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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 sub-optimal solutions. Where optimal solutions can be determined by Lagrangian based constrained optimization techniques for example, the processing complexity typically scales like $O(N^{3})$ , $N$ 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, we consider a Poisson clustered out-of-band device-to-device (D2D) network operating in Rayleigh fading channels and propose two optimization schemes based on the joint coverage probability to allocate the transmit power to D2D user equipment (DUE) in both the target cluster and the whole network. The joint coverage probability accounts for the spatial correlation of the interference among the DUE. With a differing amount of location information being available among the DUE in centralized and localized communication solutions, the joint coverage probability is formulated based on the coherent, non-coherent, and single-cluster approximated pairwise coverage probabilities. By maximizing the joint coverage probability formulated in this way, the robustness of the network can be enhanced. Meanwhile, to fulfill the green aspect of future 5G communications, the battery life of the DUE will be prolonged by minimizing the power consumption for a given joint coverage probability requirement. The formulations of the two optimization problems mentioned above are not convex but are transformed to convex by using geometric programming. The simulation results show that, compared with the conventional LTE open-loop and fixed power schemes, the joint coverage probability and power consumption are, respectively, optimized by applying the proposed schemes. [ABSTRACT FROM AUTHOR]

In this paper, we propose a full-duplex orthogonal frequency-division multiplexing (OFDM) device-to-device (D2D) system in two-hop networks, where multiple full-duplex decode-and-forward relays assist the transmission from D2D user equipment (DUE) transmitter to DUE receiver. By such a transmission mechanism, the signal transmitted by the DUE transmitter does not need to go through a base station. Meanwhile, due to the adoption of underlay D2D communication protocol, power control mechanisms are thereby necessary to be applied to mitigate the interference to conventional cellular communications. Based on these considerations, we analyze the outage performance of the proposed system, and derive the exact expressions of outage probabilities when bulk and per-subcarrier relay selection criteria are applied. Furthermore, closed-form expressions of outage probabilities are also obtained for special cases when the instantaneous channel state information between BS and cellular user equipments is not accessible, so that a static power control mechanism is applied. Subsequently, we also investigate the outage performance optimization problem by coordinating transmit power among DUE transmitter and relays, and provide a suboptimal solution, which is capable of improving the outage performance. All analyses are substantiated by numerical results provided by Monte Carlo simulations. The analytical and numerical results demonstrated in this paper can provide an insight into the full-duplex relay-assisted OFDM D2D systems, and serve as a guideline for its implementation in next generation networks. [ABSTRACT FROM AUTHOR]

We introduce a tractable approach for studying the feasibility of multiple-antenna cellular networks, where low-energy devices decode information data and harvest power simultaneously. Tools from stochastic geometry are used to quantify the information rate versus harvested power tradeoff. This letter unveils that large-scale antenna arrays and ultra-dense deployments of base stations are both necessary to harvest, with high reliability, an amount of power of the order of a milliwatt. [ABSTRACT FROM PUBLISHER]

We derive closed-form outage probability expressions for fixed-gain (FG) and variable-gain (VG) two-way amplify-and-forward (AF) relay networks subject to a nonlinear transmission at the relay. We then derive an explicit expression for the relay gain that optimizes the network's performance. Finally, we show that, if the source nodes have no access to the distortion characteristics of the relay's amplifier, which inhibits self-interference removal, the network's performance will change negligibly. [ABSTRACT FROM AUTHOR]

We develop an approximation for the outage probability of a parallel channel where the subchannel statistics satisfy mild conditions. The main result is in the form of a functional of the density function that describes the statistics of the subchannel powers. The error of the approximation is quantified to be O(\gamma^-n(q+1)-2), where $\gamma$ is the end-to-end SNR of a given subchannel, $n$ is the number of subchannels, and $q$ represents the inherent subchannel diversity. We illustrate the versatility and accuracy of the approximation by studying different statistical subchannel models, which reflect practical wireless communication systems, including line-of-sight links (Rician fading), transmissions affected by interference, and relay systems subject to amplifier distortion. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of efficiently allocating wireless resources to support multiple scalable video sequences over a downlink cognitive radio network is addressed. We consider the coarse grain scalable (CGS) and medium grain scalable (MGS) extension of the H.264 standard as the encoding method and propose to perform a per-subcarrier transmit antenna selection such that spatial diversity is exploited. We formulate the problem of optimally allocating subcarriers and antennas among secondary users as a binary integer program, where optimality is defined in terms of the aggregate visual quality of received video sequences of all cognitive users. The proposed formulation caters to the staircase rate-distortion characteristics of CGS/MGS sequences and avoids allocating more resources than are necessary to attain a given visual quality. However, due to the high computational complexity involved in solving this hard integer program using discrete programming solvers, we reduce the resource allocation problem to a subset-sum problem. Although it remains \cal NP -hard in general, we present two efficient methods to solve this subset-sum problem based on its structure. Simulation results demonstrate that the methods proposed lead to a solution that is close to the optimal. Moreover, we demonstrate that having multiple antennas at the cognitive base station reduces the outage probability of secondary users. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]