Effective Capacity Maximization With Statistical Delay and Effective Energy Efficiency Requirements

This paper presents the three-fold energy, rate and delay tradeoff in mobile multimedia fading channels. In particular, we propose a rate-efficient power allocation strategy for delay-outage limited applications with constraints on energy-per-bit consumption of the system. For this purpose, at a target delay-outage probability, the link-layer energy efficiency, referred to as effective-EE, is measured by the ratio of effective capacity (EC) and the total expenditure power, including the transmission power and the circuit power. At first, the maximum effective-EE of the channel at a target delay-outage probability is found. Then, the optimal power allocation strategy is obtained to maximize EC subject to an effective-EE constraint with the limit set at a certain ratio of the maximum achievable effective-EE of the channel. We then investigate the effect of the circuit power level on the maximum EC. Further, to set a guideline on how to choose the effective-EE limit, we obtain the transmit power level at which the rate of increasing EC (as a function of transmit power) matches a scaled rate of losing effective-EE. Analytical results show that a considerable EC-gain can be achieved with a small sacrifice in effective-EE from its maximum value. This gain increases considerably as the delay constraint becomes tight

Rate Splitting in Multi - Pair Energy Harvesting Relaying systems

Rate-splitting (RS) technique has recently been proposed to provide significant performance benefits in multiple users communication systems. In this paper, we investigate the performance benefits of RS in a multi-pair relay network, in which multiple users communicate with multiple destination users through a multiple antennas decode-and-forward (DF) energy-harvesting (EH) relay node. In the first phase, the users transmit their independent signals to the relay. Part of the received signal power will be harvested at the relay node. In the second phase, the relay uses the harvested energy to decode and forward the received signals to their intended users using RS transmission technique. Based on the amount of the harvested power and the availability of the channel state information (CSI) at the relay node, different RS transmission strategies are investigated. New closed-form analytical expressions for the ergodic spectral efficiency is derived and Monte-Carlo simulations are provided to confirm the derivations. In addition, the impacts of the main system parameters on the proposed strategies are investigated

NOMA in Cooperative Communication Systems with Energy-Harvesting Nodes and Wireless Secure Transmission

In this paper, non-orthogonal multiple access (NOMA) in cooperative relay system is considered, where a source node communicates with a pair of energy harvesting (EH) user equipments through a multiple antennas relay node. A hybrid protocol is adopted at the relay, in which if the relay can successfully decode the signals, decode- and-forward (DF) protocol will be adopted to forward the signals to the users. Otherwise, amplify-and-forward (AF) protocol will be implemented. Assuming that the users adopt maximal ratio combining (MRC) to combine the received signals in the two cooperative phases, new explicit analytical expressions for the average sum-rate are derived when the relay works in, 1) AF mode, and 2) DF mode, in two scenarios when one user is the stronger in both cooperation phases, and when an alternative user is stronger in each phase. Then, the investigation is extended to the case where the relay is an untrusted node, and cooperative jamming technique is proposed to degrade the ability of the relay to decode the signals and enforce the relay to operate always in AF mode. For the untrusted relay scenario, new analytical expression for the average secrecy rate is derived. Monte Carlo simulations are provided to validate the analysis. The simulation results reveal that the location of the relay is the key parameter to achieve the best performance

Interference Efficiency: A New Metric to Analyze the Performance of Cognitive Radio Networks

In this paper, we develop and analyze a novel performance metric, called interference efficiency, which shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the interference efficiency of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power, total transmit power, and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP) that aims to maximize ergodic sum rate of SUs and to minimize average interference power on the primary receiver. We solve the MOP by first transferring it into a single objective problem (SOP) using a weighted sum method. Considering different scenarios in terms of channel state information (CSI) availability to the SU transmitter, we investigate the effect of CSI on the performance and power allocation of the SUs. When full CSI is available, the formulated SOP is nonconvex and is solved using augmented penalty method (also known as the method of multiplier). When only statistical information of the channel gains between the SU transmitters and the PU receiver is available, the SOP is solved using Lagrangian optimization. Numerical results are conducted to corroborate our theoretical analysis

Interference Efficiency: A New Metric to Analyze the Performance of Cognitive Radio Networks

In this paper, we develop and analyze a novel performance metric, called interference efficiency, which shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the interference efficiency of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power, total transmit power, and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP) that aims to maximize ergodic sum rate of SUs and to minimize average interference power on the primary receiver. We solve the MOP by first transferring it into a single objective problem (SOP) using a weighted sum method. Considering different scenarios in terms of channel state information (CSI) availability to the SU transmitter, we investigate the effect of CSI on the performance and power allocation of the SUs. When full CSI is available, the formulated SOP is nonconvex and is solved using augmented penalty method (also known as the method of multiplier). When only statistical information of the channel gains between the SU transmitters and the PU receiver is available, the SOP is solved using Lagrangian optimization. Numerical results are conducted to corroborate our theoretical analysis

Tradeoff Analysis and Joint Optimization of Link-Layer Energy Efficiency and Effective Capacity Toward Green Communications

A joint optimization problem of link-layer energy efficiency (EE) and effective capacity (EC) in a Nakagami-m fading channel under a delay-outage probability constraint and an average transmit power constraint is considered and investigated in this paper. First, a normalized multi-objective optimization problem (MOP) is formulated and transformed into a single-objective optimization problem (SOP), by applying the weighted sum method. The formulated SOP is then proved to be continuously differentiable and strictly quasiconvex in the optimum average input power, which turns out to be a cup shape curve. Furthermore, the weighted quasiconvex tradeoff problem is solved by first using Charnes-Cooper transformation and then applying Karush-Kuhn-Tucker (KKT) conditions. The proposed optimal power allocation, which includes the optimal strategy for the link-layer EE-maximization problem and the EC-maximization problem as extreme cases, is proved to be sufficient for the Pareto optimal set of the original EE-EC MOP. Moreover, we prove that the optimum average power level monotonically decreases with the importance weight, but strictly increases with the normalization factor, the circuit power and the power amplifier efficiency. Simulation results confirm the analytical derivations and further show the effects of fading severeness and transmission power limit on the tradeoff performance

Weighted tradeoff between effective capacity and energy efficiency

This paper proposes a new power allocation technique to jointly optimize link-layer energy efficiency (EE) and effective capacity (EC) of a Rayleigh flat-fading channel with delay-outage probability constraints. Specifically, EE is formulated as the ratio of EC to the sum of transmission power and rate-independent circuit power consumption. A multi-objective optimization problem (MOP) to jointly maximize EE and EC is then formulated. By introducing importance weight into the MOP, we can flexibly change the priority level of EE and EC, and convert the MOP into a single-objective optimization problem (SOP) which can be solved using fractional programming. At first, for a given importance weight and a target delay-outage probability, the optimum average transmission power level to maximize the SOP is found. Then, the optimal power allocation strategy is derived based on the obtained average input power level. Simulation results confirm the analytical derivations and further show the effects of circuit power, importance weight, and transmission power constraint limit on the achievable tradeoff performance

Wireless Power Transfer in Distributed Antenna Systems

This paper studies the performance of wireless power transfer in distributed antenna systems (DAS). In particular, the distributed remote radio heads (RRHs), which are conventionally distributed in the network to enhance the performance, are also used to increase the energy harvesting (EH) at the energy-constrained users. Based on this idea, the network area is divided into two zones, namely, A) EH zone and B) Interference zone. The users in the EH zones are guaranteed to harvest sufficient energy from the closed RRH, while the users in the interference zones harvest energy from the surrounding RRHs. A harvest-then-transmit protocol is adopted, where in the power transfer phase the multiple antennas RRHs broadcast energy signals to the users. In the information transmission phase, the users utilize the harvested energy to transmit their signals to the RRHs. In addition, zero-forcing is applied at the RRHs receivers, to mitigate the interference. The system spectral efficiency is evaluated in two different scenarios based on the channel state information (CSI), namely: 1) CSI is unknown at the RRHs; 2) CSI is perfectly known at the RRHs. In contrast to conventional EH-muliple input multiple output (MIMO) systems, performance analysis of EH DAS-MIMO is a challenging problem, because the channels are characterized by non-identical path-loss and EH effects which make the classical analytical methods nontractable. In light of this, new analytical expressions of the ergodic spectral efficiency are derived, and then Monte-Carlo simulations are provided to verify the accuracy of our analysis. The effects of main system parameters on the EH-DAS performance are investigated. The results show that there is an optimal value of the EH time for each users locations that maximizes the system performance. In addition, size of the EH-zone area depends on the required harvested power at the users which is dependent essentially on the target spectral efficiency