Optimal routing control: game theoretic approach

Recently, cooperative communication is shown to be a promising technology to achieve spatial diversity by keeping each node with only one antenna and having a node exploit a relay node's antenna. Most previous works assume that there are multiple source-destination pairs and multiple relay nodes in a network where each node only serves as one role: either transmission node or relay node. However, this assumption will not always hold in practice where each node has its own information to transmit. This paper studies the maximal lifetime scheduling problem for cooperative communication with guaranteed throughput service in a network environment where there are multiple source-destination pairs and each node can serve as both two roles: transmission node and "relay" node. We first analyze the power allocation of optimal lifetime for a single source-destination pair with a bounded throughput in different communication modes, and then design an optimal polynomial-time algorithm to maximize the network lifetime. This algorithm is based on iteration and tries to find a better solution than that before in each iteration. After that, the optimality of this algorithm has been proved formally. The simulation results show that the algorithm can prolong about 199% lifetime than that of direct transmission.

We propose a transmission model for bacteria networks inspired by ad hoc wireless mobile networks. Using bacteria as a message transmission medium has been proposed as a promising approach in molecular communication. The expected message delivery delay is derived for single source-destination pair and can be approximated by a convex function of the number of available carriers in the environment. In the scenario with multiple source-destination pairs, bacteria serving as the medium of message transmission are viewed as a limited resource, since each source-destination pair requires unoccupied carriers to transfer messages. We show that optimal resource allocation can be achieved while satisfying a priority requirement by controlling the release probability of messages at the source nodes. This suggests a guideline for communicating prioritized tasks in ad hoc bacteria networks

Based on the advantages of small size, lightweight, as well as flexible deployment and recycling, unmanned aerial vehicle (UAV) has been more and more widely used in military and civilian. As flying relays, UAVs can quickly set up relay communication links for different missions, to enhance the receiving signal power, increase the system capacity, and expand the communication coverage. In this article, we investigate full-duplex (FD) UAV relaying for multiple source–destination pairs. To fully exploit the flying flexibility of the UAV in serving multiple source–destination pairs, we propose a scheduling protocol that exploits time-division multiple access (TDMA) to serve different source–destination pairs in turns when flying along an optimized trajectory. Then, we further formulate a joint optimization problem of the TDMA-based user scheduling, the dynamic UAV trajectory, and the UAV transmit power to maximize the system throughput. The formulated problem is nonconvex that makes it difficult to solve directly, hence we propose an iterative algorithm to obtain an approximate optimal solution based on block coordinate descent and successive convex optimization techniques. Simulation results demonstrate that our proposed FD-based UAV relaying network achieves significant throughput gains compared with the half-duplex (HD) baseline, and the TDMA-based protocol outperforms the OFDMA-based ones with fixed UAV position/trajectory when the UAV helps relay information for multiple source–destination pairs.

Cooperative communication (CC) has been proposed to increase the wireless channel capacity and reliability by employing multiple single-antenna nodes to form a virtual antenna array. Many efforts focus on exploiting the benefits of CC among multiple source-destination pairs with an unrealistic assumption that each of them communicates over a dedicated channel without interference. In this paper, we investigate the transmission scheduling problem for multiple source-destination pairs under the assistance of a set of dedicated relay nodes on a single channel. By applying the protocol interference model, we propose a concept of cooperative link to characterize the interference regions of CC. Due to the NP-completeness of optimal scheduling, LP (linear programming) based heuristic algorithms are proposed to maximize the minimum transmission rate under a given relay assignment. Then, without specifying a relay node for each source-destination pair, we study the max-min rate problem by jointly considering transmission scheduling and relay assignment. Heuristic algorithms are proposed to solve this more challenging problem. Finally, extensive simulations are conducted to show that the proposed algorithm outperforms direct transmission substantially.

Routing in delay tolerant network (DTN) closely depends on the cooperation of nodes. At present, there are many works exploring the impact of the selfish behavior. However, most of these works assume that there is only one source-destination pair, and the source just generates one message. For this reason, this paper studies the impact of selfish behavior when many messages are transmitted at the same time. In particular, there are multiple source-destination pairs, and each source generates the messages according to the Poisson process. Due to the selfish behavior, the nodes may be more willing to forward their own messages. In addition, the nodes may have closer relation with certain nodes (friends). Due to selfishness, the nodes may be more willing to help their friends other than the strangers. In such complex scenario, this paper proposes the theoretical models to evaluate the performance of the two-hop routing algorithm with single-copy and redundancy, respectively. Simulations show the accuracy of the models. Numerical results show that the selfish behavior may significantly increase the average delivery delay. In addition, the selfishness may also decrease the maximal flow.

To exploit multiuser spatial cooperative diversity, relay nodes can assist the transmission of signal from multiple sources to their corresponding destinations in order to combat the noise, the channel fading and the cross-interferences. In this work, we consider a network consisting of N source-destination pairs and a set of M relay nodes. We assume that a fixed total budget of transmit energy is available for allotment among all transmitters, i.e., the source and relay nodes. For such network, we consider the time division Amplify-and-Forward (AF) scheme in 2N time slots, and propose an algorithm to optimize the beamformers and the powers allocated to all transmit nodes. The proposed method maximizes the network sum capacity assuming that the channels state information (CSI) is known. Numerical simulations illustrate the significant improvement obtained under power constraint. This betterment is more pronounced for low power regimes.

The problem of online packet scheduling with hard deadlines has been studied extensively in the single-hop setting, whereas it is notoriously difficult in the multihop setting. This difficulty stems from the fact that packet scheduling decisions at each hop influence and are influenced by decisions on other hops, and only a few provably efficient online scheduling algorithms exist in the multihop setting. We consider a multihop wired network (interference-free and full duplex transmissions) in which packets with various deadlines and weights arrive at and are destined to different nodes through given routes. We study the problem of joint admission control and packet scheduling in order to maximize the cumulative weights of the packets that reach their destinations within their deadlines. We first focus on uplink transmissions in the tree topology and show that the well-known Earliest Deadline First algorithm achieves the same performance as the optimal offline algorithm for any feasible arrival pattern. We then address the general topology with multiple source-destination pairs, develop a simple online algorithm, and show that it is O(PM log PM)-competitive, where PM is the maximum route length among all packets. Our algorithm only requires information along the route of each packet, and our result is valid for general arrival samples. Moreover, we show that O(PM log PM)-competitive is the best any online algorithm can do. Via numerical results, we also show that our algorithm achieves performance that is comparable to the noncausal optimal offline algorithm. To the best of our knowledge, this is the first algorithm with a provable (based on a sample-path construction) competitive ratio, subject to hard deadline constraints for general network topologies.

Multiple-radio multiple-channel wireless mesh networks (MRMC WMNs) are fitting as the wireless backbone networks for ubiquitous Internet access. It is quite a challenge to satisfy the multiple traffic requests from multiple source-destination pairs with different data transmission requirements. The multiple pair traffic flows may cause heavy conflict via the nature of wireless media. To take almost full use of the limited resources, we design a routing algorithm based on ant colony optimization. The pheromone leads the finding of primary paths. The various simulations show the efficiency of the algorithm performance.KeywordsRoutingAnt colony optimizationWireless mesh networksLink interference

Extended opportunity cost model to find near equilibrium electricity prices under non-convexities

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> We propose a minimum mean-square error (MMSE)-based signal forwarding technique for a cooperative relay network. Transmission of information between multiple source-destination pairs through a set of relays is considered. Cooperation between relays has been shown to improve substantially the bit-error rate (BER) performance as compared to noncooperative relays under a total power constraint. A general model for relay cooperation has been considered; however, for a single source-destination scenario, the proposed MMSE relaying strategy has been shown to be a product of receiver and transmitter beamformers at the relay layer. </para>

This paper investigates proactive relay selection (PRS) in distributed cooperative networks with multiple potential relays and multiple source-destination pairs. A simple PRS scheme is proposed and its outage probability is analyzed. Compared with the reactive relay selection (RRS) scheme proposed in, our PRS scheme has a loss on the outage performance. However, its significance lies in three aspects: 1) It is fully decentralized; 2) It has less signalling overhead; 3) It saves the network energy consumption. This shows that our PRS scheme is specifically valuable to networks which do not allow centralized control and are energy constrained, such as ad hoc or sensor networks.

We consider a multipoint-to-multipoint cognitive network wherein the communications from L sources to their designated destinations are carried out through the use of K relays in a dual-hop amplify-and-forward cooperative scheme. Aiming to maximize the worst signal-to-interference-plus-noise ratio of the L destinations, we develop a technique that jointly optimizes the sources' transmit powers and the relays' beamforming weights while satisfying the sources and the relays total transmit power constraints as well as the sources individual power constraints and further guaranteeing that the interference powers inflicted from the cognitive network on the M existing primary users are below acceptable thresholds.

We study communication in networks with multiple source-destination pairs and relays. In such networks, the channel output at any destination receiver consists of both the desired signal and interference. In this setting the relay can help forward the desired message of a user to the destination receiver, or help forward interference to a receiver to improve its ability to cancel the interference. Focusing on the impact of interference forwarding, we define a new relay-interferer channel (RIC) model, which serves as the basic building block for the study of interference in multiuser networks. Using the RIC we show that correlation between the codebooks of the relay and the interferer (e.g. superposition codebooks) is essential for obtaining performance benefits from interference forwarding. We conclude that in order to achieve rate gains from relaying interference using the decode-and-forward strategy, a superposition codebook is required. Otherwise, this relay strategy has the same rate as interference cancellation at the receiver. We also conclude that compress-and-forward is not useful for forwarding interference and has no better performance than just treating interference as noise at the decoder.

This paper addresses the design of multiuser MIMO amplify-and-forward relaying within a cloud radio access network (C-RAN) from an energy-efficiency perspective. The aim is to jointly select remote radio heads and optimize their transceiver in order to assist the communication between multiple source-destination pairs. We formulate the design problem as an interference leakage minimization subject to per-relay power constraints along with linear signal preserving constraints at the destinations. To obtain an energy efficient relaying solution, the objective function is penalized with a regularization term which promotes group-sparsity among the resultant relaying weights. A low-complexity iterative algorithm based on the alternating direction method of multipliers (ADMM) is then proposed to solve the regularized problem. Simulation results demonstrate the explicit benefits of the proposed algorithm, which results in notably lower power consumption and computational complexity than conventional relaying design methods.

We consider the problem of minimizing age in a multihop wireless network. There are multiple source-destination pairs, transmitting data through multiple wireless channels, over multiple hops. We propose a network control policy which consists of a distributed scheduling algorithm, utilizing channel state information and queue lengths at each link, in combination with a packet dropping rule. Dropping of older packets locally at queues is seen to reduce the average age of flows, even below what can be achieved by Last Come First Served (LCFS) scheduling. Dropping of older packets also allows us to use the network without congestion, irrespective of the rate at which updates are generated. Furthermore, exploiting system state information substantially improves performance. The proposed scheduling policy obtains average age values close to a theoretical lower bound as well.