arXiv subjects

Nurul Huda Mahmood

Publications and source records attributed to Nurul Huda Mahmood.

50 records · Page 3Linked to original sources

arXiv2021

A Nonlinear Autoregressive Neural Network for Interference Prediction and Resource Allocation in URLLC Scenarios

Ultra reliable low latency communications (URLLC) is a new service class introduced in 5G which is characterized by strict reliability $(1-10^{-5})$ and low latency requirements (1 ms). To meet these requisites, several strategies like overprovisioning of resources and channel-predictive algorithms have been developed. This paper describes the application of a Nonlinear Autoregressive Neural Network (NARNN) as a novel approach to forecast interference levels in a wireless system for the purpose of efficient resource allocation. Accurate interference forecasts also grant the possibility of meeting specific outage probability requirements in URLLC scenarios. Performance of this proposal is evaluated upon the basis of NARNN predictions accuracy and system resource usage. Our proposed approach achieved a promising mean absolute percentage error of 7.8 % on interference predictions and also reduced the resource usage in up to 15 % when compared to a recently proposed interference prediction algorithm.

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arXiv2021

Average Rate and Error Probability Analysis in Short Packet Communications over RIS-aided URLLC Systems

In this paper, the average achievable rate and error probability of a reconfigurable intelligent surface (RIS) aided systems is investigated for the finite blocklength (FBL) regime. The performance loss due to the presence of phase errors arising from limited quantization levels as well as hardware impairments at the RIS elements is also discussed. First, the composite channel containing the direct path plus the product of reflected channels through the RIS is characterized. Then, the distribution of the received signal-to-noise ratio (SNR) is matched to a Gamma random variable whose parameters depend on the total number of RIS elements, phase errors and the channels' path loss. Next, by considering the FBL regime, the achievable rate expression and error probability are identified and the corresponding average rate and average error probability are elaborated based on the proposed SNR distribution. Furthermore, the impact of the presence of phase error due to either limited quantization levels or hardware impairments on the average rate and error probability is discussed. The numerical results show that Monte Carlo simulations conform to matched Gamma distribution to received SNR for sufficiently large number of RIS elements. In addition, the system reliability indicated by the tightness of the SNR distribution increases when RIS is leveraged particularly when only the reflected channel exists. This highlights the advantages of RIS-aided communications for ultra-reliable and low-latency systems. The difference between Shannon capacity and achievable rate in FBL regime is also discussed. Additionally, the required number of RIS elements to achieve a desired error probability in the FBL regime will be significantly reduced when the phase shifts are performed without error.

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arXiv2021

Deep Neural Network-Based Blind Multiple User Detection for Grant-free Multi-User Shared Access

Multi-user shared access (MUSA) is introduced as advanced code domain non-orthogonal complex spreading sequences to support a massive number of machine-type communications (MTC) devices. In this paper, we propose a novel deep neural network (DNN)-based multiple user detection (MUD) for grant-free MUSA systems. The DNN-based MUD model determines the structure of the sensing matrix, randomly distributed noise, and inter-device interference during the training phase of the model by several hidden nodes, neuron activation units, and a fit loss function. The thoroughly learned DNN model is capable of distinguishing the active devices of the received signal without any a priori knowledge of the device sparsity level and the channel state information. Our numerical evaluation shows that with a higher percentage of active devices, the DNN-MUD achieves a significantly increased probability of detection compared to the conventional approaches.

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arXiv2021

Deep Learning-Based Active User Detection for Grant-free SCMA Systems

Grant-free random access and uplink non-orthogonal multiple access (NOMA) have been introduced to reduce transmission latency and signaling overhead in massive machine-type communication (mMTC). In this paper, we propose two novel group-based deep neural network active user detection (AUD) schemes for the grant-free sparse code multiple access (SCMA) system in mMTC uplink framework. The proposed AUD schemes learn the nonlinear mapping, i.e., multi-dimensional codebook structure and the channel characteristic. This is accomplished through the received signal which incorporates the sparse structure of device activity with the training dataset. Moreover, the offline pre-trained model is able to detect the active devices without any channel state information and prior knowledge of the device sparsity level. Simulation results show that with several active devices, the proposed schemes obtain more than twice the probability of detection compared to the conventional AUD schemes over the signal to noise ratio range of interest.

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arXiv2021

Average Rate Analysis of RIS-aided Short Packet Communication in URLLC Systems

In this paper, the average achievable rate of a re-configurable intelligent surface (RIS) aided factory automation is investigated in finite blocklength (FBL) regime. First, the composite channel containing the direct path plus the product of reflected paths through the RIS is characterized. Then, the distribution of the received signal-to-noise ratio (SNR) is matched to a Gamma random variable whose parameters depend on the total number of RIS elements as well as the channel pathloss. Next, by assuming FBL model, the achievable rate expression is identified and the corresponding average rate is elaborated based on the proposed SNR distribution. The phase error due to quantizing the phase shifts is considered in the simulation. The numerical results show that Monte Carlo simulations conform to the matched Gamma distribution for the received SNR for large number of RIS elements. In addition, the system reliability indicated by the tightness of the SNR distribution increases when RIS is leveraged particularly when only the reflected channel exists. This highlights the advantages of RIS-aided communications for ultra-reliable low-latency communications (URLLC) systems. The reduction of average achievable rate due to working in FBL regime with respect to Shannon capacity is also investigated as a function of total RIS elements.

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arXiv2020

CSI-free vs CSI-based multi-antenna WET for massive low-power Internet of Things

Wireless Energy Transfer (WET) is a promising solution for powering massive Internet of Things deployments. An important question is whether the costly Channel State Information (CSI) acquisition procedure is necessary for optimum performance. In this paper, we shed some light into this matter by evaluating CSI-based and CSI-free multi-antenna WET schemes in a setup with WET in the downlink, and periodic or Poisson-traffic Wireless Information Transfer (WIT) in the uplink. When CSI is available, we show that a maximum ratio transmission beamformer is close to optimum whenever the farthest node experiences at least 3 dB of power attenuation more than the remaining devices. On the other hand, although the adopted CSI-free mechanism is not capable of providing average harvesting gains, it does provide greater WET/WIT diversity with lower energy requirements when compared with the CSI-based scheme. Our numerical results evidence that the CSI-free scheme performs favorably under periodic traffic conditions, but it may be deficient in case of Poisson traffic, specially if the setup is not optimally configured. Finally, we show the prominent performance results when the uplink transmissions are periodic, while highlighting the need of a minimum mean square error equalizer rather than zero-forcing for information decoding.

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arXiv2020

A Predictive Interference Management Algorithm for URLLC in Beyond 5G Networks

Interference mitigation is a major design challenge in wireless systems,especially in the context of ultra-reliable low-latency communication (URLLC) services. Conventional average-based interference management schemes are not suitable for URLLC as they do not accurately capture the tail information of the interference distribution. This letter proposes a novel interference prediction algorithm that considers the entire interference distribution instead of only the mean. The key idea is to model the interference variation as a discrete state space discrete-time Markov chain. The state transition probability matrix is then used to estimate the state evolution in time, and allocate radio resources accordingly. The proposed scheme is found to meet the target reliability requirements in a low-latency single-shot transmission system considering realistic system assumptions, while requiring only ~25% more resources than the optimum case with perfect interference knowledge.

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arXiv2020

White Paper on Critical and Massive Machine Type Communication Towards 6G

The society as a whole, and many vertical sectors in particular, is becoming increasingly digitalized. Machine Type Communication (MTC), encompassing its massive and critical aspects, and ubiquitous wireless connectivity are among the main enablers of such digitization at large. The recently introduced 5G New Radio is natively designed to support both aspects of MTC to promote the digital transformation of the society. However, it is evident that some of the more demanding requirements cannot be fully supported by 5G networks. Alongside, further development of the society towards 2030 will give rise to new and more stringent requirements on wireless connectivity in general, and MTC in particular. Driven by the societal trends towards 2030, the next generation (6G) will be an agile and efficient convergent network serving a set of diverse service classes and a wide range of key performance indicators (KPI). This white paper explores the main drivers and requirements of an MTC-optimized 6G network, and discusses the following six key research questions: - Will the main KPIs of 5G continue to be the dominant KPIs in 6G; or will there emerge new key metrics? - How to deliver different E2E service mandates with different KPI requirements considering joint-optimization at the physical up to the application layer? - What are the key enablers towards designing ultra-low power receivers and highly efficient sleep modes? - How to tackle a disruptive rather than incremental joint design of a massively scalable waveform and medium access policy for global MTC connectivity? - How to support new service classes characterizing mission-critical and dependable MTC in 6G? - What are the potential enablers of long term, lightweight and flexible privacy and security schemes considering MTC device requirements?

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arXiv2020

Enabling URLLC for Low-Cost IoT Devices via Diversity Combining Schemes

Supporting Ultra-Reliable Low-Latency Communication (URLLC) in the Internet of Things (IoT) era is challenging due to stringent constraints on latency and reliability combined with the simple circuitry of IoT nodes. Diversity is usually required for sustaining the reliability levels of URLLC, but there is an additional delay associated to auxiliary procedures to be considered, specially when communication includes low-cost IoT devices. Herein, we analyze Selection Combining (SC) and Switch and Stay Combining (SSC) diversity schemes as plausible solutions for enabling ultra-reliable low-latency downlink communications to low-cost IoT devices. We demonstrate the necessity of considering the time spent in auxiliary procedures, which has not been traditionally taken into account, while we show its impact on the reliability performance. We show there is an optimum number of receive antennas, which suggests that under certain conditions it might be required to turn off some of them, specially under the SC operation. We highlight the superiority of SSC with respect to SC as long the associated Signal-to-Noise Ratio threshold is properly selected. We propose using a fixed threshold relying only on long-term channel fading statistics, which leads to near-optimum results.

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arXiv2019

Dynamic Multi-Connectivity Activation for Ultra-Reliable and Low-Latency Communication

Multi-connectivity (MC) with packet duplication, where the same data packet is duplicated and transmitted from multiple transmitters, is proposed in 5G New Radio as a reliability enhancement feature. However, it is found to be resource inefficient, since radio resources from more than one transmitters are required to serve a single user. Improving the performance enhancement vs. resource utilization tradeoff with MC is therefore a key design challenge. This work proposes a heuristic resource efficient latency-aware dynamic MC algorithm which activates MC selectively such that its benefits are harnessed for critical users, while minimizing the corresponding resource usage. Numerical results indicate that the proposed algorithm can deliver the outage performance gains of legacy MC schemes while requiring up to 45% less resources.

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arXiv2019

Uplink Grant-Free Random Access Solutions for URLLC services in 5G New Radio

The newly introduced ultra-reliable low latency communication service class in 5G New Radio depends on innovative low latency radio resource management solutions that can guarantee high reliability. Grant-free random access, where channel resources are accessed without undergoing assignment through a handshake process, is proposed in 5G New Radio as an important latency reducing solution. However, this comes at an increased likelihood of collisions resulting from uncontrolled channel access, when the same resources are preallocated to a group of users. Novel reliability enhancement techniques are therefore needed. This article provides an overview of grant-free random access in 5G New Radio focusing on the ultra-reliable low latency communication service class, and presents two reliability-enhancing solutions. The first proposes retransmissions over shared resources, whereas the second proposal incorporates grant-free transmission with non-orthogonal multiple access with overlapping transmissions being resolved through the use of advanced receivers. Both proposed solutions result in significant performance gains, in terms of reliability as well as resource efficiency. For example, the proposed non-orthogonal multiple access scheme can support a normalized load of more than 1.5 users/slot at packet loss rates of ~10^{-5} - a significant improvement over the maximum supported load with conventional grant-free schemes like slotted-ALOHA.

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arXiv2019

Multi-Channel Access Solutions for 5G New Radio

5G New Radio paves the way for introducing novel multi-service radio resource management solutions tailored for enhanced Mobile Broadband and Ultra-Reliable Low Latency Communication service classes. Multi-Channel Access is a family of such multi-service solutions that enable a user equipment to aggregate radio resources from multiple sources. The objective is multi-fold; throughput enhancement through access to a larger bandwidth, reliability improvement by increasing the diversity order and/or coordinated transmission/reception, as well as flexibility and load balancing improvement by decoupling the downlink and the uplink access points. This paper presents several multi-channel access solutions for 5G New Radio multi-service scenarios. In particular, throughput enhancement and latency reduction concepts like multi-connectivity, carrier aggregation, downlink-uplink decoupled access and coordinated multi-point connectivity are discussed. Moreover, novel design solutions exploiting these concepts are proposed. Numerical evaluation of the introduced solutions indicates significant performance gains over state-of-the-art schemes; for example, our proposed component carrier selection mechanism leads to a median throughput gain of up to 100% by means of an implicit load balance. Therefore, the proposed Multi-Channel Access solutions have the potential to be key multi-service enablers for 5G New Radio.

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arXiv2019

Six Key Enablers for Machine Type Communication in 6G

While 5G is being rolled out in different parts of the globe, few research groups around the world $-$ such as the Finnish 6G Flagship program $-$ have already started posing the question: \textit{What will 6G be?} The 6G vision is a data-driven society, enabled by near instant unlimited wireless connectivity. Driven by impetus to provide vertical-specific wireless network solutions, machine type communication encompassing both its mission critical and massive connectivity aspects is foreseen to be an important cornerstone of 6G development. This article presents an over-arching vision for machine type communication in 6G. In this regard, some relevant performance indicators are first anticipated, followed by a presentation of six key enabling technologies.

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arXiv2019

On the Resource Utilization of Multi-Connectivity Transmission for URLLC Services in 5G New Radio

Multi-connectivity with packet duplication, where the same data packet is duplicated and transmitted from multiple transmitters, is proposed in 5G New Radio as a reliability enhancement feature. This paper presents an analytical study of the outage probability enhancement with multi-connectivity, and analyses its cost in terms of resource usage. The performance analysis is further compared against conventional single-connectivity transmission. Our analysis shows that, for transmission with a given block error rate target, multi-connectivity results in more than an order of magnitude outage probability improvement over the baseline single-connectivity scheme. However, such gains are achieved at the cost of almost doubling the amount of radio resources used. Multi-connectivity should thus be selectively used such that its benefits can be harnessed for critical users, while the price to pay in terms of resource utilization is simultaneously minimized.

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