Improving Amplify-and-Forward Relay Networks: Optimal Power Allocation versus Selection

In this paper, we study the power allocation of suggested cognitive relay network model to minimize the system outage probability subject to total and individual power constraints for cognitive relays and subject to interference constraints for primary user nodes. In suggested model, a source is assisted by cognitive relay nodes which allow coexisting with primary user nodes by imposing severe constraints on the transmission power so that they operate below the noise floor of primary nodes. A relay transmission scheme, namely, amplify-and-forward (AF) is considered. We present an optimal power allocation (OPA) scheme to minimize the system outage probability, based on complete channel state information among the source, destination and relay nodes and mean channel gains between primary user nodes and cognitive relays. The analytical power allocation strategies have been validated through numerical simulations. The results indicate that the AF with OPA has significantly better outage behavior and average throughput than AF scheme.

This paper considers the wiretap channel in which a source node communicates with a destination node with the aid of a single helper and in the presence of an eavesdropper. The helper can apply either amplify-and-forward (AF) relaying or jamming. The secrecy capacity and respective optimal power allocation schemes at the source and the helper are investigated under both individual and joint power constraints. Given that the links among the nodes might not always be available for transmission (e.g., due to heavy shadowing), several network topologies are considered for relaying. To deal with the related nonconcave optimization problems in solving the optimal power allocation schemes, we first propose an analytical approach based on Descartes' rule of signs. Using this approach, optimal power allocation strategies are derived for some relay topologies and for the jamming system. Insights into the proposed schemes for different transmission power ranges and comparisons to the optimal information rate power allocations are also discussed. Simulation results are finally provided to quantify the optimality of the proposed schemes.

Optimal power allocation (OPA) schemes for amplify-and-forward (AAF) relay networks have been widely investigated in recent years, usually under the assumption of readily known channel state information (CSI). This paper proposes a semi-blind iterative relay node selection (SBIRS) scheme to carry out the OPA procedure when the CSI are entirely unknown at the destination. We first develop a semi-blindly weighted multiple-eigenvector (SBWMEV) solution for optimally allocating power among all the relay nodes in the network. Aided by the intrinsic salient feature of the SBWMEV eigenvector structure, we further propose an iterative relay selection algorithm to simplify the SBWMEV solution with enhanced performance. In an iterative relay node selection manner, the proposed SBIRS scheme is capable of potentially allocating more power to the relay nodes with better channel conditions. Simulations verify that the SBIRS schemes outperform the SBWMEV scheme in terms of throughput and outage probability.

In this paper, the problem of precoder design and node power allocation in a three node cooperative multiple-input multiple-output (MIMO) relay system is discussed. All the nodes are assumed to be equipped with multiple antennas and the source and the relay nodes are subject to a total transmit power constraint. We first introduce an upper bound on the received mean square error (MSE), then we suggest suboptimal structures to the source and the relay precoders to minimize this bound. Unlike the previous works in this area, the proposed precoders are easy to calculate and does not involve in computationally costly iterative methods. Next, based on the precoder structures, it is shown that proper transmit power assignment to the source and relay nodes can further improve the system performance and the optimal power allocation for the special case of single symbol transmission is derived. Simulation results show significant improvement in the received mean square error (MSE) by applying the proposed precoding and node power allocation schemes. The node power allocation scheme is also shown to be most effective when the relay and destination nodes have different noise levels.

To combat the multipath fading, the array gain is introduced to the cooperative system when multiple antennas is applied at relay nodes. Two cooperative schemes, i.e., the reactive and proactive relaying schemes are studied for the non-regenerative relaying, i.e., the amplify-and-forward (AF) mode. The results show that for a K relays network with each relay equips n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> antennas, both these two schemes can achieve order- (2n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">r</sub> K+1) diversity. The optimal power allocation scheme among multiple relay nodes is given, which can be viewed as a modified water-filling algorithm, and improves the performance of the reactive scheme. Furthermore, these two schemes show performance gain over each other depending on the aggregate relay power in the AF mode.

In this paper, the impact of diversity order on symbol error rate (SER) performance is investigated for the cooperative amplify-and-forward (AF) multiple-input-and-multiple-output (MIMO) relaying system under the average power scaling (APS) constraints. Furthermore, the optimal power allocation (OPA) scheme is proposed based on the criterion of maximizing signal-to-noise-ratio (SNR). Through the SER analysis and numerical results, it can be shown that the diversity order in AF MIMO relaying system under APS is M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> (the number of transmitting antennas) when uniform power allocation (UPA) is adopted. Given M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> receiving antennas at the relay nodes, the proposed novel OPA scheme can not only reduce the SER but also improve the diversity order efficiently up to M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> even when M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> = 1.

In this letter, the outage probabilities of selection relaying protocols are analyzed and compared for cooperative wireless networks. It is assumed that both source and relay use equal allocated time in transmission. Depending on the quality of the source-relay channel, the relay may choose either Decode-and-Forward (DF), Amplify-and-Forward (AF), or Direct-Transmission (DT) to forward signals. It turns out that in terms of outage probability, two selection relaying schemes are better than others: selecting between DF and AF protocols (DF-AF) or selecting between DF and DT protocols (DF-DT). It is shown that with an equal power allocation, both of the DF-AF and DF-DT selection relaying protocols have the same asymptotic outage probability. However, with an optimum power allocation strategy, the DF-AF selection scheme is in general better than the DF-DT selection scheme. Note that the optimum power allocations depend on channel variances, not on instantaneous channel gains. When the quality of the relay-destination link is much better than that of the source-relay link, observed from simulation, the outage probability of the DF-AF selection protocol with its optimum power allocation is 1.5 dB better than that of the DF-DT selection with its own optimum power allocation. Extensive simulations are presented to validate the analytical results.

In this paper, a distributed power control algorithm is proposed for wireless relay networks in interference-limited environments. The objective is to minimize the total transmission power while satisfying the signal-to-interference-plus-noise ratio (SINR) requirements. Two forwarding techniques, i.e., decode- and-forward (DF) and amplify-and-forward (AF), are considered. The proposed algorithm only requires locally measured SINR on the relay nodes (RNs) and the destination nodes (DNs), based on which each cooperation unit (defined as one source node (SN) and DN pair with the RN associated to it) iteratively updates the transmission power of the SN and the RN by solving a local optimization problem. We prove that the convergence is guaranteed when the parameters adopted in the algorithm are sufficiently large, and then a parameter adjusting method is also designed. Simulation results indicate that the proposed algorithm converges fast and leads to only 7% more power consumption than the optimal power allocation in the considered scenarios. It is also shown that even in interference-limited environments, relaying can still improve system performance substantially in terms of outage and power consumption.

We study the joint allocation of three types of resources, namely, power, subcarriers and relay nodes, in cooperative two-hop multi-relay OFDM systems. Each relay adopts the amplify-and-forward (AF) protocol. The objective is to maximize the system transmission rate subject to individual power constraints on each node. We formulate such a problem as a subcarrier-pair based resource allocation that seeks the joint optimization of subcarrier pairing, subcarrier-pair-to-relay assignment, and power allocation. Using a dual decomposition method, we solve this problem efficiently in an asymptotically optimal manner. We further propose two suboptimal algorithms to trade off performance for complexity. Simulation results demonstrate that the proposed subcarrier-pair based resource allocation schemes significantly outperform the symbol based benchmark scheme. Moreover, it is shown that subcarrier pairing plays an important role in improving the system performance.

In this paper, we propose a dynamic power allocation scheme for a single-relay network based on orthogonal frequency division multiplexing (OFDM) modulation with limited feedback.We consider an Amplify-and-Forward (AF) cooperative diversity model, where one source node communicates with one destination node assisted by one half duplex relay. The power allocation scheme employs a codebook of quantized power allocation vectors designed offline equipped on the source, relay, and destination. The destination, who has full knowledge of channel state information (CSI), chooses the best power allocation vector and sends back its index to the source and relay nodes, which results in a dramatic reduced overhead over conventional resource allocation. First we achieve the optimal power allocation solution as the function of channel realizations with maximum capacity. Then we present an adaptation of the Lloyd algorithm to construct a codebook to quantize the optimal power allocation vectors subject to the amount of feedback. Simulations show that a negligible performance loss could be achieved with just a few feedback bits at different levels of SNRs.

Cooperative communication has been studied as a way to improve reliability of networks compared to conventional direct transmission scheme. We consider amplify-and-forward (AF) cooperative communication with multiple relays. In this system, there is a problem that which relay nodes should be selected and how much power should be allocated to the selected relay nodes. Most of conventional researches on this model have focused on only improving channel capacity or reliability, rather than saving power consumption in all over the network with maintaining such communication qualities. In this paper, we propose a new power allocation scheme for multiple relay nodes using game theory that focuses on transmission power efficiency. With computer simulation, we show that our proposed game theoretical approach has superiority to some conventional schemes from the viewpoint of transmission power efficiency.

This paper investigates the power allocation between the cognitive transmitter (CT) and the cognitive relay (CR) in a cognitive Amplify-and-Forward (AF) full-duplex relay network. To maximize the cognitive capacity, we firstly obtain a closed form expression of the optimal power allocation with the instantaneous interference channel information. Then considering limited cooperation between the primary and the cognitive networks, we develop an efficient iterative search algorithm to obtain the optimal power allocation with the statistical rather than the instantaneous interference channel information. Furthermore, considering absolutely no cooperation between the primary and the cognitive networks, we develop a sensing-based iterative search algorithm to obtain the optimal power allocation without any interference channel information. Simulation results show the capacity of the cognitive AF full-duplex relay network may achieve up to 50% improvement compared with the cognitive AF half-duplex relay network on the condition that the mean value of the self-interference channel gain is lower than −25 dB.

In this paper, we investigate the performance of an amplify-and-forward (AF) cooperative diversity system with multiple relays in the presence of channel estimation errors. We consider both conventional relaying (in which all relay nodes participate in the relaying phase) and opportunistic relaying (in which only a single relay is allowed to participate). We derive closed-form expressions for error probability, outage probability, and ergodic channel capacity. The derivations are confirmed through Monte Carlo simulations. We further deploy the derived expressions to obtain optimal power allocation rules for performance improvements.

Transmission collision is one of the main reasons of performance degradation in dense wireless sensor networks (WSNs). Transmission collision can cause throughput reduction, excessive delay and packet loss. One of the methods to minimize the probability of packet collision is the reduction of the collision area (area around sending nodes where collision may take place). In this study we investigate the problem of collision probability minimization through the use of cooperative transmissions and optimal power allocation in WSNs. We formulate the problem as a constrained optimization problem subject to an outage probability constraint. We determine the optimal transmission power of the source and the relay nodes which minimizes the collision area. Results show that the proposed technique significantly reduces the collision area while keeping the outage performance below the targeted value. Results also show that the proposed technique outperforms the direct transmission system as well as the cooperative system with equal transmission power.

In this letter, we investigate the joint optimization of sensing time and power allocation for amplify-and-forward cognitive relay networks. By jointly considering the sensing slot and the data transmission slot, the optimization problems are respectively formulated to maximize the average network throughput and minimize the approximate outage probability of secondary transmission under the average transmit power constraint of secondary users and the average interference power constraint of primary user. The optimal algorithms are developed to acquire the optimal sensing time and power allocation. Simulation results demonstrate that significant improvements in the average throughput and outage behavior are achieved through the joint optimization.