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Millimeter Wave (mmWave) communications are evolving as a potential and promising technology to address the ever increasing mobile data rate requirements. This paper addresses fair scheduling in directional antenna based mmWave wireless personal and local area networks with non-uniform traffic demand. Due to their small wavelength, mmWave signals are susceptible to blockage. The proposed fair schedulers handle the link blockage problem through relaying, and are capable of providing end-to-end fair bandwidth allocation to relay flows. To achieve differentiated and fair service allocation to various regions of the network while using only limited flow related information, a service tag based scheduler is proposed in this paper. Then, the performance bounds on the minimum throughput and unfairness of this scheduler are obtained. To approximate the performance of the service tag based scheduler while minimizing the control overhead, a heuristic fair scheduler is also proposed. Results from extensive simulations conducted in a mmWave WPAN deployed to support high data rate applications show the performance advantages of the proposed schedulers, compared to existing fair schedulers, in terms of throughput and fairness. [ABSTRACT FROM AUTHOR]

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]

Recently, degree-of-freedom (DoF)-based models have been widely used to study MIMO network performance. Existing DoF-based models differ in their interference cancellation (IC) behavior and many of them suffer from either loss of solution space or possible infeasible solutions. To overcome these limitations, a new DoF-based model, which employs an IC scheme based on node-ordering was proposed. In this paper, we apply this new DoF IC model to study a throughput maximization problem in a multihop MIMO network. The problem formulation involves joint consideration of flow routing and DoF allocation and falls in the form of a mixed-integer linear program (MILP). Our main contribution is an efficient polynomial time algorithm that offers a competitive solution to the MILP through a series of linear programs (LPs). The algorithm employs a sequential fixing framework to obtain an initial feasible solution and then improves the solution by exploiting: 1) the impact of node ordering on DoF consumption for IC at a node and 2) route diversity in the network. Simulation results show that the solutions obtained by our proposed algorithm are competitive and feasible. [ABSTRACT FROM PUBLISHER]

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]

Cellular third—generation wideband code division multiple access (WCDMA) systems must meet interference constraints to maintain coverage when uplink traffic is scheduled. The interference constraints can be expressed in the form of load factor constraints but current scheduling algorithms are typically not formulated in terms of these variables. The current paper shows how a cost function for the scheduling problem can be expressed directly in terms of load factors. A near optimal solution is developed for the resulting problem. [ABSTRACT FROM PUBLISHER]

Recently, a new MIMO degree-of-freedom (DoF) model was proposed to allocate DoF resources for spatial multiplexing (SM) and interference cancellation (IC) in a multi-hop network. Although this DoF model promises many benefits, it hinges upon a global node ordering to keep track of IC responsibilities among all the nodes. An open question about this model is whether its global ordering property can be achieved among the nodes in the network through distributed operations. In this paper, we explore this question by studying DoF scheduling in a multi-hop MIMO network, with the objective of maximizing the minimum throughput among a set of sessions. We propose an efficient DoF scheduling algorithm to solve it and show that our algorithm only requires local operations. We prove that the resulting DoF scheduling solution is globally feasible and show that there exists a corresponding feasible global node ordering for IC, albeit such global ordering is implicit. Simulation results show that the solution values obtained by our algorithm are relatively close to the upper bound values computed by CPLEX solver, thereby indicating that our algorithm is highly competitive. [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]