One of the major goals of emerging wireless systems is to prolong the lifetime of wireless communication devices. To this end, this contribution evaluates and optimizes the performance of simultaneous wireless information and power transfer (SWIPT) with an integrated energy and information receiver, which has the advantage of low complexity and energy cost. A tractable expression for the achievable rate is first derived, which is subsequently used to quantify the achievable harvested energy-rate region for the two fundamental SWIPT protocols, namely, power-splitting (PS) and time-switching (TS). In this context, the joint harvested energy-rate outage probability is then defined and minimized for a point-to-point and multicasting system, determining the optimal PS and TS factors for both linear and nonlinear energy harvesting models. In addition, a TS-based broadcasting system is dynamically optimized by maximizing the energy harvested by all users under an achievable rate threshold for each user. The formulated optimization problem is, in fact, particularly challenging due to the non-convex form of the expression for the achievable rate. Yet, an effective solution is ultimately achieved by converting this problem into a convex one. Also, respective computer simulation results corroborate the effectiveness of the proposed framework. Overall, it is shown that the offered results provide meaningful theoretical and practical insights that will be useful in the design and efficient operation of wireless powered systems. Indicatively, unlike the trend in common separated receivers, a region has been identified, where TS outperforms PS.

Airborne radio access networks (A-RANs) is a particularly promising technology due to its ability to offer fast, cost-efficient, and on-demand enhancement of the existing telecommunication infrastructure. The main challenges of ARANs are the energy sustainability of the aerial platforms (APs) and the establishment of reliable links with the ground nodes. To this direction, we propose a novel approach, which is based on mixed free-space optical (FSO)/radio frequency (RF) relaying protocol and simultaneous lightwave information and power transfer (SLIPT). In this context, we also formulate and optimally solve the max-min fairness problem, which regulates the trade-off between the energy and information transfer to the AP and allocates the available resources to multiple endusers. Finally, the impact of the number of users and weather conditions on system's optimal configuration and performance is investigated through simulations. The offered results provide meaningful theoretical and practical insights on the capabilities of the proposed scheme.

We study a wireless-powered uplink communication system with non-orthogonal multiple access (NOMA), consisting of one base station and multiple energy harvesting users. We focus on data rates optimization and fairness increase. We show that the formulated optimization problems can be optimally and efficiently solved by either linear programming methods or convex optimization, which means that the proposed scheme can be easily implemented in practical applications. Simulation results illustrate that the proposed scheme outperforms the baseline orthogonal multiple access scheme, while they reveal the dependence between sum-throughput, minimum data rate, and harvested energy.

Efficient demand side management through dynamic power pricing is an important application in the smart grids. However, in the absence of a detailed user consumption model, it is difficult to set an optimal power price. In this paper, we propose to efficiently capture the user consumption behavior through a user-dependent acceptance price. Each rational user will decide its own acceptance price based on its desire to get served. Then, we model the selfish interaction between operator and users as a Stackelberg game, where the operator aims to maximize its profit, while the individual users try to pay the lowest price and be served in time. After each user selfishly declares its own acceptance price, the operator sets an optimal power price, based on the user feedback and taking into account the random output of the renewable power sources. Simulation results confirm that the operator can maximize its profit and the users get served in time, while the proposed scheme leads to the optimal usage of the renewable power production.

In this paper, we investigate joint relay selection and optimal power allocation, as a means to maximize the achievable rate of an underlay cooperative cognitive radio with carrier aggregation, taking into account the availability of multiple carrier components in two different bands and primary users (PUs) with specific average outage probability requirements. For the acquisition of the interference thresholds, which are set by the PUs on the secondary user (SU), we incorporate a minimum feedback strategy into the problem formulation, based on the minimization of the PUs outage probabilities. The resulting non-convex optimization problem is transformed into a convex one and optimally solved using dual decomposition and an efficient iterative method with closed-form power policies. Simulation results illustrate that the proposed configuration exploits the available degrees of freedom in an efficient way which maximizes the SU throughput while the average outage probability of the PUs is kept at acceptable levels.

We study a wireless-powered uplink communication system with non-orthogonal multiple access (NOMA), consisting of one base station and multiple energy harvesting users. More specifically, we focus on the individual data rate optimization and fairness improvement and we show that the formulated problems can be optimally and efficiently solved by either linear programming or convex optimization. In the provided analysis, two types of decoding order strategies are considered, namely fixed decoding order and time sharing. Furthermore, we propose an efficient greedy algorithm, which is suitable for the practical implementation of the time-sharing strategy. The simulation results illustrate that the proposed scheme outperforms the baseline orthogonal multiple access scheme. More specifically, it is shown that the NOMA offers a considerable improvement in throughput, fairness, and energy efficiency. Also, the dependence among system throughput, minimum individual data rate, and harvested energy is revealed, as well as an interesting tradeoff between rates and energy efficiency. Finally, the convergence speed of the proposed greedy algorithm is evaluated, and it is shown that the required number of iterations is linear with respect to the number of users.

-We study a cloud network with M distributed receiving antennas and L users, which transmit their messages towards a centralized decoder (CD), where M ≥ L. We consider that the cloud network applies the Compute-and-Forward (C&F) protocol, where L antennas/relays are selected to decode integer equations of the transmitted messages. In this work, we focus on the best relay selection and the optimization of the Physical-Layer Network Coding (PNC) at the relays, aiming at the throughput maximization of the network. Existing literature optimizes PNC with respect to the maximization of the minimum rate among users. The proposed strategy maximizes the sum rate of the users allowing non-symmetric rates, while the optimal solution is explored with the aid of the Pareto frontier. The problem of relay selection is matched to a coalition formation game, where the relays and the CD cooperate to maximize their profit. Efficient coalition formation algorithms are proposed, which perform joint relay selection and PNC optimization. Simulation results show that a considerable improvement is achieved compared to existing results, both in terms of the network sum rate and the players' profits.

Motivated by the cooperative game theory, we propose an efficient physical layer network coding technique for compute-and-forward (C&F) relaying systems, which jointly optimizes the sum and the minimum transmission rate, while minimizing the total transmitting power. Specifically, we show that relay selection in C&F networks leads to an increase of both rates. We also propose an algorithmic approach for the rates' further optimization and we illustrate that its implementation can offer the same or even greater gain than adding an extra relay. Furthermore, the tradeoff between the minimum and the sum rate is explained by utilizing the concept of Pareto frontier. Simulations and numerical results show that a combination of relay selection and the proposed algorithms offers a considerable increase in the sum rate for the same transmitting power, without reducing the system's Quality of Service.

We present a novel low-complexity technique that obtains the Physical-Layer Network Coding (PNC) equation coefficient vectors for the two-way relay channel when Compute-and-Forward is employed. The proposed method is based on pre-computed look-up tables that are used for all channel realizations. It is shown that the size of the look-up tables can be made small by taking into account the statistics of the channel coefficients as well as power and performance specifications. Moreover, a low-complexity algorithm is developed for efficient real-time selection of the equation coefficient vectors using the instantaneous channel coefficients and the look-up tables. Although the method may at times exclude some candidate vectors from the search space, simulation results indicate that the effect on the achievable computation rate at the relay is very small. Hence, significant complexity reduction is achieved, while the computation rate remains extremely close to the optimal value.

We employ the theory of multidimensional lattice constellations in order to evaluate the maximum-likelihood (ML) performance of a general multiple-input multiple-output MIMO system. We show that the lattice representation of the equivalent system model enables a mapping of the received signal set to a single point in a multidimensional constellation, with the generator matrix being equal to the equivalent channel matrix. With the aid of this geometrical interpretation, we derive a performance limit for a general MIMO system in terms of the symbol error probability, which can be written in closed form for various designs. Application of the proposed analysis to popular MIMO schemes reveals the tractability of the approach and validates that designs exploiting the available degrees of freedom in a better way approach the proposed performance limit.

We investigate the sensitivity of Compute-and-Forward (C&F) to channel estimation errors. More specifically, a general formula for the computation rate region of a C&F relay, suffering from imperfect channel estimation, is derived, which is then tightly approximated for Gaussian distributed channel estimation errors. Furthermore, a closed-form expression for the distribution of the C&F rate loss is presented, which can be efficiently used to compute relevant statistical parameters, such as the mean rate loss. Numerical and simulation results highlight the high sensitivity of the overall network performance to channel estimation errors.

Multidimensional lattice constellations which present signal space diversity (SSD) have been extensively studied for single-antenna transmission over fading channels, with focus on their optimal design for achieving high diversity gain. In this two-part series of papers we present a novel combinatorial geometrical approach based on parallelotope geometry, for the performance evaluation of multidimensional finite lattice constellations with arbitrary structure, dimension and rank. In Part I, we present an analytical expression for the exact symbol error probability (SEP) of multidimensional signal sets, and two novel closed-form bounds, named Multiple Sphere Lower Bound (MLSB) and Multiple Sphere Upper Bound (MSUB). Part II extends the analysis to the transmission over fading channels, where multidimensional signal sets are commonly used to combat fading degradation. Numerical and simulation results show that the proposed geometrical approach leads to bounds that can be used for the performance evaluation and the design of multidimensional lattice constellations, both in Additive White Gaussian Noise (AWGN) and fading channels.

This is the second part of a two-part series of papers, where the error performance of multidimensional lattice constellations with signal space diversity (SSD) is investigated. In Part I, following a novel combinatorial geometrical approach which is based on parallelotope geometry, we have presented an exact analytical expression and two closed-form bounds for the symbol error probability (SEP) in Additive White Gaussian Noise (AWGN). In the present Part II, we extend the analysis and present a novel analytical expression for the Frame Error Probability (FEP) of multidimensional lattice constellations over Nakagami-m fading channels. As the FEP of infinite lattice constellations is lower bounded by the Sphere Lower Bound (SLB), we propose the Sphere Upper Bound (SUB) for block fading channels. Furthermore, two novel bounds for the FEP of multidimensional lattice constellations over block fading channels, named Multiple Sphere Lower Bound (MSLB) and Multiple Sphere Upper Bound (MSUB), are presented. The expressions for the SLB and SUB are given in closed form, while the corresponding ones for MSLB and MSUB are given in closed form for unitary block length. Numerical and simulation results illustrate the tightness of the proposed bounds which can be efficiently used to set the performance limits on the FEP of lattice constellations of arbitrary structure, dimension and rank.

We present a novel combinatorial geometrical approach for evaluating the performance of multidimensional finite lattice constellations in Additive White Gaussian Noise (AWGN). More specifically, we present an analytical expression for the exact symbol error probability (SEP) of multidimensional signal sets, which is then used to derive a tight closed-form lower bound of the SEP, named Multiple Sphere Lower Bound (MLSB). Simulations are used to compare the proposed bound with the performance of various lattice constellations. It is clearly demonstrated that the MSLB can be efficiently used in finite lattice constellations, with arbitrary structure, dimension and rank. Furthermore, it can be easily extended to the case of fading channels, where multidimensional signal sets are commonly used to combat fading degradation.

We study a parametric quadrature amplitude modulation (QAM) family, called θ-QAM, which includes other known constellations, such as square QAM (SQAM) and triangular QAM (TQAM), as special cases. The versatile structure of the θ-QAM signal constellation, which occurs from the varying angle between the signal points, results in achieving the minimum symbol error rate (SER) or bit error rate (BER), under an average power constraint. The theoretical study aims at providing insight into the trade-off between error performance and complexity of this parametric modulation scheme. Exact analytical expressions are obtained for the SER in additive white Gaussian Noise (AWGN) and Nakagami-m fading channels, while highly accurate BER approximations are presented. Finally, we find the optimum angles, in a minimal SER or BER sense, for a specific signal-to-noise ratio (SNR) and modulation order, M. This serves as an indicator for the appropriate constellation with respect to channel conditions and SER or BER requirements. The presented theoretical analysis is validated via extensive computer simulations.

We study the performance of a parametric quadrature amplitude modulation (QAM) family, called thetas-QAM, which includes other known constellations, such as square QAM (SQAM) and triangular QAM (TQAM), as special cases. The versatile structure of the thetas-QAM signal constellation, which occurs from the varying angle between the signal points, results in achieving the minimum symbol error rate (SER) or bit error rate (BER), under an average power constraint. Exact analytical expressions are obtained for the SER performance of thetas-QAM in additive white Gaussian noise (AWGN) and Nakagami-m fading channels, while highly accurate approximations for the BER are presented. The theoretical study aims at providing insight into the tradeoff between error performance and complexity of this parametric modulation scheme. The presented theoretical analysis is validated via extensive computer simulations.