Throughput Gain Research Articles

A Base Station Agnostic Network Slicing Framework for 5G

The major investment required to roll out new 5G networks has been partially overcome with the definition of a set of migration paths from current 4G deployments to full 5G NR standalone deployments. However, these migration paths, which reduce the time to market of 5G services and the initial investment, result in heterogeneous networks with higher complexity. In this article, we propose a base station agnostic framework for Network Slicing (NetSliC), a new virtualization layer that creates slices taking into account a set of specific constraints per BS. The proposed mechanism is able to effectively deal with these new network architectures by abstracting the complexity of BSs and slicing the network to guarantee the traffic requirements. It is shown that NetSliC can outperform the existing literature. For instance, NetSliC achieves around 67 percent average throughput gain and 16.6 percent baseband unit processing load reduction when compared to baseline scenarios.

Uplink Resource Allocation for Multi-Cluster Internet-of-Things Deployment Underlaying Cellular Networks

Internet-of-Things (IoT) deployment underlaying cellular communication have been drawing increasing attention in recent years. In this work, we consider Device-to-Device (D2D) communication technology for enabling uplink transmission in multiple IoT groups/clusters at which the resource block (RB) of each cellular user is reused by multiple IoT devices (IoTDs). Joint resources and power allocation optimization problem is formulated for maximizing both the IoTDs connectivity and cell throughput under an interference constraint. A heuristic algorithm, namely greedy iterative matching (GIM), is proposed as a sub-optimal solution for the resource allocation problem while a fixed-power margin technique is used for the cellular users’ power allocation. Simulations results show that the proposed GIM algorithm provides enhanced cell throughput gain and accessibility to IoTDs. The proposed reuse model is applicable in a network at which the number of IoTDs deployed within multiple groups is larger than the available cellular reuse partners.

Cross-Entropy Method for Content Placement and User Association in Cache-Enabled Coordinated Ultra-Dense Networks

Due to the high splitting-gain of dense small cells, Ultra-Dense Network (UDN) is regarded as a promising networking technology to achieve high data rate and low latency in 5G mobile communications. In UDNs, each User Equipment (UE) may receive signals from multiple Base Stations (BSs), which impose severe interference in the networks and in turn motivates the possibility of using Coordinated Multi-Point (CoMP) transmissions to further enhance network capacity. In CoMP-based Ultra-Dense Networks, a great challenge is to tradeoff between the gain of network throughput and the worsening backhaul latency. Caching popular files on BSs has been identified as a promising method to reduce the backhaul traffic load. In this paper, we investigated content placement strategies and user association algorithms for the proactive caching ultra dense networks. The problem has been formulated to maximize network throughput of cell edge UEs under the consideration of backhaul load, which is a constrained non-convex combinatorial optimization problem. To decrease the complexity, the problem is decomposed into two suboptimal problems. We first solved the content placement algorithm based on the cross-entropy (CE) method to minimize the backhaul load of the network. Then, a user association algorithm based on the CE method was employed to pursue larger network throughput of cell edge UEs. Simulation were conducted to validate the performance of the proposed cross-entropy based schemes in terms of network throughput and backhaul load. The simulation results show that the proposed cross-entropy based content placement scheme significantly outperform the conventional random and Most Popular Content placement schemes, with with 50% and 20% backhaul load decrease respectively. Furthermore, the proposed cross-entropy based user association scheme can achieve 30% and 23% throughput gain, compared with the conventional N-best, No-CoMP, and Threshold based user association schemes.

Performance and Energy Conservation of 3GPP IFOM Protocol for Dual Connectivity in Heterogeneous LTE–WLAN Network

For the 5th Generation networks, Third Generation Partnership Project (3GPP) is considering standardization of various solutions for traffic aggregation using licensed and unlicensed spectrum, to meet the rising data demands. IP Flow Mobility (IFOM) is a multi-access connectivity solution/protocol standardized by the Internet Engineering Task Force and 3GPP in Release 10. It enables concurrent access for an User Equipment (UE) to Heterogeneous Networks (HetNets) such as Long Term Evolution (LTE) and IEEE 802.11 Wireless Local Area Network (WLAN). IFOM enabled UEs (IeUs) have multiple interfaces to connect to HetNets. They can have concurrent flows with different traffic types over these networks and can seamlessly switch the flows from one network to the other. In this paper, we focus on two objectives. First is to investigate the performance parameters, e.g. throughput, latency, tunnelling overhead, packet loss, energy cost, etc. of IeUs in HetNets of LTE and WLAN. We have proposed a novel mechanism to maximize the throughput of IeUs achieving a significant throughput gain with low latency for the IeUs. We have explored further and observed a throughput-energy trade-off for low data rate flows. To address this, we also propose a smart energy efficient and throughput optimization algorithm for the IeUs, resulting in a substantial reduction in energy cost, while maintaining the high throughput at lower latency and satisfying the Quality of Service requirements of the IeUs.

Network Coding Based Evolutionary Network Formation for Dynamic Wireless Networks

In this paper, we aim to find a robust network formation strategy that can adaptively evolve the network topology against network dynamics in a distributed manner. We consider a network coding deployed wireless ad hoc network where source nodes are connected to terminal nodes with the help of intermediate nodes. We show that mixing operations in network coding can induce packet anonymity that allows the inter-connections in a network to be decoupled. This enables each intermediate node to consider complex network inter-connections as a node-environment interaction such that the Markov decision process (MDP) can be employed at each intermediate node. The optimal policy that can be obtained by solving the MDP provides each node with optimal amount of changes in transmission range given network dynamics (e.g., the number of nodes in the range and channel condition). Hence, the network can be adaptively and optimally evolved by responding to the network dynamics. The proposed strategy is used to maximize long-term utility, which is achieved by considering both current network conditions and future network dynamics. We define the utility of an action to include network throughput gain and the cost of transmission power. We show that the resulting network of the proposed strategy eventually converges to stationary networks, which maintain the states of the nodes. Moreover, we propose to determine initial transmission ranges and initial network topology that can expedite the convergence of the proposed algorithm. Our simulation results confirm that the proposed strategy builds a network which adaptively changes its topology in the presence of network dynamics. Moreover, the proposed strategy outperforms existing strategies in terms of system goodput and successful connectivity ratio.

UAV-Relaying-Assisted Secure Transmission With Caching

Unmanned aerial vehicle (UAV) can be utilized as a relay to connect nodes with long distance, which can achieve significant throughput gain owing to its mobility and line-of-sight (LoS) channel with ground nodes. However, such LoS channels make UAV transmission easy to eavesdrop. In this paper, we propose a novel scheme to guarantee the security of UAV-relayed wireless networks with caching via jointly optimizing the UAV trajectory and time scheduling. For every two users that have cached the required file for the other, the UAV broadcasts the files together to these two users, and the eavesdropping can be disrupted. For the users without caching, we maximize their minimum average secrecy rate by jointly optimizing the trajectory and scheduling, with the secrecy rate of the caching users satisfied. The corresponding optimization problem is difficult to solve due to its non-convexity, and we propose an iterative algorithm via successive convex optimization to solve it approximately. Furthermore, we also consider a benchmark scheme in which we maximize the minimum average secrecy rate among all users by jointly optimizing the UAV trajectory and time scheduling when no user has the caching ability. Simulation results are provided to show the effectiveness and efficiency of our proposed scheme.

Monostatic Antenna In-Band Full Duplex Radio: Performance Limits and Characterization

This paper presents an in-band full duplex (IBFD) architecture, comprised of a monostatic antenna and software defined radio (SDR) implementing digital self-interference cancellation (DSIC). For this architecture, three alternative monostatic antennas with high passive suppression are integrated with a least squares linear DSIC algorithm implemented on the WARP v3 orthogonal frequency-division multiplexing based IEEE 802.11 SDR. Via detailed laboratory tests, the performance of the proposed IBFD radio architecture is investigated, considering various indoor positions and orientations for each antenna. The measurement results have been utilized to devise an analytical model for characterizing the power of the residual self-interference in the monostatic antenna IBFD radio as a function of transmit power levels. It is shown that the monostatic IBFD architecture can achieve up to almost 99 dB total cancellation, enabling medium range full duplex communication with moderate transmit power levels. Bidirectional communication is demonstrated between the two IBFD nodes with the proposed architecture, and error vector magnitude is observed as a function of increasing transmit power, i.e., SI. The throughput gain of full-duplex communication over half-duplex communication is also calculated as a function of payload size and the gain is found to be close to two for the settings used in the experiments.

Random Access: Packet-Based or Connection-Based?

Different from the conventional packet-based random access schemes where each data packet needs to contend for channel access, with connection-based random access, a connection is first established before data packet transmission. Despite the consensus that there exists a critical threshold of the data packet transmission time, only above which establishing a connection is beneficial, characterization of such a threshold has received little attention. In this paper, a comparative study will be presented on the optimal throughput performance of the packet-based random access and the connection-based random access to characterize criteria for beneficial connection establishment. Based on a unified channel-centric model, explicit expressions of the maximum effective throughput are obtained for both packet-based and connection-based Aloha and Carrier Sense Multiple Access (CSMA). The analysis shows that whether connection establishment is beneficial crucially depends on the sensing capability of nodes. The threshold of data packet transmission time with Aloha is found to be much lower than that with CSMA, indicating that the throughput gain brought by connection establishment is more significant when sensing is absent. The analysis sheds important light on the access design of machine-to-machine (M2M) communications.

An Interference-Aware Rate and Channel Adaptation Scheme for Dense IEEE 802.11n Networks

Rate adaptation, which dynamically chooses transmission rate provided at the physical layer according to the current channel conditions, is a fundamental resource management issue in IEEE 802.11 networks with the goal of maximizing the network throughput. Traditional rate adaptation algorithms for IEEE 802.11n networks do not consider the interference problem, which becomes much more serious due to the rapid deployment of IEEE 802.11n devices and large number of mobile terminals. In this paper, an interference-aware rate and channel adaptation scheme RaCA for intensive IEEE 802.11n networks was proposed. Firstly, RaCA leverages RSSI and CSI information together to measure the current channel conditions at the receiver side. RSSI is a coarse-grained indicator and CSI is a fine-grained indicator. Secondly, a two-stage rate adaptation scheme TSRA was designed, which can quickly adapt to optimal bit rate based on RSSI and CSI information. Finally, a quorum-based channel adaptation algorithm QCA was proposed, which does not need control channel. If channel suffers severe interferences, RaCA calls QCA to choose another channel to work on. Simulation and testbed implementation results demonstrate that RaCA achieves significant throughput gain over SampleLite and Minstrel-HT.

Optimal Resource Allocation in Full-Duplex Ambient Backscatter Communication Networks for Wireless-Powered IoT

This paper considers an ambient backscatter communication network in which a full-duplex access point (FAP) simultaneously transmits downlink orthogonal frequency division multiplexing signals to its legacy user (LU) and receives uplink signals backscattered from multiple backscatter devices (BDs) in a time-division-multiple-access manner. To maximize the system throughput and ensure fairness, we aim to maximize the minimum throughput among all BDs by jointly optimizing the backscatter time and reflection coefficients of the BDs, and the FAP’s subcarrier power allocation, subject to the LU’s throughput constraint, the BDs’ harvested-energy constraints, and other practical constraints. For the case with a single BD, we obtain closed-form solutions and propose an efficient algorithm by using the Lagrange duality method. For the general case with multiple BDs, we propose an iterative algorithm by leveraging the block coordinated decent and successive convex optimization techniques. In addition, we study the throughput region which characterizes the Pareto-optimal throughput tradeoffs among all BDs. Finally, extensive simulation results show that the proposed joint design achieves significant throughput gain as compared to the benchmark schemes.

Constant envelope precoding in multi-cell massive MIMO systems with channel uncertainty

In this paper, the downlink transmission of a multi-cell massive multiple input multiple output (MIMO) system is studied, in which constant envelope precoding (CEP) is utilized for the precoding operation. The single-cell realization of CEP is presented in the literature in case exact CSI is at hand. In this work we aim to extend this structure to a multi-cell scenario with noisy CSI available to the base stations (BS). To this end, first of all, a fully cooperative cellular structure is presented, and then, an effort is made to mitigate the overhead by proposing a limited cooperation setting where the amount of the exchanged CSI among the cells is significantly decreased. Finally, by suggesting a distributed realization of the system, the overhead is diminished to its lowest value. Furthermore, it is attempted to analyze the system performance in case of having a noisy CSI and to compensate for this effect in the proposed schemes. Numerical results demonstrate that by reduction of the overhead in the limited cooperation and the distributed structures compared to the fully cooperative one, the performance faces merely a negligible drop, which compared to the throughput gain, seems entirely worth the cost.

Performance centric design of subnetwork-based diagonal mesh NoC

ABSTRACTPerformance of NoC relies heavily on underlying interconnect network and related message forwarding technique. Here, Mesh is an obvious network choice by the designer due to its regular grid-based structure, making it easy to implement in chip surface. However, mesh suffers from degrading network performance issue in large-scale dimension due to the increasing hop count that leads to both congestion and link contention at the same time. Conventional topologies like Folded Torus, Butterfly-fat-tree (BFT) and recently proposed topologies like Flattened BFT, Sc-mesh and SD2D mesh topologies are mostly relying on express bypass links to mitigate this limitation in large-scale dimension. Proposed work presents a low latency oriented diagonally linked network that combines both 2 × 2 and a 1 × 1 diagonal links over the generic mesh connection to shorten the network diameter rendering chip designers more flexibility in regulating important performances centric design trade-offs such as packet delay, throughput and network energy while employing a low area overhead (~7%). Experimental results over 8 × 8 and 12 × 12 sized network show 8–11%, 18–66% and 60–66% lower packet delay while gain in throughput raises to 15–17%, 29–64% and 46–58% compared to 2-hop Dia-mesh (2x2 diagonal), Sc-mesh (1x1 diagonal) and conventional mesh topologies, respectively, under uniformly distributed traffic.

Centralized UL/DL Resource Allocation for Flexible TDD Systems With Interference Cancellation

Flexible time division duplex (TDD) is expected to be one of the key technologies for 5G flexible air interface. The main benefit of flexible TDD is to allow for better radio resource utilization based on instantaneous user traffic demands. To boost network capacity, one could thus, utilize flexible TDD along with a dense deployment of small cells. Flexible TDD systems can be designed to benefit from strong-interference cancellation of the cross-link interference along with advanced inter-cell coordination. In this paper, we propose a centralized coordination scheme with joint uplink/downlink (UL/DL) user scheduling, rate, and MIMO rank adaptation. To reduce the complexity of coordinated scheduling, we propose a cluster-based scheduling scheme where joint UL/DL selection and joint user scheduling are performed within a cluster. MIMO rank and rate adaptation are performed across the clusters using inter-cluster rate and rank adaptation. Simulation based results are evaluated in an outdoor urban micro scenario with bursty traffic and assuming realistic channel estimation. It is observed that the proposed flexible TDD scheme with joint UL/DL scheduling, interference cancellation, and coordination provides over 120% gain in the fifth percentile and over 29% gain in the average end-to-end UL throughput as compared to flexible TDD standalone scheduling without coordination. Our results show that successive interference cancellation receivers provide over 20% UL throughput gain for flexible TDD systems as compared to Interference Rejection Combining (IRC) receivers. We also find that fully flexible TDD with interference cancellation significantly outperforms fully synchronized TDD for different cell sizes.

Trajectories and Resource Management of Flying Base Stations for C-V2X.

In a vehicular scenario where the penetration of cars equipped with wireless communication devices is far from 100% and application requirements tend to be challenging for a cellular network not specifically planned for it, the use of unmanned aerial vehicles (UAVs), carrying mobile base stations, becomes an interesting option. In this article, we consider a cellular-vehicle-to-anything (C-V2X) application and we propose the integration of an aerial and a terrestrial component of the network, to fill the potential unavailability of short-range connections among vehicles and address unpredictable traffic distribution in space and time. In particular, we envision a UAV with C-V2X equipment providing service for the extended sensing application, and we propose a UAV trajectory design accounting for the radio resource (RR) assignment. The system is tested considering a realistic scenario by varying the RRs availability and the number of active vehicles. Simulations show the results in terms of gain in throughput and percentage of served users, with respect to the case in which the UAV is not present.

Multiconnectivity in Multicellular, Multiuser Systems: A Matching- Based Approach

Wireless communication systems have been evolving since the first generation. With the fifth generation of wireless systems, not only the evolutionary aspect of increased data rates is tackled but also the revolutionary aspect. Here, emerging use cases such as massive machine-type communication and ultrareliable low-latency communication will play a crucial role. Within this context, applications with stringent latency and reliability requirements are emerging. Wireless reliability is understood as successfully transmitting the desired amount of data within a given time. Diversity techniques, such as multiconnectivity, are potential solutions to achieve stringent reliability requirements. However, in a multiuser scenario, in which resources are shared, this might not always be possible. In this paper, we discuss the feasibility of various multiconnectivity approaches and propose a matching theory-based algorithm together with a novel scheduler aiming to guarantee the reliability requirements of as many users as possible in a multicellular, multiuser system. System-level simulations demonstrate that the proposed approach achieves 100% reliability for the fifth-percentile users in a highly loaded system. The maximum gain of fifth-percentile user throughput as compared to a static multiconnectivity approach is 150%.

Throughput Region of Spatially Correlated Interference Packet Networks

In multi-user wireless packet networks, interference, typically modeled as packet collision, is the throughput bottleneck. Users become aware of the interference pattern via feedback and use this information for contention resolution and packet retransmission. Conventional random access protocols interrupt communication to resolve contention, which reduces network throughput and increases latency and power consumption. In this paper, we take a different approach, and we develop opportunistic random access protocols rather than pursuing conventional methods. We allow wireless nodes to communicate without interruption and to observe the interference pattern. We then use this interference pattern knowledge and channel statistics to counter the negative impact of interference. We prove the optimality of our protocols using an extremal rank-ratio inequality. An important part of our contributions is the integration of spatial correlation in our assumptions and results. We identify spatial correlation regimes in which inherently outdated feedback becomes as good as idealized instantaneous feedback and correlation regimes in which feedback does not provide any throughput gain. To better illustrate the results, and as an intermediate step, we characterize the capacity region of finite-field spatially correlated interference channels with delayed channel state information at the transmitters.

Optimal Multipath TCP Offloading Over 5G NR and LTE Networks

Multipath TCP (MPTCP) is one of the key technologies that can improve the throughput performance by exploiting multiple path communications. This letter proposes an offloading by restriction (OBR) scheme to enhance the throughput by offloading data traffic optimally when fifth generation (5G) new radio (NR) and LTE communication paths are aggregated. The proposed OBR scheme also considers interaction with MPTCP congestion control and scheduling algorithms, thus can be added without modification to MPTCP. Simulation results show that the proposed OBR scheme can provide a significant throughput gain compared to the MPTCP control scheme linked increases algorithm and multipath offloading scheme multipath offloading algorithm.

3D UAV placement and user association in software-defined cellular networks

With the onset of unexpected or temporary problems resulting in degraded user performance, the flexibility and elasticity requirements of future cellular networks may not be fully satisfied by fixed ground base stations. A promising solution for this deficiency is to establish drone cells, which are formed by quickly deploying unmanned aerial vehicles (UAVs) equipped with base stations. Consequently, a UAV placement and user association algorithm for future software-defined cellular networks (SDCN) is proposed in this study. In consideration of the optimal three-dimensional placement of UAVs and the optimal drone cell users’ associations, a utility maximization problem is formulated by utilizing a global view of the SDCN controller. Following mathematical manipulation, the intractable multidimensional problem is transformed into a two-phase algorithm involving the optimal UAV placement altitude-to-radius ratio and the optimal two-dimensional (2D) drone cell horizontal coverage combined with user association. Simulation results indicate the superiority of the proposed algorithm, which increases the average throughput and average utility of all users compared with random, center and 2D UAV placement schemes. By deploying the new design, the maximum average throughput gain can reach up to $$36.4\%$$ .

On Throughput Maximization in Cooperative Cognitive Radio Networks With Eavesdropping

In this letter, a cooperative cognitive radio network, in presence of an eavesdropper, is considered that operates in a frame structure comprising of energy harvesting, spectrum sensing and cooperation or opportunistic data transmission. The objective is to maximize the sum secondary throughput under the constraints of sensing reliability, harvesting energy causality, primary user cooperation data rate, secondary data outage, sum and individual secondary secrecy outage. Results show a gain in sum throughput ~25.43% over the existing work.

Reverse Cooperatively Routed Wi-Fi Direct in the Advent of 5G Driven Designs

In this article, the instantiation of the logic behind the so-called “Multi-Connect” mode of Wi-Fi Direct is advocated for and prescribed in order to make it possible to increase, if not multiply, the data throughput attainable by a given P2P Device thanks to traffic aggregation. In general, the described extension to the existing standard, defined by the Wi-Fi Peer-to-Peer (P2P) Technical Specification, enables the reversal of the logical roles of a P2P Group Owner (P2P GO) and its respective P2P Clients, while ensuring that the general architectural framework of Wi-Fi Direct should remain unchanged for backward compatibility reasons. This is achieved with the aid of a number of specifically tailored modifications including: new P2P Attribute allocation, extended Group Owner determination, modified P2P State Machine operation, enhanced Concurrent and Non-Concurrent operation, as well as expanded Reverse Operation Logic definition. The concept is illustrated with and verified through the analysis of cumulative virtual channel capacity and, therefore, the expected data throughput gain.