Search

In this article, we investigate the performance of a reconfigurable intelligent surface (RIS) assisted full-duplex (FD) communication network, where each user is facilitated by a specific RIS in the network. The correlated Nakagami-$m$ fading channel is first considered in a RIS system, which is a general channel model that can capture the spatial correlation effect inherent in the RIS-assisted communication system. Using the two-dimensional Laplace transform and its inverse, the closed form expressions of the mean and variance of the signal power distribution are obtained. Then, the outage probability and average achievable rates of the uplink and downlink users are derived in closed form. Furthermore, the impact of the residual self-interference (SI) on FD communication performance is discussed. It is demonstrated that FD communication outperforms HD communication when the residual SI is below a threshold, and the threshold is derived in closed form. Simulation results are presented to confirm the accuracy of the theoretical analysis and show the negative impact of channel correlation on the system performance. Moreover, it is illustrated that the outage probability and the average achievable rate of the uplink user will converge to a constant when the residual SI is linearly dependent on the transmit power.

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.

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 consider control mechanisms for mobile devices in a stochastic environment. In particular, we consider a device in $n$-dimensional space subject to Brownian perturbations where a control mechanism moves the device towards its target location at a speed which is a function of its displacement. For this scenario, we construct stochastic differential equations for the mobility process and solve for the steady state probability density function of displacement. From this we are able to give general solutions to key metrics such as displacement outage (the long term probability of exceeding a given distance from the target), connectivity probability (derived from the SNR distribution in a Rayleigh channel with pathloss), the mean time at which the device first exceeds a given distance from the target, and the mean kinetic energy required by the control mechanism. We evaluate these metrics for important special cases of the control mechanism and also study the optimization problem of minimizing kinetic energy over the parameters of the control function.

This paper studies a novel electrophoretic molecular communication (EMC) framework utilizing a piecewise constant electric field. EMC is a particular type of molecular communication that exploits electric fields to induce the movement of charged particles to enhance communication performance. Our previous work proposed an EMC framework utilizing a time-varying electric field that exponentially changes; however, the field with such a complicated shape might be challenging to be implemented in practice. Thus, this paper proposes a new EMC approach exploiting a piecewise constant electric field that can be readily implemented via, e.g., an on/off switch method. We formulate two optimization problems to design the electric field based on different objectives: minimizing a mean squared error and minimizing a bit interval. The solutions of each, such as optimal on-off timings and corresponding strengths of the constant electric fields, are obtained through the Lagrange multiplier approach and the geometric programming, respectively. The Monte Carlo simulation results verify that the proposed piecewise constant electric field significantly reduces the bit error rate relative to the constant field benchmark while performing less well, but not significantly, than the exponential field benchmark.

In this letter, we investigate the performance of a communication link assisted by a reconfigurable intelligent surface (RIS) over line-of-sight (LOS) channels. The phase configuration of the RIS is imperfect and the phase error for each reflective element is modeled by a Von Mises distribution. First, we derive novel closed-form approximations for the lower tail distribution of the magnitude of the equivalent channel coefficient. Then, we use the obtained expressions to evaluate the outage probability and diversity order of the proposed system. Approximation errors of the proposed method are analyzed in detail. Simulation results validate the theoretical analysis is accurate at a high signal-to-noise ratio (SNR) regime.

Assume the communication between a source and a destination is supported by a large reflecting surface (LRS), which consists of an array of reflector elements with adjustable reflection phases. By knowing the phase shifts induced by the composite propagation channels through the LRS, the phases of the reflectors can be configured such that the signals combine coherently at the destination, which improves the communication performance. However, perfect phase estimation or high-precision configuration of the reflection phases is unfeasible. We study the transmission through an LRS with phase errors that have a generic distribution. We show that the LRS-based composite channel is equivalent to a direct channel with Nakagami scalar fading. This equivalent representation allows for theoretical analysis of the performance and can help the system designer study the interplay between performance, the distribution of phase errors, and the number of reflectors. Numerical evaluation of the error probability for a limited number of reflectors confirms the theoretical prediction and shows that the performance is remarkably robust against the phase errors.

In this letter, we propose a novel orthogonal frequency division multiplexing with index modulation (OFDM-IM) scheme, which we call ${Q}$ -ary multi-mode OFDM-IM ( ${Q}$ -MM-OFDM-IM). In the proposed scheme, ${Q}$ disjoint ${M}$ -ary constellations are used repeatedly on each subcarrier, and a maximum-distance separable code is applied to the indices of these constellations to achieve the highest number of index symbols. A low-complexity subcarrier-wise detection is shown possible for the proposed scheme. Spectral efficiency (SE) and the error rate performance of the proposed scheme are further analyzed. It is shown that the proposed scheme exhibits a very flexible structure that is capable of encompassing conventional OFDM as a special case. It is also shown that the proposed scheme is capable of considerably outperforming the other OFDM-IM schemes and conventional OFDM in terms of error and SE performance while preserving a low-complexity structure.

Recently, the mission-critical push-to-talk (MCPTT) system has emerged as the new broadband technology for public safety networks. In this paper, we propose a route selection method based on the connectivity, delay, and trust in the MCPTT system to offer the best connectivity-delay-trust performance. To begin with, the connection probability between a pair of user equipment (UE) has been analyzed with the interference from other MCPTT groups. Then, the timeliness probability is studied to capture the level of confidence for the delay requirement. Moreover, the trust probability is calculated by a beta reputation system to prevent potential attacks from malicious nodes and ensure secure interactions among the forwarding UE. By combining three probabilistic results, we investigate the optimal path route selection method based on the Dijkstra's algorithm to find the path, which can meet the requirement of the MCPTT system. The simulation results validate our models and theoretical analysis. The results provide a useful insight into designing the MCPTT system for 5G public safety and disaster relief networks.

In this letter, we propose a two-hop orthogonal frequency-division multiplexing with index modulation (OFDM-IM) system, which is assisted by multiple relays and employs multi-carrier relay selection to enhance the system reliability. In particular, two commonly used multi-carrier relay selection schemes are considered, i.e., bulk and per-subcarrier relay selections, and the decode-and-forward relaying is adopted as the forwarding protocol for the proposed system. The analysis of average outage probability of the proposed system is given in closed form and substantiated by numerical results generated by Monte Carlo simulations. By the analytical and numerical results provided, we can observe that the full diversity (equal to the number of relays) can be achieved by applying both bulk and per-subcarrier relay selections in two-hop OFDM-IM systems.

We show that the von Neumann entropy (from herein referred to as the von Neumann index) of a graph’s trace normalized combinatorial Laplacian provides structural information about the level of centralization across a graph. This is done by considering the Theil index, which is an established statistical measure used to determine levels of inequality across a system of ‘agents’, for example, income levels across a population. Here, we establish a Theil index for graphs, which provides us with a macroscopic measure of graph centralization. Concretely, we show that the von Neumann index can be used to bound the graph’s Theil index, and thus we provide a direct characterization of graph centralization via the von Neumann index. Because of the algebraic similarities between the bound and the Theil index, we call the bound the von Neumann Theil index. We elucidate our ideas by providing examples and a discussion of different $n=7$vertex graphs. We also discuss how the von Neumann Theil index provides a more comprehensive measure of centralization when compared to traditional centralization measures, and when compared to the graph’s classical Theil index. This is because it more accurately accounts for macro-structural changes that occur from micro-structural changes in the graph (e.g. the removal of a vertex). Finally, we provide future direction, showing that the von Neumann Theil index can be generalized by considering the Rényi entropy. We then show that this generalization can be used to bound the negative logarithm of the graph’s Jain fairness index.

This letter investigates the secrecy performance in visible light communication (VLC) in the presence of randomly located colluding eavesdroppers (EDs). Colluding EDs can combine their observations and degrade the secrecy performance of the VLC systems. Utilizing the numerical inversion of a characteristic function, the probability distribution of the combined signal-to-noise ratio of colluding EDs is analyzed. The closed-form expression of the secrecy outage probability is derived and verified by Monte Carlo simulations.

Physical layer secrecy is highly costly in terms of achievable data rates if perfect secrecy is considered. However, in many practical systems this level of secrecy is not required. In this letter, we introduce a secrecy system based on network coding and physical layer secrecy which is throughput efficient while maintaining a practical level of secrecy. In this system, a set of linear combinations of the original messages are protected with a physical-layer secrecy scheme and another set of linear combinations are freely transmitted over the wireless broadcast channel. This will allow the designer to tune the system for a desired level of secrecy and throughput. We discuss three variants of this coding scheme. The first two use random linear network codes and hence, highly efficient in terms of throughput. The third variant is based on instantly decodable network codes and designed for delay sensitive applications.

This letter studies the meta distribution of the secrecy rate for a legitimate link in the presence of eavesdroppers (EDs) with locations modeled as a Poisson point process. Both colluding and non-colluding EDs are considered. The meta distribution of the secrecy rate can provide the fraction of the realizations of EDs fulfilling a target secrecy rate. It can either be formulated using the Gil-Pelaez theorem with the imaginary moments of the conditional secrecy success probability (CSSP) given the realization of EDs or approximated by the beta distribution with the first two moments only. Hence, we first derive the ${b}$ th moment of the CSSP for the colluding scenario. Then, we formulate the exact first moment and the approximated second moment of the CSSP for the non-colluding scenario using the Fortuin–Kasteleyn–Ginibre inequality. Finally, simulations are used to validate the analytic results.

In this letter, we study the joint impact of user density, blockage density, and deployment area on the temporal correlation of interference for static users and users with uncorrelated mobility. Even if the user locations are uncorrelated over time, the interference level can still be correlated when the deployment area is bounded and/or there is blockage. We also show that at a high blockage density, the temporal correlation coefficients increase with the user-to-blockage density ratio.

This letter analyzes the resource allocation problem for full-duplex relay-assisted device-to-device (D2D) multicarrier systems, where multiple D2D user groups (UGs) coexist in an underlaying manner. We formulate the optimization problem, which takes the maximization of the system throughput as an objective. Two resources, i.e., subcarrier and transmit power are considered to be appropriately allocated to UGs in order to meet the objective. The formulated problem can be independently divided into a quasi-concave problem and a mixed binary integer programming (MBIP) problem. The MBIP problem is NP-hard. Therefore, to solve this problem efficiently by standard optimization techniques, we propose an alternative algorithm, which is the linear relaxation of the MBIP problem. Then, we mathematically prove and numerically verify the equivalence of the MBIP problem and its linear relaxation. By this way, the resource allocation for UGs can be carried out by a small amount of computational overhead.

This letter investigates the secrecy outage probability in the downlink with ordered user equipment (UE) based on two ordering metrics. UEs and independently acting eavesdroppers (EDs) are positioned randomly according to a Poisson point process. We consider a transmit antenna selection (TAS) scheme at the base station (BS) to enhance secrecy performance and propose two metrics to order the UEs: one based on long-term average channel gain information from the BS to the UEs, and the other based on instantaneous channel gains. We derive closed form expressions for the secrecy outage probability subject to each of these ordering policies and verify our calculations through Monte Carlo simulations. Our results show that while TAS yields a performance improvement relative to single-antenna systems, the secrecy outage probability for TAS systems actually increases with the path loss exponent. Furthermore, we show that the importance of the specific user ordering policy that is adopted in these systems is reduced for high path loss environments or situations where large numbers of antennas are employed.

In this paper, we study the feasibility of receiver diversity for application to downlink cellular networks, where low-energy devices are equipped with information decoding and energy harvesting receivers for simultaneous wireless information and power transfer. We compare several options that are based on selection combining and maximum ratio combining, which provide different implementation complexities. By capitalizing on the Frechet inequality, we shed light on the advantages and limitations of each scheme as a function of the transmission rate and harvested power that need to be fulfilled at the low-energy devices. Our analysis shows that no scheme outperforms the others for every system setup. It suggests, on the other hand, that the low-energy devices need to operate in an adaptive fashion, by choosing the receiver diversity scheme as a function of the imposed requirements. With the aid of stochastic geometry, we introduce mathematical frameworks for system-level analysis. We show that they constitute an important tool for system-level optimization and, in particular, for identifying the diversity scheme that optimizes wireless information and power transmission as a function of a sensible set of parameters. Monte Carlo simulations are used to validate our findings and to illustrate the trade-off that emerge in cellular networks with simultaneous wireless information and power transfer.

We present scaling laws that dictate both local and global connectivity properties of bounded wireless networks. These laws are defined with respect to the key system parameters of per-node transmit power and the number of antennas exploited for diversity coding and/or beamforming at each node. We demonstrate that the local probability of connectivity scales like $\mathcal{O}(z^{\mathcal{C}})$ in these parameters, where $\mathcal{C}$ is the ratio of the dimension of the network domain to the path loss exponent, thus enabling efficient boundary effect mitigation and network topology control.

A novel Markovian network evolution model is introduced and analysed by means of information theory. It will be proved that the model, called network evolution chain, is a stationary and ergodic stochastic process. Therefore, the asymptotic equipartition property can be applied to it. The model’s entropy rate and typical sequences are also explored. Extracting particular information from the network and methods to simulate network evolution in the continuous time domain are discussed. Additionally, the Erdős–Rényi network evolution chain is introduced as a subset of our model with the additional property of its stationary distribution matching the Erdős–Rényi random graph model. The stationary distributions of nodes and graphs are calculated for this subset alongside its entropy rate. The simulation results at the end of the article back up the proved theorems and calculated values.

Spectrum handoff is a promising spectrum management approach that enables the secondary user to continue its transmission by switching to a sensed-as-idle channel when the current channel is re-occupied by the primary user. Periodic sensing is commonly employed to facilitate spectrum handoff by improving sensing accuracy so that the secondary user has a better opportunity to avoid transmission collision via switching to a truly idle channel. However, byproducts of spectrum handoff, such as extra energy cost on channel switch, switch delay, and collisions due to excessive switch, have been largely underestimated. These by-products which have significant impacts on the overall performance lead to the questions: Should we switch the channel? How often should we switch? In this article we first review several different periodic sensing and handoff mechanisms. Then we identify the trade-off between the secondary user's energy efficiency and transmission reliability. The proposed switch-stay model is elaborated and studied to balance the aforementioned trade-off in light of sensing accuracy, the probability of collision, throughput and delay constraints. Upper and lower bounds of the stay probability on the current channel are illustrated from these constraints. In addition, we discuss the implementation of an antenna-selection sensing mechanism in order to relax these bounds for a better energy-efficient spectrum management solution. Performance evaluation and some open issues are also discussed in this article.

In this paper, we present a novel bit flipping algorithm for high-throughput decoding of LDPC codes. The algorithm exploits the turbo principle to reduce the average number of iterations and employs a bit-local thresholding operation to remove the need for a block-wise minimum operation — which is common to many conventional bit flipping decoders — that hinders decoder throughput. Through simulations the proposed decoder is shown to achieve comparable bit-error rate performance to state-of-the-art techniques while requiring approximately half the number of iterations on average thus facilitating high-throughput decoding.

This article presents the latest progress on green healthcare research in heterogeneous networks (HetNet), where devices are capable of switching between multiple radio access technologies (RAT) and each RAT operates on a different frequency channel. After outlining the design features and challenges of a medical service paradigm for green cognitive medical body area networks (MBAN), measurements are made to investigate the turn-on characteristics of a power amplifier (PA) in terms of excess energy consumption and turn-on delay. We then present a multi-mode PA architecture for an MBAN relay system. An energy-efficient PA switch/stay mechanism is also presented. This allows the proposed PA architecture to operate given a transmission outage probability and transmission delay constraint. Antenna selection between two heterogeneous RATs is exploited to improve the transmission reliability. Both measurement and numerical results are provided to corroborate the performance of the proposed architecture and its switch/stay mechanism.

Multiple-input multiple-output (MIMO) systems have shown a huge potential for increased spectral efficiency and throughput. With an increasing number of transmitting antennas comes the burden of providing training for channel estimation for coherent detection. In some special cases optimal, in the sense of mean-squared error (MSE), training sequences have been designed. However, in many practical systems it is not feasible to analytically find optimal solutions and numerical techniques must be used. In this paper, two systems (unique word (UW) single carrier and OFDM with nulled subcarriers) are considered and a method of designing near-optimal training sequences using nonlinear optimization techniques is proposed. In particular, interior-point (IP) algorithms such as the barrier method are discussed. Although the two systems seem unrelated, the cost function, which is the MSE of the channel estimate, is shown to be effectively the same for each scenario. Also, additional constraints, such as peak-to-average power ratio (PAPR), are considered and shown to be easily included in the optimization process. Numerical examples illustrate the effectiveness of the designed training sequences, both in terms of MSE and bit-error rate (BER).