Control Channel Overhead Research Articles

Uplink-downlink resource optimization for provisioning 5G application considering SUI fading channel models

Recently, superposition coding (SC), Stanford University Interim (SUI) fading channel, user clustering, successive interference cancellation (SIC) mechanism has been incorporated into the power allocation design for attaining good performance. Nonetheless, the existing model works with cluster size up to 4 user per cluster and induce higher control channel overhead. In addressing this paper introduce an effective resource allocation (ERA) design for power domain non-orthogonal multiple access (PD-NOMA) system. The ERA, first employ Zadoff Chu (ZC) coding, then power is allocated according to the distance considering 5 user per cluster. Finally, multi-level SIC is done at the receiver end. The ERA performance is studied by varying signal-to-noise ratio (SNR) in terms of bit error rate (BER) considering a maximum of five users per cluster. Further, the ERA performance in terms of BER is tested under different scenario defined in SUI propagation scenario such as higher pathloss, moderate path loss, and low path loss. The throughput performance under varied density and speed is also studied; the ERA achieves much better performance in terms of ERA, SNR and throughput than standard multi-user downlink resource allocation (MUDRA) model.

Adaptive traffic aware clustering and routing model for wireless sensor networks

<span>Designing effective clustering algorithms plays a very important role in improving network lifetime target coverage (NLTC) in heterogeneous wireless sensor networks (HWSNs). However, the current clustering mechanism failed to address hotspot problem resulting in poor coverage and network lifetime performance. Recently, unequal clustering has been used for addressing hotspot problem in HWSNs. However, when performing inter-cluster routing, load balancing is not efficient and the energy degradation is high, which affects the overall network performance. This work introduces an effective model namely adaptive traffic aware clustering and routing (ATACR) model to address hotspot and load balancing issues. The ATACR introduces a novel unequal clustering and ideal distribution of load in different cluster levels. The ATACR model improves network lifetime, reduces control channel overhead, and attains better throughput in comparison with existing routing models.</span>

HH-IPG: Leveraging Inter-Packet Gap Metrics in P4 Hardware for Heavy Hitter Detection

The research community has recently proposed several solutions based on modern programmable switches to detect entirely in the data plane the flows exceeding pre-determined thra eshold in a time window, i.e., Heavy Hitters (HH). This is commonly achieved by dividing the network stream into fixed time slots and identifying each separately without considering the traffic trends from previous intervals. In this work, we show that using specified time windows can lead to high inaccuracies. We make a case for rethinking how switches analyze the incoming packets and propose to leverage per-flow Inter Packet Gap (IPG) analytics instead of using flow counters for HH detection. We propose an algorithm and present a P4 pipeline design using this new metric in mind. We implement our solution on P4 hardware and experimentally evaluate it against real traffic traces. We show that our results are more accurate than related work by up to 20% while reducing the control channel overhead by up to two orders of magnitude. Finally, we showcase a QoS-oriented application of the proposed dataplane-only IPG-based HH detection in a mobile network scenario.

On the Cost of Achieving Downlink Ultra-Reliable Low-Latency Communications in 5G Networks

We determine the cost of serving Ultra-Reliable Low-Latency Communications (URLLC) traffic (1 ms one-way latency, 99.999% reliability) in 5G New Radio (NR) Macro cellular networks. The cost is measured as the degradation of the enhanced Mobile Broadband (eMBB) downlink system capacity when serving a certain offered load of URLLC traffic on the same radio carrier. A methodology for assessing the cost of URLLC is presented, which takes into account all the aspects related to configuring a suitable resource allocation and link adaptation strategy, as well as the associated control channel overhead due to the use of mini-slots with very frequent control channel resources for monitoring downlink data assignments. When taking a holistic view on the performance, advanced system-level simulation results show that 1 Mbps of URLLC traffic results in an eMBB throughput reduction of up to 60 Mbps, i.e. URLLC traffic can be up to 60 times more costly than traditional best-effort. The presented results can be used by cellular service providers, such as operators, for understanding and dimensioning the tradeoffs and impact towards traditional network services when adding URLLC services to their portfolio.

IPro: An approach for intelligent SDN monitoring

Traffic Monitoring assists in achieving network stability by observing and quantifying its behavior. A proper traffic monitoring solution requires the accurate and timely collection of flow statistics. Many approaches have been proposed to monitor Software-Defined Networks. However, these approaches have some disadvantages. First, they are unconcerned about the trade-off between probing interval and Monitoring Accuracy (MA). Second, they lack intelligent mechanisms intended to optimize this trade-off by learning from network behavior. This paper introduces an approach, called IPro, to address these shortcomings. Our approach comprises an architecture based on the Knowledge-Defined Networking paradigm, an algorithm based on Reinforcement Learning, and an IPro prototype. In particular, IPro uses Reinforcement Learning to determine the probing interval that keeps Control Channel Overhead (CCO) and the Extra CPU Usage of the Controller (CUC) within thresholds. An extensive quantitative evaluation corroborates that IPro is an efficient approach for SDN Monitoring regarding CCO, CCU, and MA.

Non-uniform Quantized Data Fusion Rule for Data Rate Saving and Reducing Control Channel Overhead for Cooperative Spectrum Sensing in Cognitive Radio Networks

In this paper a pretty new concept of non-uniform quantized data fusion (N-QDF) rule reducing control channel data overhead has been proposed for energy detection based cooperative spectrum sensing scheme in cognitive radio networks. To strike a balance between efficient detection performance and less complexity, the network has to allow soften hard or quantized data fusion (QDF) technique though this technique incurs few bit overhead on the control channel from each user. Again lower bit QDF causes loss of more information, where as higher bit QDF increases detection probability at the cost of some extra bits per user. Here lies the beauty of NQDF scheme which uses variable number of bits: more number of bits for lower energy region—thus increases detection probability for a given false alarm, and less number of bits for higher energy region—thus data rate gets saved which in turn alleviates control channel overhead. A holistic simulation study has been done in this very paper where the performance of variable bit NQDF scheme is compared with different uniform bit i.e. 2, 3, 4, 5 QDF with respect to different parameters to validate our proposed scheme.

A Quantization-Based Multibit Data Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks.

Spectrum sensing remains a challenge in the context of cognitive radio networks (CRNs). Compared with traditional single-user sensing, cooperative spectrum sensing (CSS) exploits multiuser diversity to overcome channel fading, shadowing, and hidden terminal problems, which can effectively enhance the sensing performance and protect licensed users from harmful interference. However, for a large number of sensing nodes that need high bandwidth of the control channel for data transmitting, CSS increases cooperative overhead. To address this problem, we investigated the soft decision fusion strategy under a limited bandwidth of the control channel and proposed a simple quantization-based multibit data soft fusion rule for CSS for its simple structure and easily implementation. Under the quantization-based sensing strategy, each cooperative secondary user (SU) adopts an energy detector for local spectrum sensing. Each SU transmits quantized multibit data that sends local sensing information, instead of forwarding local one-bit hard decision results or original observation statistics, to the fusion center (FC). Furthermore, the closed-form expressions of the quantization levels and the quantization thresholds are analytically derived. Simulation results indicate that the detection performance of the proposed method approaches that of the conventional soft fusion rule with less cooperative overhead and outperforms the hard decision rules. Extensive simulations also show that multibit quantization fusion achieves a desirable tradeoff between the sensing performance and the control channel overhead for CSS.

Transmit Power Optimization for Amplify-and-Forward Relay Networks With Reduced Overheads

Transmit power optimization or power control plays an important role in implementing wireless relay networks since it can significantly improve system performance, such as transmission rate, power consumption, etc. However, power optimization introduces considerable control channel overheads due to exchanging channel state information (CSI) and optimization results. In this paper, we aim to design a new power optimization scheme to reduce overheads while avoiding a large performance loss. We consider a typical three-node amplify-and-forward relay network consisting of a source, a relay, and a destination. The power of source and that of relay are optimized to minimize the total power consumption under the constraint of a minimum transmission rate or nonviolation probability. We first define and analyze two schemes based on traditional routines, which are called Strategies I and II. In Strategy I, transmit power of both source and relay is optimized based on instantaneous CSI, whereas in Strategy II, transmit power is based on statistical CSI. We then propose a new partial CSI strategy, which is called Strategy III, where source power is based on statistical CSI, whereas relay power is based on instantaneous CSI. Strategy III is formulated and solved by the two-stage stochastic programming method. With this new strategy, the control channel overhead can be reduced by 50% compared with Strategy I, and at the same time, the potential significant performance degradation as in Strategy II can be avoided. Simulation results show that the proposed strategy results in near-optimal performance when the relay is located close to the source.

Macro-assisted data-only carrier for 5G green cellular systems

As the commercial operation of 4G systems is speeding up worldwide to meet the increasingly explosive growth of mobile Internet in the 2020 era, a great many R&D efforts targeting the next generation wireless systems (5G) have been launched. With densely deployed small cells in a heterogeneous network, the excessive signaling overhead of conventional carrier design greatly degrades system performance. A new carrier designed for small cells in the next generation system will be highly beneficial toward a green communication network. In this article, we propose a macro-assisted data-only carrier for future 5G networks from a green prospective. With the help of macro base stations, control channel overhead, and cell-specific reference signals for small cells can be minimized to achieve a pure-data carrier. Under this architecture, key procedures are designed including small cell identification and access, synchronization, hand over, and small cell sleeping. Furthermore, to evaluate the potential of our proposed scheme, a complete system and link-level simulation platform according to the current 3GPP LTE standard is built. The simulation results show that our proposed systems, achieving significant performance enhancement of signaling overhead, can lead to more than 17 percent throughput improvement and 90 percent energy efficiency gain over the current LTE HetNet with on-off strategy implemented. The proposed scheme appears to be highly attractive as part of the future 5G green mobile networks.

인지 무선 애드혹 네트워크에서 경로 신뢰성을 고려한 효율적인 라우팅 기법

인지무선 애드혹 네트워크(Cognitive Radio Ad-hoc Networks)에서 요구기반 라우팅을 수행할 경우, 경로 탐색 과정에서 발생하는 경로탐색 메시지의 브로드캐스팅은 공통 제어 채널의 과부하를 유발하고 패킷 간의 충돌을 발생시킨다. 이런 현상은 경로탐색의 오버헤드를 증가 시키며, 정확하고 신뢰성있는 경로의 탐색에 제한을 받게 된다. 이로 인하여 신뢰성있는 채널을 찾는 경로가 제한되기 때문에 경로의 생존 시간이 단축되고 경로의 안정성이 감소된다. 본 논문에서는 인지무선 ad-hoc네트워크에서 주사용자의 출현 가능성과 주변 사용자의 상황을 고려하여 패킷 충돌을 감소시키고 경로의 생존시간을 향상 시키는 라우팅 알고리즘을 제안한다. 각 노드는 주기적인 센싱을 통해 주사용자의 사용패턴을 감지하고 채널의 사용 확률과 현재 채널 상태를 알고 있다. 또한 이웃 노드와 메시지 교환을 통해 공통된 채널과 해당 채널의 품질을 파악하여 노드 사이에 링크 레벨을 부여한다. 제안된 방법에서는 링크 레벨을 이용하여 경로 탐색 과정에서 발생하는 제어 메시지의 수를 감소시킨다. 또한 링크의 생존성과 품질을 홉 카운트에 따라 가중치를 부여하여 경로를 선택함으로써 경로의 생존 시간을 향상 시킬 수 있다. 성능 평가를 통해 기존의 방법 보다 제안된 방법을 이용하여 라우팅을 수행할 경우 제어 채널의 오버헤드가 감소되고 경로의 생존시간이 증가하는 것을 확인 할 수 있다. In the case of On-demand routing protocol in cognitive radio ad-hoc networks, broadcasting of control packets may occur common control channel overload and packet collisions during the routing procedure. This situation is to increase the overhead of path finding and also limited to find the accurate and reliable path. Since reliable channel and path finding is restricted, path life time is shorten and path reliability is reduced. In this paper, we propose a new routing algorithm that reduces control channel overhead and increases path life time by considering the probability of appearance of primary user and channel status of neighbor nodes. Each node performs periodic local sensing to detect primary user signal and to derive primary user activity patterns. The probability of primary appearance on the current channel and the channel status can be obtained based on the periodic sensing. In addition, each node identifies the quality of the channel by message exchange through a common channel with neighbor nodes, then determines Link_Levels with neighbor nodes. In the proposed method, the Link Level condition reduces the number of control messages that are generated during the route discovery process. The proposed method can improve path life time by choosing a path through Path_Reliability in which stability and quality are weighted depending on the location. Through simulation, we show that our proposed algorithm reduces packet collisions and increases path life time in comparison with the traditional algorithm.

The Study on Peak Throughput of TD-LTE

Based on the analysis of the physical channel and frame structure of TD-LTE system, considering the influence of control channel overhead and uplink-downlink configuration, two estimating methods of the TD-LTE peak throughput are analyzed, which have positive preference value for network planning.

A Lean Carrier for LTE

The next major step in the evolution of LTE targets the rapidly increasing demand for mobile broadband services and traffic volumes. One of the key technologies is a new carrier type, referred to in this article as a Lean Carrier, an LTE carrier with minimized control channel overhead and cell-specific reference signals. The Lean Carrier can enhance spectral efficiency, increase spectrum flexibility, and reduce energy consumption. This article provides an overview of the motivations and main use cases of the Lean Carrier. Technical challenges are highlighted, and design options are discussed; finally, a performance evaluation quantifies the benefits of the Lean Carrier.

Resource allocation for energy efficient cellular systems

The need for more throughput in wireless cellular networks has been increasing in recent years. It has led to an increase in operational costs due to higher energy use as operators deploy more cell sites or increase transmission power at existing ones to satisfy demand. Energy costs are a major expense, and reducing them is a priority. This article presents a scheduler which aims to solve the problem of energy efficient resource allocation in orthogonal frequency division multiple access (OFDMA) cellular systems. The suggested approach is to make the resource scheduling process also consider energy costs as well as allow it to manipulate these by exploiting time/frequency vs energy efficiency trade-offs that are present in the system. The energy efficient score-based scheduler (EESBS) is a novel scheduler which takes energy costs into account when allocating resource blocks (RBs) to users. This allows it to promote energy efficiency in the system alongside throughput and fairness maximization. One of the means it has to manipulate users' expended energy is the bandwidth expanded mode (BEM). BEM is a technique that allows the scheduler to decrease a user's energy consumption by allocating it more RBs and maintaining a constant data rate. This is possible when the energy consumption is dominated by the energy used for data communication as opposed to control channel overhead transmission. Time compression mode (TCoM) is a technique that is complementary to BEM. It allows for energy savings through a reduction of the number of allocated RBs to a user when the energy consumption is dominated by the transmission of signaling traffic. Both BEM and TCoM need to be employed by an energy-aware scheduler like EESBS in order to extract the maximum performance gains. A realistic framework modeling future cellular systems is established to test the performance of the proposed techniques. Within this framework, EESBS generates an average energy saving of 29% over a frequency selective proportional fair (FsPF) benchmark. EESBS coupled with BEM or TCoM achieves a saving of 38% over the same benchmark. These savings are achieved with no detriment to user satisfaction in terms of achieved data rate.

The Effect of On-Off Scheduling to the Required Transmit Power in Systems with Fast Power Control

Physical layer channel-aware scheduling may significantly improve coverage and throughput of IP based services in wireless cellular networks, and the feasibility of such schedulers is actively studied within 3G and 4G systems. A channel-aware scheduler requires access to instantaneous channel state information in order to direct transmission to users with favorable channel conditions. In frequency division duplex (FDD) systems, this requires a fast feedback channel between mobile and base stations, and the overhead of the feedback control channel should be kept as low as possible. In this paper, we study the effect of control channel overhead to on-off scheduling (OOS) when fast transmit power control is applied in data and control channels. On-off scheduling is a simple channel-aware scheduling algorithm, where transmission to a user is suspended if the transmit power exceeds a given threshold. On-off scheduling is applied on the data channel while control channel is always on so that the scheduler is able to obtain channel state information from active users. The gain of OOS strongly depends on the power ratio between control and data channels, and increased interference due to control signaling and decreased interference due to channel-aware scheduling should be jointly considered in system design. Gains in the required transmit power are translated into gains in coverage and capacity assuming WCDMA parameters, and the results can be applied, e.g., when designing scheduling algorithms and corresponding signaling formats for WCDMA uplink.