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This paper proposes a novel approach to assess the performance in terms of end-to-end throughput of an ad hoc multi-hop wireless network, where each link is affected by interference coming from other multi-hop paths nearby. The approach captures the mutual impact of each path on all others. It can be applied to both, contention-based and scheduled, medium access control (MAC) protocols. Sources have data to send to destination nodes through $n$ relays. Nodes are assumed to be uniformly and randomly distributed in the 2-D infinite plane. The model shows the impact on the end-to-end throughput of $n$ ; it also captures the influence of node density, traffic generated, number of retransmissions, and other MAC parameters. Finally, the model provides the throughput-delay tradeoff. Unlike most previous approaches, the mathematical tool proposed appears to be scalable, allowing easy extension to any number of hops. Comparison with simulation results is provided to prove that the impact of the approximations introduced in the analysis is almost negligible. [ABSTRACT FROM PUBLISHER]

In this paper, we study the throughput and delay in wireless cognitive social networks. Specifically, we consider a common scenario for cognitive radio networks (CRNs) where the primary and secondary networks operate at the same time and space and share the spectrum. On this basis, we integrate a social relationship into the CRN where each source node selects its destination upon a rank-based model, which captures the social characteristic well. By applying a cellular time-division multiple-access scheduling scheme, we first characterize the distinct traffic pattern caused by the social relationships between nodes. Then, we derive the achievable throughput and delay for both primary and secondary networks under the new network setting. In addition, we also study the cognitive social networks with infrastructure where $l=o$ $(n)$ base stations are regularly deployed within the primary network. Given a probabilistic routing strategy, throughput of the proposed network is recalculated. Particularly, due to the social relationships between nodes, we reveal that a larger $l$ is required if we expect a significant capacity gain within the primary network compared with previous works. [ABSTRACT FROM PUBLISHER]

The medium access probability (MAP) of a random access protocol can severely impact network throughput especially for delay-sensitive applications, since it determines whether a node should transmit packets in a given slot or not. This paper focuses on network throughput maximization through optimizing the MAPs of all users under delay quality-of-service constraints in wireless interference-limited networks. Specifically, first, the total delay for transmitting one packet for a user is analyzed and derived based on an M/G/1 model. Then, the stochastic property of the aggregated interference is analyzed and its distribution is modeled as a log-normal distribution. Based on the delay and interference models, an optimization problem is formulated to derive the optimal MAPs so that the network throughput is maximized under the delay constraints. Two network traffic scenarios, homogeneous and heterogeneous user traffic, are discussed, respectively. For the case of homogeneous traffic, a closed-form expression of the optimal MAP is derived; for the case of heterogeneous traffic, a global $\epsilon $ -optimal algorithm based on the branch-and-bound framework and convex relaxation technology is proposed with relatively low complexity. Simulations results show that the proposed algorithms can achieve superior network throughput performance over existing schemes. [ABSTRACT FROM PUBLISHER]

This paper studies the bottleneck link capacity under the Gaussian channel model in strongly connected random wireless ad hoc networks, with n nodes independently and uniformly distributed in a unit square. We assume that each node is equipped with two transceivers (one for transmission and one for reception) and allow all nodes to transmit simultaneously. We draw lower and upper bounds, in terms of bottleneck link capacity, for homogeneous networks (all nodes have the same transmission power level) and propose an energy-efficient power assignment algorithm (CBPA) for heterogeneous networks (nodes may have different power levels), with a provable bottleneck link capacity guarantee of \Omega (B\log (1+1/\sqrtn\log^2n)), where B is the channel bandwidth. In addition, we develop a distributed implementation of CBPA with O(n^2) message complexity and provide extensive simulation results. [ABSTRACT FROM PUBLISHER]

In multihop ad hoc networks over 802.11, the real bandwidth-delay product (BDP) cannot reach a value as large as in wired networks due to contention through wireless shared channels. As a result, conventional congestion-control algorithms cause an overshooting window problem and result in poor throughput in ad hoc networks. In this paper, we split the real round-trip time (RTT) into two parts: 1) congestion RTT and 2) contention RTT. We reveal that the contention RTT has nothing to do with the BDP and that the BDP is determined by only the congestion RTT if a link with the worst contention status does not lead to link breakage. An inadequate use of contention RTT causes a Transmission Control Protocol (TCP) congestion window overshooting problem. We propose a novel mechanism called congestion window adaptation through contention detection, which provides a more accurate method of estimating the contention status. Based on this mechanism, we present a congestion window adaptation method to limit the window size from overshooting. Simulation results show that our proposed mechanism outperforms the conventional TCP and the enhanced mechanisms called TCP with contention control and TCP with a maximum window. [ABSTRACT FROM PUBLISHER]

We study distributed queueing games in interference-limited wireless networks. We formulate the throughput maximization problem via distributed selection of users' transmission thresholds as a Nash Equilibrium Problem (NEP). We first focus on the solution analysis of the NEP and derive sufficient conditions for the existence and uniqueness of a Nash Equilibrium (NE). Then, we develop a general best-response-based algorithmic framework wherein the users can explicitly choose the degree of desired cooperation and signaling, converging to different types of solutions, namely: 1) a NE of the NEP when there is no cooperation among users and 2) a stationary point of the Network Utility Maximization (NUM) problem associated with the NEP, when some cooperation among the users in the form of (pricing) message passing is allowed. Finally, as a benchmark, we design a globally optimal but centralized solution method for the nonconvex NUM problem. Our experiments show that in many scenarios the sum-throughput at the NE of the NEP is very close to the global optimum of the NUM problem, which validates our noncooperative and distributed approach. When the gap of the NE from the global optimality is non negligible (e.g., in the presence of “high” coupling among users), exploiting cooperation among the users in the form of pricing enhances the system performance. [ABSTRACT FROM AUTHOR]

We analyze a novel architecture for caching popular video content to enable wireless device-to-device (D2D) collaboration. We focus on the asymptotic scaling characteristics and show how they depend on video content popularity statistics. We identify a fundamental conflict between collaboration distance and interference and show how to optimize the transmission power to maximize frequency reuse. Our main result is a closed form expression of the optimal collaboration distance as a function of the model parameters. Under the common assumption of a Zipf distribution for content reuse, we show that if the Zipf exponent is greater than 1, it is possible to have a number of D2D interference-free collaboration pairs that scales linearly in the number of nodes. If the Zipf exponent is smaller than 1, we identify the best possible scaling in the number of D2D collaborating links. Surprisingly, a very simple distributed caching policy achieves the optimal scaling behavior. [ABSTRACT FROM AUTHOR]

There has been recent interest within the networking research community to understand how performance scales in cognitive networks with overlapping n primary nodes and m secondary nodes. Two important metrics, i.e., throughput and delay, are studied in this paper. We first propose a simple and extendable decision model, i.e., the hybrid protocol model, for the secondary nodes to exploit spatial gap among primary transmissions for frequency reuse. Then, a framework for general cognitive networks is established based on the hybrid protocol model to analyze the occurrence of transmission opportunities for secondary nodes. We show that if the primary network operates in a generalized TDMA fashion, or employs a routing scheme such that traffic flows choose relays independently, then the hybrid protocol model suffices to guide the secondary network to achieve the same throughput and delay scaling as a standalone network without harming the performance of the primary network, as long as the secondary transmission range is smaller than the primary range in order. Our approach is general in the sense that we only make a few weak assumptions on both networks, and therefore it obtains a wide variety of results. We show secondary networks can obtain the same order of throughput and delay as standalone networks when primary networks are classic static networks, networks with random walk mobility, hybrid networks, multicast networks, CSMA networks, networks with general mobility, or clustered networks. Our work presents a relatively complete picture of the performance scaling of cognitive networks and provides fundamental insight on the design of them. [ABSTRACT FROM AUTHOR]

Synchronization among primary users (PUs) and secondary users (SUs) is either explicitly or implicitly assumed in the literature to allow reliable dynamic spectrum access (DSA) and cognitive radio (CR) networking. However, in realistic DSA that supports ad-hoc transmissions, perfect synchronization is not attainable in the absence of a centralized control mechanism, particularly among SUs. Current efforts either ideally assume perfect synchronization among PUs and SUs or consider medium access that does not require network synchronization based on a single SU. In this paper, we propose an implementable asynchronous DSA scheme by practically considering the timing misalignment with multiple SUs competing for the spectrum opportunity. We further employ a game theoretical framework in asynchronous DSA to thoroughly predict the competition among SUs. Based on the equilibrium concept, we identify the feasible operating region, achieving optimal equilibrium that is not only reaching a win–win situation in the sense of PU throughput and spectrum utilization maximization but is robust to potential selfish behavior of SUs as well. Both low-complexity one-shot and sequential-decision access schemes are analyzed. We demonstrate that, when operating in the proposed feasible region, contrary to intuitive conjecture, the asynchronous DSA achieves surprising improvement in spectrum utilization. [ABSTRACT FROM PUBLISHER]

The widespread of smart phones has brought new social-aware features to wireless networks. Users prefer to forward traffic to their social contacts in social-aware networks, which is highly different from the traditional uniform traffic pattern. To this end, we analyze a social-aware wireless network, which is modeled by the social contacts between nodes, and explore its impact on network throughput capacity. We present that it can refine social contacts, thus improving the network capacity. Moreover, directional antennas are applied to further enhance the capacity performance, which can reduce the interference brought by other simultaneous communications. We derive the throughput capacity for social-aware networks with single-beam and multi-beam directional antenna, respectively. For single-beam directional antenna, we prove that when wireless networks are dominated by traffics of short-distance social contact, the throughput capacity can be promoted from order of (\Theta (1/\theta ^2n\,\text log\,n)^1/2) to \Theta (1/\theta ^2 \text log\,n) . In addition, when the beamwidth \theta is at order of \Omega ({1}/{({\log {n}})^{1/2}}) , the throughput capacity is a constant. Thus, the wireless network is scalable. For multi-beam antennas, we prove that when sidelobe gain G_{s} is at order of o(Gm) , where Gm is main lobe gain, compared with the single-beam case, the network capacity can achieve the order of \Theta (1/\theta ^2\text log\,n) . [ABSTRACT FROM AUTHOR]

We consider a multicast scenario that involves an ad hoc network of cochannel multiple-input–multiple-output (MIMO) nodes in which a source node attempts to share a streaming message with all nodes in the network through some predefined multihop routing tree. The message is assumed to be broken down into packets, and the transmission is conducted over multiple frames. Each frame is divided into time slots, and each link in the routing tree is assigned one time slot in which to transmit its current packet. We present an algorithm for determining the number of time slots and the scheduling of the links in these time slots to optimize the connectivity of the network, which we define to be the probability that all links can achieve the required throughput. In addition to time multiplexing, the MIMO nodes also employ beamforming to manage interference when links are simultaneously active, and the beamformers are designed with the maximum connectivity metric in mind. The effects of outdated channel-state information are taken into account in both the scheduling and the beamforming designs. We also derive bounds on the network connectivity and sum transmit power to illustrate the impact of interference on network performance. Our simulation results demonstrate that the choice of the number of time slots is critical in optimizing network performance and illustrates the significant advantage provided by multiple antennas in improving network connectivity. [ABSTRACT FROM PUBLISHER]

Throughput maximization is a key challenge for wireless applications in cognitive Vehicular Ad-hoc Networks (C-VANETs). As a potential solution, cooperative communications, which may increase link capacity by exploiting spatial diversity, has attracted a lot of attention in recent years. However, if link scheduling is considered, this transmission mode may perform worse than direct transmission in terms of end-to-end throughput. In this paper, we propose a cooperative communication aware link scheduling scheme and investigate the throughput maximization problem in C-VANETs. Regarding the features of cooperative communications and the availability of licensed spectrum, we extend the links into cooperative links/general links, define extended link-band pairs, and form a 3-dimensional (3-D) cooperative conflict graph to characterize the conflict relationship among those pairs. Given all cooperative independent sets in this graph, we mathematically formulate an end-to-end throughput maximization problem and near-optimally solve it by linear programming. Due to the NP-completeness of finding all independent sets, we also develop a heuristic pruning algorithm for cooperative communication aware link scheduling. Our simulation results show that the proposed scheme is effective in increasing end-to-end throughput for the session in C-VANETs. [ABSTRACT FROM PUBLISHER]

We study the capacity scaling laws for the cognitive network that consists of the primary hybrid network (PhN) and secondary ad hoc network (SaN). PhN is further comprised of an ad hoc network and a base station-based (BS-based) network. SaN and PhN are overlapping in the same deployment region, operate on the same spectrum, but are independent with each other in terms of communication requirements. The primary users (PUs), i.e., the ad hoc nodes in PhN, have the priority to access the spectrum. The secondary users (SUs), i.e., the ad hoc nodes in SaN, are equipped with cognitive radios, and have the functionalities to sense the idle spectrum and obtain the necessary information of primary nodes in PhN. We assume that PhN adopts one out of three classical types of strategies, i.e., pure ad hoc strategy, BS-based strategy, and hybrid strategy. We aim to directly derive multicast capacity for SaN to unify the unicast and broadcast capacities under two basic principles: 1) The throughput for PhN cannot be undermined in order sense due to the presence of SaN. 2) The protocol adopted by PhN does not alter in the interest of SaN, anyway. Depending on which type of strategy is adopted in PhN, we design the optimal-throughput strategy for SaN. We show that there exists a threshold of the density of SUs according to the density of PUs beyond which it can be proven that: 1) when PhN adopts the pure ad hoc strategy or hybrid strategy, SaN can achieve the multicast capacity of the same order as it is stand-alone; 2) when PhN adopts the BS-based strategy, SaN can asymptotically achieve the multicast capacity of the same order as if PhN were absent, if some specific conditions in terms of relations among the numbers of SUs, PUs, the destinations of each multicast session in SaN, and BSs in PhN hold. [ABSTRACT FROM AUTHOR]

We study the scaling laws for the throughputs and delays of two coexisting wireless networks that operate in the same geographic region. The primary network consists of Poisson distributed legacy users of density n, and the secondary network consists of Poisson distributed cognitive users of density m, with m>n. The primary users have a higher priority to access the spectrum without particular considerations for the secondary users, while the secondary users have to act conservatively in order to limit the interference to the primary users. With a practical assumption that the secondary users only know the locations of the primary transmitters (not the primary receivers), we first show that both networks can achieve the same throughput scaling law as what Gupta and Kumar (IEEE Trans. Inf. Theory, vol. 46, no. 2, pp. 388–404, Mar. 2000) established for a standalone wireless network if proper transmission schemes are deployed, where a certain throughput is achievable for each individual secondary user (i.e., zero outage) with high probability. By using a fluid model, we also show that both networks can achieve the same delay-throughput tradeoff as the optimal one established by El Gamal (IEEE Trans. Inf. Theory, vol. 52, no. 6, pp. 2568–2592, Jun. 2006) for a standalone wireless network. [ABSTRACT FROM PUBLISHER]