Keshav Singh

Toward Green Power Allocation in Relay-Assisted Multiuser Networks: A Pricing-Based Approach

Green communications have emerged as a demanding concept for improving the network energy efficiency (EE). In this paper, a pricing-based approach is investigated to achieve energy-efficient power allocation in relay-assisted multiuser networks. We introduce a network price to the power consumption as a penalty for the achievable sum rate, and study its impact on the tradeoff between the EE and the spectral efficiency (SE). It is hard to directly solve the problem as it is non-convex, and thus a concave lower bound on the pricing-based utility is applied to transform the problem into a convex one. Through dual decomposition, a q-price algorithm is proposed for iteratively tightening the lower bound and finding the optimal solution. In addition, an optimal price that enables green power allocation is defined and found from the viewpoint of maximizing EE. We further analyze the optimal power allocation strategies of the pricing-based approach in a two-user case under different noise operating regimes, yielding on-off, water-filling, and channel-reversal approaches, etc. Finally, the performance of the proposed approach is evaluated by computer simulations, and we characterize the interaction between the EE and SE for various network parameters when the network is designed from the energy-efficient perspective.

Joint QoS-promising and EE-balancing power allocation for two-way relay networks

In this paper, we focus on designing energy-efficient power allocation schemes to improve the energy efficiency (EE) in multiuser multi-carrier two-way relay networks which are able to not only balance the EE of the two-way links but also ensure the quality-of-service (QoS). Specifically, the proposed design framework attempts to maximize a ratio of the spectral efficiency (SE) over the total network power consumption under a total power constraint as well as a signal-to-interference plus noise power ratio (SINR) constraint. The original problem is indeed non-convex, and we prove the convexity of the problem after a series of convex transformation. An iterative approach is proposed to find the local optimal solution of the original problem for achieving the maximum EE. Simulation results are provided to demonstrate the tradeoff between the EE and the SE.

Optimal Energy-Efficient Power Allocation for Multiuser Relay Networks

The rapid growth of diversified applications has led to significant increase in data traffic and energy consumption in wireless networks. Hence, the energy efficiency becomes one of critical performance indices for designing next-generation wireless networks. In this paper, an optimization framework of power allocation is investigated for maximizing energy efficiency in multiuser relay networks. Under a total power constraint, we formulate the design problem with the objective as the ratio of the spectral efficiency over the entire power consumption of the network. An optimal energy-efficient power allocation algorithm is proposed for the source and the relay nodes to approach the maximum efficiency in an iterative manner. Compared with a heuristic scheme where the total available power is equally allocated to all nodes, the proposed optimal power allocation algorithm can dramatically improve energy efficiency with a slight loss in spectral efficiency.

Power control for achieving energy-efficient multiuser two-way balancing relay networks

Energy efficiency is a growing concern for the future wireless networks as energy consumption becomes a global environment problem. In this paper, an energy-efficient power control scheme is investigated for achieving the maximum energy efficiency in multiuser two-way balancing relay networks. We formulate the design problem as a ratio of the spectral efficiency over the entire energy consumption of the network under a total power constraint. An optimal power control scheme is proposed to iteratively improve the efficiency and finally reach the globally optimal solution. Compared with a heuristic scheme where the total available power is equally distributed among all nodes, the proposed scheme can dramatically improve not only the energy efficiency but also the spectral efficiency.

A General Approach Toward Green Resource Allocation in Relay-Assisted Multiuser Communication Networks

The rapid growth of energy consumption due to the strong demands of wireless multimedia services, has become a major concern from the environmental perspective. In this paper, we investigate a novel energy-efficient resource allocation scheme for relay-assisted multiuser networks to maximize the energy efficiency (EE) of the network by jointly optimizing the subcarrier pairing permutation formed in one-to-many/many-to-one manner, subcarrier allocation, as well as the power allocation altogether. By analyzing the properties of the complex mixed-integer nonlinear programming problem, which is generally very difficult to solve in its original form, we transform the problem into an equivalent convex problem by relaxing the integer variables using the concept of subcarrier time sharing, and by applying a successive convex approximation approach. Based on the dual decomposition method, we derive an optimal solution to the joint optimization problem. The impact of different network parameters, namely number of subcarriers and number of users, on the attainable EE and spectral efficiency (SE) performance of the proposed design framework is also investigated. The numerical results are provided to validate the theoretical findings and to demonstrate the effectiveness of the proposed algorithm for achieving higher EE and SE than the existing schemes.

QoS-Driven Resource Allocation and EE-Balancing for Multiuser Two-Way Amplify-and-Forward Relay Networks

In this paper, we study the problem of energy-efficient resource allocation in multiuser two-way amplify-and-forward (AF) relay networks with the aim of maximizing the energy efficiency (EE), while ensuring the quality-of-service (QoS) requirements and balancing the EE of the user links. We formulate an EE-balancing optimization problem that maximizes the ratio of the spectral efficiency (SE) over the total power dissipation subject to QoS and a limited transmit power constraints. The problem which maximizes the EE by jointly optimizing the subcarrier pairing, power allocation, and subcarrier allocation, turns out to be a non-convex fractional mixed-integer nonlinear programming problem, which has an intractable complexity in general. We apply a concave lower bound on the achievable sum rate and a series of convex transformations to make the problem convex one and propose an iterative algorithm for iteratively tightening the lower bound and finding the optimal solution through dual decomposition approach. In addition, a low-complexity suboptimal algorithm is investigated. We then characterize the impact of various network parameters on the attainable EE and SE of the network employing both EE maximization and SE maximization algorithms when the network is designed from the EE perspective. Simulation results demonstrate the effectiveness of the proposed algorithms.

Energy Efficient Resource Allocation for Multiuser Relay Networks

In this paper, a novel resource allocation algorithm is investigated to maximize the energy efficiency (EE) in multiuser decode-and-forward (DF) relay interference networks. The EE optimization problem is formulated as the ratio of the spectrum efficiency (SE) over the entire power consumption of the network subject to total transmit power, subcarrier pairing, and allocation constraints. The formulated problem is a nonconvex fractional mixed binary integer programming problem, i.e., NP-hard to solve. Furthermore, we resolve the convexity of the problem by a series of convex transformations and propose an iterative EE maximization algorithm to jointly determine the optimal subcarrier pairing at the relay, subcarrier allocation to each user pair and power allocation to all source and the relay nodes. Additionally, we derive an asymptotically optimal solution by using the dual decomposition method. To gain more insights into the obtained solutions, we further analyze the resource allocation algorithm in a two-user case with interference-dominated and noise-dominated regimes. In addition, a suboptimal algorithm is investigated with reduced complexity at the cost of acceptable performance degradation. Simulation results are used to evaluate the performance of the proposed algorithms and demonstrate the impacts of various network parameters on the attainable EE and SE.

Power Allocation and Relay Selection in Relay Networks: A Perturbation-Based Approach

A perturbation-based power allocation and multirelay selection approach is proposed for multiple-input multiple-output relay networks in multipath fading channels. In this approach, the relays are partitioned into two groups according to Lagrangian multipliers of power constraints. The power allocation for the relays is perturbed by increasing the power for the potential relays group, while decreasing the power of the relays in the other group. An optimization framework is then formulated as a tradeoff between the relay selection and the mean square error performance degradation. Computer simulations are used to demonstrate the performance.

Joint power control and energy transfer for energy harvesting relay networks

Energy harvesting and wireless energy transfer are capable of relieving the battery limitation of wireless devices. In this paper, an amplify-and-forward relay network (AF-RN) is considered, where an energy harvesting source node communicates with a destination node through an energy harvesting relay node. To further improve the performance, the relay is allowed to harvest energy from the radio frequency (RF) signals sent by the source node through a dedicated energy control channel. A joint power control and energy transfer scheme is investigated with the goal of maximizing the achievable sum rate by a deadline subject to energy causality constraints. The problem is challenging in that the objective function is non-convex, and a successive convex approximation approach is proposed to achieve the optimal power control and energy transfer solution. Finally, numerical examples are given to demonstrate the effectiveness of our proposed algorithm.

Joint Power Allocation, Equalization, and Relay Selection for MIMO Relay Networks With Multipath Receptions

Multiple-input multiple-output (MIMO) relays can improve cell coverage and data throughput for wireless networks. The key challenge for the success of MIMO relay networks is effectively managing the intersymbol interference (ISI) and multiantenna interference (MAI) in multipath channels. In this paper, equalize-and-forward (EF) relaying strategies are employed to mitigate the interference by jointly optimizing equalizer weights and power allocation for dual-hop MIMO relay networks. Two scenarios with different channel state information (CSI) knowledge are investigated: 1) full CSI at the relays and 2) only backward CSI at the relays and the destination. By considering CSI availability and using the minimum-mean-square-error (MMSE) criterion, iterative algorithms are proposed for the joint design of equalizer weights and power allocation to resolve the interference problem. We then extend the design to a more general case, in which the direct link between the source and the destination is taken into account. Furthermore, two relay selection algorithms based on allocated power and MSE performance are investigated for the two scenarios, which attain a performance that is comparable to that of cases with brute-force search or without relay selection. The design framework can capture the impact of the available CSI at the relays and the destination on the performance of MIMO multirelay networks with multipath receptions.