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The performance of throughput, delay, and their tradeoff in mobile ad hoc networks (MANETs) has been investigated on different assumptions. Nevertheless, few papers consider the supportive infrastructure in MANETs. With the help of supportive infrastructure, i.e., cellular networks, the performance of throughput and delay in MANETs can be improved. The impact of supportive infrastructure on the throughput–delay tradeoff in MANETs is an open research point. In this paper, we are interested in the optimal throughput–delay tradeoff in MANETs with supportive infrastructure. We investigate the supportive infrastructure that only provides transmission pipes between distant nodes. We study the optimal throughput–delay tradeoff in MANETs on different assumptions such as different densities of nodes and base stations (BSs), discrete/continuous mobility models with various velocities, and the fast/slow mobility assumption. We obtain the asymptotically optimal throughput–delay tradeoff and propose transmission policies based on random linear coding (RLC) to achieve the optimal throughput–delay tradeoff asymptotically. From the obtained optimal throughput–delay tradeoff, we find that supportive infrastructure reduces the delay bound from velocity, which is a lower bound of delay caused by nodes' velocity. In particular, if supportive infrastructure can cover the entire network, then the delay bound from velocity vanishes when per-node throughput does not exceed a threshold. Moreover, we find that there also exists a delay bound from the transmission range of the instant transmission. In addition, we observe that, for the optimal throughput–delay tradeoff in the large throughput region, the case in the continuous mobility model outperforms the case in the discrete mobility model, and the case on the slow mobility assumption outperforms the case on the fast mobility assumption. [ABSTRACT FROM PUBLISHER]

In this letter, we propose a novel component carrier on/off scheduling scheme using the learning-based prediction for LTE in the unlicensed spectrum. Particularly, we use Lyapunov optimization to improve the performance of packet throughput and energy consumption, and use Vapnik-Chervonenkis theory to analyze the gap between the predicted optimal value and the practical one. The simulation results show that the proposed scheme can deliver good trade-off between packet throughput and energy consumption by turning off some carrier components, especially when the traffic load is not high. [ABSTRACT FROM PUBLISHER]

This paper studies the beamforming design problem of a multiuser downlink network, assuming imperfect channel state information known to the base station. In this scenario, the base station is equipped with multiple antennas, and each user is wiretapped by a specific eavesdropper where each user or eavesdropper is equipped with one antenna. It is supposed that the base station employs transmit beamforming with a given requirement on sum transmitting power. The objective is to maximize the sum secrecy rate of the network. Due to the uncertainty of the channel, it is difficult to calculate the exact sum secrecy rate of the system. Thus, the maximum of lower bound of sum secrecy rate is considered. The optimization of the lower bound of sum secrecy rate still makes the considered beamforming design problem difficult to handle. To solve this problem, a beamforming design scheme is proposed to transform the original problem into a convex approximation problem, by employing semidefinite relaxation and first-order approximation technique based on Taylor expansion. In addition, with the advantage of low complexity, a zero-forcing-based beamforming method is presented in the case that base station is able to nullify the eavesdroppers’ rate. When the base station does not have the ability, user selection algorithm would be in use. Numerical results show that the former strategy achieves better performance than the latter one, which is mainly due to the ability of optimizing beamforming direction, and both outperform the signal-to-leakage-and-noise ratio-based algorithm. [ABSTRACT FROM PUBLISHER]

In this paper, we study the impact of human mobility on throughput and delay for people-centric applications in mobile ad hoc networks (MANETs). We consider a general human mobility model for MANETs, which can capture important features of human mobility, such as time correlation, node correlation, location heterogeneity, and node heterogeneity. Multiple unicasts with general arrival processes are delivered, and nodes are equipped with infinite buffers. Under our system model, we first characterize the network stability region in terms of the probability of each node set visiting each location and the amount of transmission resources at each location. We show that the node correlation and heterogeneity of locations' popularity usually decrease the size of the network stability region, whereas the diversity of locations visited by a node usually increases the size of the network stability region. Then, by solving a stability-related optimization problem, we develop a throughput-optimal policy based on the obtained optimal solution. We obtain the upper and lower bounds of the delay performance under the proposed policy. Finally, using simulations based on a theoretical model and some real traces, we verify the analytical results and compare the performance of the proposed policy with some existing policies. [ABSTRACT FROM PUBLISHER]

In this paper, we analyze the impact of network coding (NC) configuration on the performance of ad hoc networks with the consideration of two significant factors, namely, the throughput loss and the decoding loss, which are jointly treated as the overhead of NC. In particular, physical-layer NC and random linear NC are adopted in static and mobile ad hoc networks (MANETs), respectively. Furthermore, we characterize the goodput and delay/goodput tradeoff in static networks, which are also analyzed in MANETs for different mobility models (i.e., the random independent and identically distributed (i.i.d.) mobility model and the random walk model) and transmission schemes (i.e., the two-hop relay scheme and the flooding scheme). Moreover, the optimal configuration of NC, which consists of the data size, generation size, and NC Galois field, is derived to optimize the delay/goodput tradeoff and goodput. The theoretical results demonstrate that NC does not bring about order gain on delay/goodput tradeoff for each network model and scheme, except for the flooding scheme in a random i.i.d. mobility model. However, the goodput improvement is exhibited for all the proposed schemes in mobile networks. To our best knowledge, this is the first work to investigate the scaling laws of NC performance and configuration with the consideration of coding overhead in ad hoc networks. [ABSTRACT FROM PUBLISHER]

In this paper, we use the Lyapunov optimization technique to develop scheduling policies for multiradio multichannel cognitive networks to optimize jointly the throughput and the average delay of a secondary network, with limited interference to primary users (PUs)' transmission. In particular, we consider three scenarios, including a static single-hop secondary network, a static multihop secondary network, and a mobile secondary network. For these cases, with the consideration of general mobility and interference models, we design efficient scheduling and channel allocation algorithms based on the concept of Lyapunov drift and give the corresponding performance bound. Furthermore, our theoretical analysis demonstrates that the proposed algorithms can achieve a flexible tradeoff between network throughput and average backlogs by using the Lyapunov optimization technique. Finally, the efficiency of the proposed algorithms is verified by the numerical simulations. [ABSTRACT FROM PUBLISHER]

In this letter, we propose a novel dynamic cell on/off scheduling algorithm in small cell networks based on the Stackelberg game. The objective of the proposed algorithm is to optimize the packet throughput performance with a tradeoff of energy consumption. In our system-level simulations, the proposed algorithm exhibits considerable performance gains, in terms of packet throughput per unit of energy consumption, compared with two existing algorithms respectively based on random on/off and packet arrival-triggered cell activation. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the robust beamforming for multi-user multiple-input single-output systems underquantized channel direction information (CDI) with per-antenna power constraints. The robustness of the consideredbeamforming design is achieved in the sense that the stochastic interference leakage is below a certain level by a givenprobability. Our design objective is to maximize the expectation of the weighted sum-rate performance. From thediscussion of the non-robust optimal beamforming based on the polyblock algorithm, we propose a robust beamformingscheme for the quantized CDI case with per-antenna power constraints. In the proposed beamforming scheme, we useJensen's inequality to generate a tractable feasibility problem for the polyblock algorithm and apply the semi-definiteprogramming relaxation, as well as the randomization technique to find its approximate rank-one matrix solution and userequipments' beamforming vectors. Simulation results show that substantial gains can be achieved by the proposed schemecompared with the existing schemes in terms of the average weighted sum-rate performance. Although very high complexityis required for the implementation of the proposed scheme, it stands as a good benchmark for robust beamformingdesigns. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the robust beamforming schemes for a multi-user multiple-input-single-output (MU-MISO) system with per-antenna power constraints and quantized channel direction information (CDI) feedback. Our design objective is to maximize the expectation of the weighted sum-rate performance by means of controlling the interference leakage and properly allocating the power among user equipments (UEs). First, we prove the optimality of the non-robust zero-forcing (ZF) beamforming scheme in the sense of generating the minimum amount of average inter-UE interference under quantized CDI. Then we derive closed-form expressions of the cumulative density function (CDF) of the interference leakage power for the non-robust ZF beamforming scheme, based on which we adjust the leakage thresholds and propose two robust beamforming schemes under per-antenna power constraints with an iterative process to update the per-UE power allocations using the geometric programming (GP). Simulation results show the superiority of the proposed robust beamforming schemes compared with the existing schemes in terms of the average weighted sum-rate performance. [ABSTRACT FROM AUTHOR]

This paper studies the precoder design of bidirectional networks in which each node is equipped with multiple antennas. In contrast to the conventional model of bidirectional relay networks, this paper considers a more general scenario, i.e., a multi-user multi-relay network. First, by assuming that perfect channel state information (CSI) is available, we investigate the precoding design for the relays and users to minimize the sum mean squared error (MSE) and the maximum of single user's MSE, respectively. Then, we consider a more practical scenario where CSI estimation error is taken into account. By means of alternating optimization approach, we decompose the main problem into several decoupled subproblems with tractable solutions. It is shown that, in both the perfect and imperfect CSI cases, the proposed precoding algorithms outperform the existing solutions in terms of MSE and bit-error-rate (BER) performance. [ABSTRACT FROM AUTHOR]

In this letter, we study relay-aided networks with presence of single eavesdropper. We provide joint beamforming design of the source and relay that can minimize the overall power consumption while satisfying our predefined quality-of-service (QoS) requirements. Additionally, we investigate the case that the channel between relay and eavesdropper suffers from channel uncertainty. Finally, simulation results are provided to verify the effectiveness of our algorithm. [ABSTRACT FROM PUBLISHER]

Green communication receives a growing number of concerns due to the consideration for energy and environment issues. On the other hand, the evolution of mobile and wireless communication also results in heterogeneous Radio Access Technologies (RATs), such as Wi-Fi, UMTS, LTE, CDMA2000 and so on. As a result, energy saving by inter-RAT cooperation has raised significant discussions in both industrial and academical worlds. In this paper, we concentrate on inter-RAT energy saving for multicast services. Moreover, we use Integer Linear Programming to model the problem and propose a distributed algorithm which can efficiently save the energy consumption. [ABSTRACT FROM PUBLISHER]