With the advance of the photovoltaic panel technology, the infrastructure equipment of cellular networks with solar energy sources has attracted extensive interests. It is expected that base stations (BSs) and relay stations (RSs) with renewable energy will play important roles in reducing the power consumption from electrical grids in future green cellular networks. Inspired by this technology trend, this paper considers a heterogeneous green cellular network, in which a part of RSs is powered by solar energy sources to represent the incremental deployment for the infrastructure with renewable energy in the near future. We formulate a new relay selection and power allocation problem with Mixed Integer Linear Programming to select solar-powered RSs and grid-powered RSs, such that the total grid power consumption is effectively minimized in decode-and-forward cooperative communication networks. We design an algorithm to derive the optimal solution, and also devise an efficient distributed algorithm to reduce the computational cost. The simulation results demonstrate that the algorithms can effectively reduce the total grid power consumption with different channel conditions, different deployments of RSs in a network, and different available power levels in solar-powered RSs. In addition, the problem model and the proposed algorithms can be extended to support hybrid energy sources.

Power and on-off control problems are examined for renewable energy enabled base-stations (BSs) and relay nodes (RNs) in cooperative multicast networks. Renewable energy is utilized at BSs and RNs to reduce the overall grid energy cost. By considering a practical energy consumption model and the statistics of the renewable energy arrival, the optimal transmit powers are first determined by minimizing the expected grid energy consumption subject to an average outage probability constraint at MUs. The optimal solution is found via line search in the general case and is obtained in closed-form at high SNR. In addition, an on-off control policy is also proposed to further reduce the basic operational energy costs. The joint on-off and power control problems are solved approximately using two sequential deflation techniques, namely, the subset-search and the convex-relaxation-based approaches. The power control problem is also extended to the multicarrier scenario with unequal transmit powers and is solved using successive convex approximation. Simulations using the photovoltaic energy arrival model are provided to demonstrate the effectiveness of the proposed schemes. The results show that expending more power at RNs allows for more efficient use of renewable energy and, thus, increases energy-savings.

The effectiveness of epidemic routing for information dissemination in energy harvesting wireless sensor networks is examined in this work. Here, information is to be disseminated from a few nodes to a considerable fraction of all other nodes in the network. The use of epidemic routing is motivated by the fact that, when sensors are supported solely by harvested energy, the sensors' availability and the network topology may change dynamically due to the uncertainty of the energy arrival at the sensors. With epidemic routing, a node will receive and forward a packet to all other nodes in its neighborhood whenever it is able to do so. Each node will keep the packet only for a certain time duration depending on its recovery rate. By utilizing only energy harvested from the environment, the transmission radius of each sensor (and, thus, the network connectivity) is affected by its local energy arrival and the time in between transmissions. The less frequently it transmits, the further the distance it is able to reach. Two cases are examined in this work: 1) the case with identical transmission radius and 2) the case with identical inter-transmission time. The first case occurs when sensors transmit with fixed power and the second case occurs when the sensors operate under a fixed sleep-wake cycle or TDMA scheduling. The transmission radius and intertransmission time required to guarantee that a considerable fraction of nodes receive the information is derived for a given sensor density and recovery rate. Computer simulations are provided to validate our theoretical claims.

The grid-connected photovoltaic (PV) power generator has been demonstrated as a promising solution of hybrid energy to leverage instantaneous renewable energy generation for reducing the energy acquired from electrical grid. In light of this technology trend and opportunity, this paper takes an initial attempt to explore the relay selection and power allocation for green cooperative cellular networks with grid-connected PV power generators. By properly considering the distributions of PV power, we propose an opportunistic relay selection scheme to minimize the grid power consumption. We also analyze the performance on the expected total grid power consumption in the whole network and derive a corresponding upper bound. The simulation results demonstrate that more than 53% of grid power can be saved by the exploitation of PV power with the proposed scheme.

Increasing concerns about climate change are generating significant interest among researchers in reducing the energy consumption of existing communication infrastructure. However, previous research into the efficiency of cooperative communication networks only considers throughput or energy consumption separately. In response, this paper explores the trade-off between these two important factors and proposes maximizing energy efficiency, defined as the ratio of throughput over energy consumption. Because recent research demonstrates that machine operations require more energy, we propose opti- mally switching off unnecessary relays, while efficiently exploiting adaptive modulation (AM) to ensure that all multicast users can be served simultaneously under a required bit error rate. However, finding the optimal on/off relay mode and AM mode is challenging due to numerous possibilities required to be carefully considered and examined. To address this issue, we design an energy efficiency-aware search algorithm (EESA) to find the optimal solution. Our simulation results demonstrate that EESA is able to effectively improve the energy efficiency in cooperative multicast networks.

Cooperative communication has been drawn much attention recently due to the benefit of diversity; however, this technique also reduces the spectral efficiency. To aim at this problem, adaptive modulation is a possible remedy to achieve better efficiency especially for the multinode cooperative communication system. In this work, the Gilbert channel model is adopted to emulate the behavior of the decode-and-forward protocol at the relay nodes. At the destination node, three commonly used combining methods are evaluated, such as the maximum ratio combination (MRC), the equal gain combination (EGC), and the pre-weighted maximum ratio combination (Pre-MRC). The mathematical analysis of the total SNR of each case is also conducted, including the exact results for MRC and proper upper bounds for EGC and Pre-MRC. Based on this analysis, the improvement of multinode cooperation is validated. Meanwhile, the diversity benefit of this system will be also studied via the comparison with the traditional multiple-input single-output (MISO) system.

OFDM-based communication systems have been widely used in several wireless network applications. In order to achieve a more efficient resource allocation, an novel bit and power allocation algorithm with lifetime consideration is proposed. In this work, the lifetime is specified by the portion of power or energy that a particular user can enjoy during the entire transmission. The proposed algorithm aims at the maximization of total transmission rate so that the lifetime constraint can be fulfilled in the long run. The proposed algorithm consists of two steps. In the first step, the optimal solution is found via the Lagrange multiplier method. However, the optimal solution is infeasible. In the second step, a suboptimal solution is achieved based on the optimal solution in the first step. Through the rigorous mathematical proof, the proposed algorithm is shown to be able to fulfill the lifetime requirement. Also, the simulation results show the validation of the theoretical derivation and the feasibility of the proposed algorithm.

We investigate a commonly used power control scheme called single-step power control (SSPC) in finite state Markov channel (FSMC). The performance of SSPC is highly affected by two major factors, the power control error (PCE) and the imperfect feedback of the SSPC commands. In the first part of this work, we aim at modelling the behavior of PCE in FSMC. Based on the proposed PCE model, BER and PER performance are evaluated. Simulation results have shown the validity of the proposed PCE model, derived PER and BER in this work. In the second part of this work, SSPC models under different scenarios are established in order to understand the impact of the imperfect feedback on SSPC commands and to obtain the interactions between SSPC and FSMC. We consider four scenarios, perfect feedback, command error, command loss and command delay. The associated transitional probabilities of each scenario are given. Extensive simulation has shown the accuracy of the proposed SSPC models in these four scenarios.

Much attention had been devoted to study the bit error rate (BER) of hierarchical modulation on point-to-point transmissions in recent years. But few mention the error performance of hierarchical modulation on cooperative communication systems. Thus, in this paper, we derive the explicit closed-form expressions of the exact bit error rate computation for cooperative communication systems with hierarchical modulation over additive white Gaussian noise (AWGN) channels and Rayleigh fading channels. To obtain the theoretical formulas of error rate performance, an analyzing model is proposed to clearly express all possibilities of each transmission. For error rate performance, the expression for BER is a function of distance parameters. Based on this relationship, a criterion is proposed to choose the optimal distance parameters for minimizing the BER of the refinement bits while guaranteeing the BER requirement of the base bits. Simulation results validate the correctness of the derived BERs of the base bits and the refinement bits. Also from simulation results, the performance with optimal distance parameters is greatly improved compared to the non-optimal distance parameters.

The analysis regarding the impact of the single-step power control (SSPC) scheme on the system performance such as bit error rate, packet error rate and queueing variation is hard to access. In this work, we propose an approach to analyze that impact when being in finite state Markov channel (FSMC). To achieve the understanding of the relationship between SSPC, FSMC, and the queueing variation, power control error (PCE), error rate, and PDF of queueing length are first calculated. PCE variation is modelled, which then benefits the evaluation of packet error rate (PER) and bit error rate (BER). Furthermore, based on these results, a queueing model is proposed to describe the variation of queueing length, which is an embedded Markov chain. The proposed queueing model can help determine the optimal queueing buffer size and the optimal target SNR for a specific overflow probability under. Simulation results have shown the validation of the proposed PCE variation model and queueing variation model.

The analysis regarding the impact of the single-step power control (SSPC) scheme on the system performance such as bit error rate, packet error rate, and queueing variation is hard to access. In this work, we propose an approach to analyze that impact when being in finite state Markov channel (FSMC). To achieve the understanding of the relationship between SSPC, FSMC, and the queueing variation, power control error (PCE), error rate, and the PDF of queueing length are first calculated. PCE variation is modelled, which then benefits the evaluation of packet error rate (PER) and bit error rate (BER). Furthermore, based on these analysis, a SSPC model is proposed to simplify the overall system. The behavior of SSPC in FSMC can be better understood with the help of the proposed SSPC model. Simulation results have shown the validation of the proposed PCE variation model and SSPC model.

Cross-layer design has been drawing much attention recently. However, few works are related to how traditional power control schemes, like single-step and multiple-step power control schemes, affect the queueing performance. In light of this, we will compare the queueing performance of single-step and multiple-step power control schemes in finite state Markov channel (FSMC) through simulation in this work. Along with this comparison, we will propose an approach to estimate the power control error (PCE) in the single-step power control scheme. Based on the estimated PCE, the theoretical performance of single-step power control scheme is given. Simulation results have shown that the multiple-step power control scheme is superior to the single-step power control scheme regarding queueing length, service time and throughput. Simulations also validates the proposed PCE estimation and the theoretical performance based on the estimated PCE.