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Recently, multiple concurrent transmission techniques have been proposed for smartly exploiting interference to improve network throughput. This paper considers zero-forcing (ZF) precoding that allows two interfering links to concurrently transmit under certain situations. This paper focuses on identifying appropriate schedule schemes that efficiently utilize the ZF precoding opportunities to improve network throughput. With this motivation, we define novel link models to formulate our concerned problem. We also develop a distributed scheduling algorithm by using belief propagation. Finally, we conduct extensive simulation experiments to evaluate the efficiency of ZF in improving network throughput in multihop wireless networks. Our simulations confirm that intelligently utilizing ZF in multihop networks is very effective in improving throughput. [ABSTRACT FROM PUBLISHER]

In this paper, we consider random-access wireless multihop networks, with multipacket reception capabilities, where multiple flows are forwarded to the gateways through node disjoint paths. We explore the issue of allocating flow on multiple paths, exhibiting both intra- and interpath interference, in order to maximize average aggregate flow throughput (AAT) and provide bounded packet delay. A distributed flow allocation scheme is proposed where allocation of flow on paths is formulated as an optimization problem. Through an illustrative topology, it is shown that the corresponding problem is nonconvex. Furthermore, a simple but accurate model is employed for the AAT achieved by all flows, which captures both intra- and interpath interference through the signal-to-interference-plus-noise ratio (SINR) model. The proposed scheme is evaluated through Ns2 simulations of several random wireless scenarios. Simulation results reveal that the model employed accurately captures the AAT observed in the simulated scenarios, even when the assumption of saturated queues is removed. Simulation results also show that the proposed scheme achieves significantly higher AAT for the vast majority of the wireless scenarios explored than for the following flow allocation schemes: one that assigns flows on paths on a round-robin fashion, one that optimally utilizes the best path (BP) only, and another one that assigns the maximum possible flow on each path. Finally, a variant of the proposed scheme is explored, where interference for each link is approximated by considering its dominant interfering nodes only. [ABSTRACT FROM PUBLISHER]

The optimum designs of multihop networks operating in an interference-limited environment are studied in this paper. The objective is to identify the optimum operation parameters that can maximize the end-to-end throughput of a multihop link in the network. The optimum designs are performed with respect to two parameters, the number of hops, and the signal-to-interference ratio (SIR) threshold for successful transmission. Under a fixed total transmission power, more hops means shorter distance for each hop, but also less power per hop and longer delays. A higher SIR threshold can achieve a higher throughput by employing high-order modulations, but at the cost of a higher outage probability. We capture these tradeoff relationships by deriving the throughput, which is expressed as an explicit function of a number of system parameters. It is shown through theoretical analysis that the throughput is quasi-concave in the number of hops or the SIR threshold, and the optimum design parameters that can maximize the throughput are obtained analytically and verified through simulations. [ABSTRACT FROM AUTHOR]

D2D communications are considered as effective means to achieve vehicle-to-vehicle (V2V) communications, which can be used to improve the performance in vehicular ad hoc networks (VANETs). In this paper, we investigate the resource allocation and interference management based on clustering mechanism in the D2D communications under-laying VANETs aiming to optimize resource utilization efficiency. Firstly, given the transmission resources of intra-cluster for D2D communications, we design a vehicle clustering algorithm to improve intra-cluster resource efficiency and nullify the intra-cluster interference. Secondly, by analyzing the wireless service in VANETs, a cooperative communication scheme with optimized resource utilization is proposed to maximize intra-cluster spectral efficiency. Thirdly, when uplink spectrums are shared, an interference neutralization (IN) model is developed to manage inter-cluster interference, while each vehicle is equipped with one antenna and there is no extra antenna for interference cancellation. In accordance with the IN model, a cross-layer optimization frame for multi-hop VANETs is proposed to maximize the end-to-end throughput of multiple coexisting communication sessions. To evaluate the performance, we select the method without cooperative communication and IN as a benchmark and compare it against the method with cooperative communication only and the method with both cooperative communication and IN. The simulation results show that the method that uses cooperative communication and IN can dramatically increase the throughput. Furthermore, the throughput gains increase along with vehicle density growing in VANETs. [ABSTRACT FROM AUTHOR]

Previous works on multicast capacity mainly focus on deriving asymptotic order results in large-scale wireless networks. While they can explore the general scaling laws of throughput capacity, it is also of great interest for practical concern to predict the exact achievable throughput in networks with an arbitrary finite number of nodes. In this paper, we investigate the nonasymptotic throughput and delay of multihop wireless networks for multicast applications wherein for each source node, $k$ nodes are randomly selected as receivers. It is challenging for the exact performance analysis since multicast transmission has a dynamic nature due to the following factors: 1) random distribution of nodes; 2) bursty traffic arrivals; and 3) different timescales for transient analysis. To tackle the problem, we propose an explicit analytical model and develop a multicast routing scheme, which accounts for these aspects. With our proposed model, we derive lower bound (LB) and upper bound (UB) on nonasymptotic multicast throughput and delay using stochastic network calculus. We show that the performance results hold for all timescales and network sizes and are strongly correlated to data burstiness and the number of receivers. While we investigate from a nonasymptotic point of view, our results can also cover the asymptotic scaling laws. Simulations are conducted to further verify the accuracy of the analytical bounds. [ABSTRACT FROM AUTHOR]

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]

In this paper, we propose two cross-layer algorithms, namely, the Power-optimal Scheduling Algorithm (PSA) and the Throughput-optimal Scheduling Algorithm (TSA), to minimize energy consumption and to maximize throughput, respectively, in multihop wireless networks. Our algorithms guarantee a flow-based minimum data rate and jointly integrate congestion control, power allocation, routing, and link rate scheduling. Different from traditional algorithms that assume infinite buffers, the proposed algorithms deterministically upper bound the flow-based packet queue length and thus can be employed in multihop networks with finite buffers. In addition, the algorithms achieve a power expenditure/throughput “\epsilon-close” to the optimal value, with a tradeoff of order O(\1/\epsilon) in buffer size. The average end-to-end delay upper bound can also be derived from the finite buffer property. Finally, numerical results are presented to show the performance of the two algorithms with different system parameters. [ABSTRACT FROM PUBLISHER]

Interference alignment (IA) is widely regarded as a promising interference management technique for wireless networks and its potential is most profound in interference-intensive environments. This motivates us to study IA for multicast communications in multihop MIMO networks, which are rich in interference by nature. We develop a set of linear constraints that can characterize a feasible design space of IA for multicast communications. The set of linear constraints constitutes a simple mathematical model of IA that allows us to conduct cross-layer multicast throughput optimization in multihop MIMO networks, but without getting involved into the onerous signal design at the physical layer. Based on the mathematical model of IA, we formulate a multicast throughput maximization problem and develop an approximation solution that can achieve $(1-\varepsilon)$ -optimality. Simulation results show that the use of IA can significantly increase the multicast throughput in multihop MIMO networks and the throughput gain increases with the volume of multicast traffic and the number of antennas. [ABSTRACT FROM AUTHOR]