the elements of the received vector in such a way that the equivalent STBC code observed at the destination is quasi-orthogonal. The characteristics and one structure for the precoding matrices are proposed. Initially, a dual hop system is considered for convenience. We then demonstrate how the scheme can be readily extended to multihop networks. We refer to this type of relay system as the transform-and-forward scheme. Simulation results demonstrate the performance of the technique over an existing approach.

We present a multi-mode power amplifier (PA) set with an antenna selection mechanism in a body area relaying network for healthcare applications. The PA set of the relay node is designed to work in two modes where the RF switch utilized for antenna selection is located between the highly efficient narrowband PAs and a low-efficiency wideband PA supporting two heterogeneous networks. Our study shows that, unlike in the wideband PA mode, where antenna selection is always desirable for transmission reliability, antenna selection is not always preferred in the narrowband PA mode since in this mode, the PA needs to turn on and off constantly. Consequently, extra switch delay and energy consumption occur. To balance the tradeoff between the relay node's energy efficiency and transmission reliability, both the switching probability between two modes and bounds on the probability of staying on the current antenna are analyzed. Numerical results are provided to corroborate the improved performance of the proposed architecture and the switch/stay mechanism.

Recently, there has been considerable interest to utilize the power line infrastructure for broadband communications. Power Line Communications (PLC) operate in the frequency range between 1.8MHz to 30MHz defined by the IEEE 1901 standard. Within this frequency range, a number of organizations and users occupy their own specific spectrum. As a result, spectrum notching and interference avoidance need to be applied to enable co-existence between the primary users and secondary PLC transmissions. Instead of employing a notch filter, this paper presents an effective spectrum notching technique to provide multiple deep notches in the PLC band. The performance and complexity of this notching technique is investigated.

In this paper, an orthogonal training signal relaying technique for channel estimation in a dual-hop amplify-and-forward (AF) relay network with multiple relays is proposed. In an existing technique, the cross interference occurs between the precoded training signals of the relays since their precoded noise vector terms are not orthogonal. This leads to an increased channel estimation mean squared error (MSE) at the destination. To tackle the cross interference problem without changing the channel estimator at the destination, we propose to use an additional step at each relay prior to training signal precoding. That is, converting the received training signal vector to a scalar channel estimate term via estimating the channel of the first hop at each relay. In this case, the received noise vector at each relay is converted to an scalar channel estimation error term. When multiplying the mutually orthogonal precoding vectors with the scalar values (i.e. the estimated channels at the relays), the resultant precoded training signals of the relays remain mutually orthogonal. Hence the cross interference is eliminated. The proposed technique can provide a significantly lower channel estimation MSE at the destination as the number of relays M increases. Results show that the proposed technique yields 0.5 dB, 1.5 dB and 2 dB of BER performance gains over the existing method at a bit error rate (BER) of 0.001 when M are 2, 4 and 8 respectively.

In this paper, we propose the pilot design and channel estimation schemes for uplink block-spread code division multiple access (BS-CDMA) systems. In particular, we propose the use of a common spreading code to spread the pilot signals of all users such that a high bandwidth efficiency is achieved. The expense, however, is the multi-user interference (MUI) introduced in uplink channel estimation. On that account, three pilot design schemes are proposed to eliminate the MUI. We show through simulations that, a BS-CDMA system using the proposed pilot design schemes with recursive least squares (RLS) channel tracking algorithm achieves a comparable performance to a similar system using the pilot block based channel estimation (as employed in the LTE uplink) in low mobility scenario, while significantly outperforming that using the pilot block based channel estimation in high mobility scenario. In particular, the performance of BS-CDMA using the proposed channel estimation methods remains robust at a Doppler frequency of 400Hz.

In this study the authors perform a diversity analysis for an energy detection-based non-coherent spectrum sensing scheme and benchmark it against a genie aided coherent spectrum sensing scheme, which has full knowledge of the fading channel. In both cases the sensor has access to multiple independent channel observations. Results show that both schemes achieve full diversity. However, the authors find that the coherent scheme approaches this asymptotic limit faster than the non-coherent scheme. Through analysis the authors determine the penalty of the non-coherent scheme over the coherent scheme in converging to the asymptotic limit as a function of the SNR and the number of diversity branches. With these results the authors substantiate analysis, previously made, and thus provide further insights into the trade-off between complexity and performance for spectrum sensing schemes.

A simple but effective way of precoding signals in multiantenna OFDM systems using antenna subset selection (fewer RF chains than antennas) is per-tone antenna selection, which can be applied to the chosen subset. In this paper we study the performance of coded systems using this type of precoding and compare it to bulk selection and per-tone selection when all antennas are used. The diversity is the same for all three schemes but the analysis shows that the coding gain of the combined scheme is superior to the bulk selection and not much worse than per-tone selection. These conclusions are verified by simulations and show that bulk antenna selection with subsequent per-tone selection is an effective way of achieving good performance with limited cost.

The performance of an OFDM system can be improved by performing per-subcarrier antenna selection, which facilitates the exploitation of frequency and spatial diversity in the wireless channel. In this paper, we extend the concept of per-subcarrier antenna selection to a multiuser cognitive radio environment and present a practical subcarrier and antenna selection algorithm that exploits the multiuser, frequency and spatial diversities inherent in such systems while requiring only limited channel knowledge. The problem is formulated as an integer programming (IP) problem. We demonstrate that a linear relaxation of the problem still leads to an optimal solution, thus reducing the computational complexity relative to other approaches found in the literature. Simulation results demonstrate that the proposed resource allocation problem leads to an improvement in secondary users' link qualities, compared to a single-input single-output system and, at the same time, limits the interference to the primary user.

In a cognitive radio system, the accuracy of spectrum sensing is critical for both primary and secondary systems. Both cooperative sensing and single-user multiple-antenna techniques have been proposed in the literature to enhance the accuracy of spectrum sensing. However, these techniques may require additional signaling and hardware costs, and can lead to user reliability problems or energy consumption issues. To avoid these problems, we propose a scheme that requires no extra signaling and low hardware costs, while still offering substantial diversity gains for enhancing the sensing performance. This is achieved by combining antenna selection with the spectrum sensing mechanism. We analyze the diversity order of the proposed scheme and show that no loss occurs relative to the case of single-user multiple-antenna sensing. This benefit is achieved while keeping a low implementation complexity as only a subset of RF chains are used in a given time period. Simulations show that a substantial sensing gain can be obtained compared to using other traditional multiple-antenna techniques in some practical cases.

Antenna subset selection is a cost-effective way of exploiting the spatial dimension by only using a subset of the available antennas and thereby reducing the number of RF chains. A simple but effective way of precoding signals in multiantenna OFDM systems using antenna subset selection is per-tone antenna selection, which can be applied to the chosen subset. In a TDD system, estimates of the strength of the antennas can easily be obtained from the uplink and then used for the downlink precoding. However if only a subset of the antennas is active, no information is available for the remaining antennas; this may result in poor downlink performance. In this paper we propose a simple modification to the uplink reception which allows channel sounding of inactive antennas; this will aid the per-tone selection process in the downlink. With simulations we show that this scheme outperforms other alternatives, such as switch-and-stay.

This work considers the placement of pilot symbols in orthogonal frequency division multiplexed transmissions, to minimise the mean squared error in the corresponding channel estimation. We show that further improvements in this widely investigated topic are possible, for example, in indoor wideband channels, which are subject to significantly correlated scattering processes. Noting that the naive approach incurs a prohibitive complexity, low complexity greedy solutions are developed. A measurement campaign is conducted to estimate real-world channel statistics in an indoor wideband environment. It is confirmed that practical channels are correlated, even to the extent of exhibiting rank deficiencies, and that the proposed placement algorithms result in improved channel estimation performance.

Block-spread code division multiple access (BS-CDMA) systems have been shown to achieve multiuser interference (MUI) free reception when signals of all the users arrive at the base station synchronously. In practice, imperfect timing synchronization destroys the orthogonality among users and MUI occurs. In this paper, based on the fact that unequal interference power distribution occurs in an uplink BS-CDMA system where varying degrees of interference power occur among users and across the despread message, we apply unequal error protection (UEP) to mitigate the MUI due to quasi-synchronous reception. Two UEP methods are studied. It is shown through simulations that BS-CDMA systems using these methods achieve significant performance improvement in terms of packet-error-rate (PER) compared to conventional quasi-synchronous BS-CDMA systems where the same error correcting codes are applied to the entire information packet for all users.

To facilitate coherent detection of orthogonal frequency division multiplexed transmissions, pilot symbols can be transmitted in some of the subcarriers. Their placement to minimise the mean squared error in channel estimation is considered. Such problems have been widely addressed previously for channels subject to wide sense stationary uncorrelated scattering processes. While the stationarity assumption is usually realistic, indoor wideband channels, for example, are subject to significantly correlated scattering processes. Furthermore, practical multiple antenna transmitters/receivers are bound to exhibit spatial correlations. This work considers pilot placement optimisation in a multiple antenna setting subject to arbitrary correlations in the delay and spatial domains. Noting that the naive approach incurs a prohibitive complexity, low complexity greedy solutions are developed. It is further proven that the conventional equi-spaced placement becomes optimal at high SNR even with correlations, when the correlation matrices are of full rank. A measurement campaign is conducted to estimate real-world channel statistics in an indoor wideband environment, and observe the applicability of developed algorithms. It is confirmed that practical channels are correlated to the extent of exhibiting rank deficiencies, and that the proposed placement algorithms result in improved channel estimation performance.

In this paper, we propose an antenna selection method in a wireless cognitive radio (CR) system, which we term difference selection, whereby a single transmit antenna is selected at the secondary transmitter out of M possible antennas such that the weighted difference between the channel gains of the data link and the interference link is maximized. We analyze the mutual information and the outage probability of the secondary transmission in a CR system with difference antenna selection, and propose a method of optimizing these performance metrics subject to practical constraints on the peak secondary transmit power and the average interference power as seen by the primary receiver. The optimization is performed over two parameters: the peak secondary transmit power and the difference selection weight δ∈[0,1]. Furthermore, we show that the diversity gain of a CR system employing difference selection is an impulsive function of δ, in that a value of δ=1 yields the full diversity order of M and any other value of δ gives no diversity benefit. Finally, we demonstrate through extensive simulations that, in many cases of interest, difference selection using the optimal values of these two parameters is superior to the so-called ratio selection method disclosed in the literature.

Low Density Parity Check (LDPC) codes have been adopted in a number of wired and wireless communication standards due to their improved error correcting ability and relatively simple decoder structure. However, for very high throughput systems operating in the multi-Gb/s range conventional decoding methods based on message passing are limited, due largely to the sheer volume of messages being exchanged. Thus, simpler decoding methods have been proposed such as bit flipping permitting efficient and fast hardware implementation. This paper presents two new bit flipping algorithm designed to reduce latency and power consumption. For a small loss in bit error rate performance (0.5 dB) we show how the application of an early stopping criteria uses 89% fewer iterations compared to a similar published algorithm. We also present a method for reducing power consumption by placing processing elements into a quiescent state based on a bit-local metric. Using this technique we show a potential reduction in power consumption of 76%.

This paper aims to combine adaptive subcarrier allocation and bit loading with the transmission of the H.264 SVC (Scalable Video Coding) encoded video sequences in order to increase the number of supported users in the system and provide the best quality of service (QoS) to the subscribers. We initially assume that the number of calls at the base station can be supported, and present an integer program (IP) formulation of the problem that considers the frequency selective nature of the channel, bit error rate requirement and the discrete rate requirements of the different layers of the medium grain scalable (MGS) video. It is shown how the IP can be extended to perform call admission control (CAC). Due to the complexity involved with IP, a sub-optimal scheme is then presented. Results demonstrate that our proposed scheme performs better than systems with a fixed resource allocation strategy by supporting more users and by always achieving acceptable QoS. Furthermore, the low complexity of the proposed CAC schemes makes it suitable for practical application.

In this paper we consider a non-coherent and coherent spectrum sensing scheme for OFDM signals. In addition to perfect symbol timing information we also assume full channel knowledge in the coherent case. For the non-coherent and the coherent scheme we derive analytical expressions for the detection error probability. In a comparison of these analytical and additional numerical results we find that the increased complexity of the coherent scheme does not necessarily result in a better performance. We thus provide an important insight in the complexity performance trade-off of spectrum sensing schemes.

Using mutually shift orthogonal spreading codes, block spread code division multiple access (BS-CDMA) systems have been shown to achieve multiuser interference (MUI) free reception when signals of all the users arrive at the base station synchronously. In practice, imperfect synchronization destroys the orthogonality among users and causes MUI. We present in this paper the design of spreading and despreading codes to reduce the MUI due to quasi-synchronous reception. A quasi- synchronous BS-CDMA system using the proposed spreading and despreading codes is shown to achieve a performance close to that of a synchronous system, while maintaining a low receiver complexity. The cost is reduced bandwidth efficiency in transmission, which becomes less significant as the number of users increases.

We propose a rate-lossless technique for reducing the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing systems employing antenna selection on a per-subcarrier basis. The proposed technique, which is from the family of the active constellation extension (ACE) approach to PAPR reduction, exploits the nulled subcarriers (for a given antenna) that arise through the antenna selection process to reduce the PAPR by introducing a controlled level of distortion to these subcarriers. We show that the new scheme is capable of achieving a much lower PAPR than traditional ACE methods applied to per-subcarrier antenna selection systems. Moreover, we demonstrate through simulation analyses that the distortion transmitted on the nulled subcarriers will not hinder practical system performance.

Recently, a block spreading code division multiple access (BS-CDMA) technique was presented whereby user-specific preceding along with orthogonal spreading codes are used to achieve multi-user interference (MUI) free when all users arrive at the base station simultaneously. In practice however, imperfect synchronization destroys the orthogonality among users and MUI occurs. This paper investigates the design of linear frequency domain equalizers to reduce the MUI in a quasi-synchronous BS-CDMA system. An optimal frequency domain linear minimum-mean squared error (LMMSE) equalizer is derived. Further simplification leads to a novel sub-optimal equalizer with reduced computational complexity. It is shown through simulation that the proposed equalizers effectively suppress the error floor due to quasi-synchronous reception when channel coding is applied.

In this paper, we propose a method of constructing a novel generalized space-time code from a linear dispersion (LD) "protocode" by using the block spreading (BS) technique. The resulting generalized space-time code, therefore referred to as the BS-LD code, is shown to achieve the same rate, capacity, and performance as its protocode in flat fading channels. Moreover, our BS-LD codes exhibit a higher bandwidth efficiency when overlayed onto a block transmission method such as orthogonal frequency division multiplexing (OFDM). This property suggests BS-LD codes are ideal for use in frequency selective fading channels.

Detection of OFDM transmissions with interspersed pilot symbols is considered. A hard output detection algorithm developed by Taricco et. al. for flat fading channels is extended for this frequency selective scenario. In the investigated systems with 128 subcarriers, this algorithm outperforms conventional approaches and performs close to a genie aided receiver even with the use of a single pilot symbol for the whole frame. Furthermore, a novel soft output generating algorithm is developed, which is more suitable for channel coded systems. The resultant algorithm is capable of detecting coded OFDM transmissions with fewer pilot symbols than that required for noiseless channel identification.

Layered decoding of Low Density Parity Check (LDPC) codes has been shown to give faster convergence and use less storage than the conventional Two Phase Message Passing (TPMP) algorithm in decoding such codes. To achieve higher throughput, multiple rows of the parity check matrix may be decoded in parallel, as in the Parallel-Turbo Decoding Message Passing (P-TDMP) algorithm. However, contention for globally shared memory permits only a subset of rows to be decoded in parallel thus limiting overall throughput. This paper uses a near optimal scheduling algorithm, based on graph colouring, to overcome memory contention, allowing processing of multiple rows without code modification, resulting in significant throughput gains over the standard P-TDMP algorithm. For the LDPC codes studied, throughput gains compared to the P-TDMP algorithm, of between ten and fifteen are shown to be possible.

In this paper, we present a new tone reservation (TR) scheme that facilitates peak-to-average power ratio (PAPR) reduction in orthogonal frequency-division multiplexing systems employing antenna selection on a per-subcarrier basis. In contrast to conventional TR schemes, the proposed technique does not lead to a reduction in the data rate, although it does introduce a controllable level of interference into the transmission, which can affect the throughput. We show that this drawback is manageable by analyzing the signal-to-interference-plus-noise ratio and the bit-error rate at high signal-to-noise ratio, and we conclude that it is best to allocate a large number of tones for PAPR reduction using only a small amount of power per tone. Finally, we illustrate through simulations that the proposed TR scheme is capable of facilitating PAPR reduction in practical systems.

A novel method of utilizing the channel state information at the transmitter (CSIT) for orthogonal frequency division multiplexing (OFDM) systems with multiple transmit antennas is presented in this paper. Using the conventional time reversal (TR) technique along with a specific OFDM symbol structure, the method facilitates the application of full-rate orthogonal space-time block coding (OSTBC) to systems with more than two transmit antennas for complex signalling. Compared to the conventional eigen- beamforming method, which maximizes the received signal- to-noise ratio (SNR) when CSIT is available, it is shown that the proposed system has a much reduced computational complexity. However, this complexity reduction comes at the expense of a loss of diversity in an uncoded system, which we show through an analysis of bit error rate (BER). Despite this drawback, we show through simulations that the proposed method achieves BER performance almost as well as the eigenbeamforming method when channel coding is employed, which is the case in most practical systems.

A novel methodology of transmit beamforming for systems subjected to equivalent isotropic radiated power restrictions is presented in this paper. Based on the properties of the radiation due to the optimal beamforming method compared with that due to the eigen-beamforming, beamforming vectors are designed by perturbing the scaled eigen-beamforming vector such that the peak-to-average power ratio of the spatial radiation is reduced. Two algorithms incorporating this general methodology are presented. With a computational complexity less than the optimal method, both are shown to outperform conventional sub-optimal beamforming methods. For example, in an investigated system with four transmit and one receive antennas, performance is improved by more than 1 dB at a packet-error-rate of 10−3.

A novel block-spread code-division multiple access (BS-CDMA) framework is presented whereby user-specific, channel-independent precoding is employed along with special spreading codes to ensure multi-user interference free reception with maximum user load. This framework is presented in a general form, from which other BS-CDMA techniques can be derived. Finally, it is shown that specific precoder and spreading code designs facilitate low-complexity frequency-domain equalization at the receiver.

In an OFDM system, antenna selection can be performed on a per-subcarrier basis, which can exploit the frequency selectivity of the channel. However, this may cause power imbalance across the antennas, which may lead to problems with the power amplifiers (PA). To avoid this problem, we devise a scheme that allocates the same number of subcarriers to all antennas, while still offering substantial diversity gains. This is achieved by using integer optimization and we show that this is solvable by linear relaxation, which results in a reduced complexity. The constrained antenna selection is analyzed and it is shown that choosing the cost function as BER offers better diversity gains than using SNR. Simulations with a nonlinear PA show that the integer optimization scheme performs better than unconstrained antenna selection and a previously published ad hoc method.

Certain communications transmitters are restricted by their equivalent isotropic radiated power (EIRP) rather than the total transmitted power. Important examples are ultra-wideband systems. Use of channel knowledge at transmission for such systems, when there are multiple transmit antennas, is complicated due to the need to consider the spatial directivities of the radiation. Thus it is computationally prohibitive to implement optimal EIRP constrained beamforming schemes. This work presents a novel low complexity transmit beamforming method for such systems. Motivated by the radiation due to optimal schemes, the algorithm is based on perturbing the dominant channel eigenvector such that the peak-to-average power ratio of the spatial radiation is reduced. Simulation results confirm the improved system performance compared to existing sub-optimal beamforming methods.

This paper presents an improved active interference cancellation (AIC) algorithm for ultra wideband (UWB) systems with antenna selection on a per subcarrier basis. The improved algorithm overcomes the drawbacks of the conventional AIC algorithms by jointly minimizing the notch depth over multiple transmitter antennas, while ensuring that the power transmitted on the AIC tones adheres to the spectral mask imposed by the Federal Communications Committee (FCC). The improved algorithm is shown, through simulation and hardware demonstration, to provide sufficiently deep spectral notches for multiple transmitter antennas and to effectively suppress the excess power of the AIC tones generated by the conventional AIC algorithms.

Antenna selection can be an efficient way of exploiting spatial diversity while offering low feedback rates and simple receivers. In an OFDM system, antenna selection can be performed on a per-subcarrier basis, which can exploit the frequency-selectivity of the channel. However, this will cause a power imbalance across the antennas, which may lead to problems with the power amplifiers. An increased dynamic range may require power back-off, which results in a performance loss. To avoid this problem, we devise an optimum scheme that allocates the same number of subcarriers to all antennas, while still offering substantial diversity gains. This is achieved by using integer optimization. We show that this is solvable by linear relaxation, which results in a reduced complexity. Simulation results illustrate that the proposed scheme performs better than a previously published ad hoc method and only slightly worse than the impractical conventional per-subcarrier antenna selection where no subcarrier allocation constraints are imposed.

In this article, a novel method of performing interference avoidance in next-generation single-carrier ultrawideband block transmission systems is presented. This method relies on the application of a time-domain window to each data block prior to transmission, where the window is optimized such that the required notch depth is achieved for each transmission. Furthermore, a modification of this technique is also detailed, whereby the complexity can be reduced from O(N3) to O(N2) where N is the number of symbols per block. It is shown that the proposed techniques overcome many of the drawbacks of current methods such as transmit power control, frequency notching, and active interference cancellation.

Ultra wideband transceivers promise multi-gigabit per second performance at power consumptions commensurate with portable devices. Future products are likely to adopt multiple antennas to maximize performance. Severe FCC EIRP restrictions impose an interesting system design constraint. In this paper, capacity optimal multiple antenna transmission schemes are investigated for EIRP restricted systems under the assumption that the channel is known at the transmitter. It is shown that per subcarrier antenna power allocation, which reduces to antenna selection at low SNR or when using one receive antenna, is optimal for some transmitter configurations. The improvements in capacity are quantified for representative channels.

Block-spread code-division multiple access (BS- CDMA) is a bandwidth efficient method by which multiple users can utilize a transmission medium simultaneously. One special property of BS-CDMA transmissions is that they facilitate the use of low-complexity frequency-domain equalization (FDE) at the receiver. Recently, it was shown that this property can only be preserved for multi-user interference (MUI) free reception when the number of simultaneously transmitting users does not exceed [M/2], where M is the length of the block spreading code. In this paper, a novel BS-CDMA technique is presented whereby user-specific preceding is employed along with special spreading codes to ensure MUI-free reception forMsimultaneous users, while preserving the properties of the transmission that facilitate FDE at the receiver.

Spectral shaping for narrowband interference avoidance is an important part of cognitive radio, and is essential in ultra wideband (UWB) communication systems. In this paper, a novel interference avoidance algorithm is proposed for use in next-generation single-carrier UWB block transmission systems. The proposed technique provides a means of implementing interference avoidance in a dynamic manner with the added expense of an increase in transmitter complexity. When constant modulus constellations are employed, the receiver does not need any additional information about the transmitted signal in order to recover the transmitted message. Even with this "blind" detection strategy, the proposed method performs within 1-2 dB of a system where interference avoidance is not required or implemented.

As the potential data-rates of wireless local area networks (WLANs) continue to rise, the ability of such systems to support a rich set of applications increases. The centralized control functions in the IEEE 802.11 family of standards have been developed to enable both data-oriented (browsing, email, etc.) traffic and quality of service (QoS) sensitive traffic to coexist. Balancing the demands of the two types of traffic has, to date, been achieved by algorithms based on experimental, heuristic data. In this paper we present a non-linear optimization theory-based approach for deriving optimum configurations with the IEEE 802.11/e centralized control functions in mind. The optimization algorithm itself (the "barrier method") is well-known; the challenge in problems such as this is in the formation of the utility function and its constraints, so these are explored in detail. Finally, we show the advantages of this approach over discrete look-up based approaches

This work investigates the performance of a new reduced-complexity trellis decoding algorithm (termed the EP-MBCJR algorithm) when employed for the task of equalization in an indoor multiple input multiple output wireless environment. The algorithm is a generic approximate reduced-state variation of the BCJR algorithm modeled after the conventional M-BCJR algorithm. Instead of choosing the active states based on the filtered distribution of states in the forward recursion, the EP-MBCJR algorithm selects the active states based on "beliefs" on the states. This can be seen as an application of the concept of "expectation propagation" and leads to identical forward and backward recursions which can be iterated to improve system performance. A receiver architecture comprising of channel estimation, sampling phase selection and turbo equalization is proposed and its performance evaluated through computer simulations. For the simulation of channels closely resembling the physical environment, we have used channels generated in accordance with the IEEE 802.11n TGn channel models

Single-carrier (SC) wireless communication systems generally require knowledge of the channel and the variance of the additive noise process to equalize a received message. Obtaining this information can be straightforward in stationary environments; however, these parameters constantly change in mobile environments. In this paper, we propose novel algorithms for estimating and tracking the channel and noise variance in SC systems by exploiting a unique word (UW) extension. These UW-based algorithms benefit from low complexity and lend themselves to SC systems employing frequency-domain equalization at the receiver

In MIMO OFDM systems, the quality of channel estimation becomes important, especially for a large number of antennas. On the other hand, it is desirable to minimise the overhead, making the design of training sequences a crucial task. Although this problem has been solved efficiently for OFDM systems using all subcarriers, it is still an open question for systems with nulled subcarriers (such as IEEE802.11a and IEEE802.11n), where some of the subcarriers are left unmodulated in order to fit specified spectrum masks. In this paper we present a numerical method for designing MIMO OFDM training sequences for arbitrary systems using nulled subcarriers. It is shown that substantial gains can be had over simple training sequences, such as only transmitting on non-overlapping subcarriers. The performance of these new training sequences are measured in both mean-squared error and bit-error rate

Channel estimation and tracking pose real problems in wideband single-carrier wireless communication systems employing multiple transmit and receive antennas. An alternative to estimating the channel is to adaptively equalize the received symbols. In this paper, we present an adaptive equalization algorithm for implementation in multiple-input multiple-output (MIMO) single-carrier (SC) systems with frequency-domain equalization (FDE). Furthermore, we outline a novel method of reducing the overhead required to train the adaptive equalizer. Other computationally efficient adaptive MIMO SC-FDE algorithms can only be applied to space-time block-coded (STBC) architectures. The algorithm detailed in this paper can be implemented in STBC systems as well as in broadband spatial multiplexing systems, making it suitable for use in high data rate MIMO applications.

We investigate a new class of training sequences that are optimal for least squares (LS) channel estimation in systems employing transmit diversity and single-carrier (SC) modulation with a cyclic prefix (CP) extension. The sequences have a constant envelope in the time domain and are orthogonal in the frequency domain. Transmission of these sequences facilitates optimal (in the LS sense) estimation of the channel impulse response at the receiver while precluding the peak-to-average power ratio problem that is inherent in other CP-based architectures such as orthogonal frequency division multiplexing.

Recent developments in orthogonal frequency division multiplexing (OFDM) and single-carrier frequency-domain equalization (SCFDE) have sparked debate about the superiority of one method over the other. In this paper, we further this debate by comparing the theoretical performance of OFDM and SCFDE when each is implemented in one of two different multiple-input multiple-output (MIMO) architectures: spatial multiplexing and space-time block codes. This study focuses on the use of MIMO-OFDM and MIMO-SCFDE in wireless local area network (WLAN) applications. Performance is given in terms of the packet error rate (PER) and the throughput of the systems.