Department Publications

Low-resolution analog-to-digital converters (ADCs) have emerged as a promising solution to reduce the power consumption of massive multiple-input-multiple-output (MIMO) receivers. However, allocating a fixed number of ADC bits uniformly across all receive antennas often results in suboptimal energy efficiency (EE), particularly when channel conditions vary significantly across antennas. This paper proposes a learning-based ADC bit allocation strategy that dynamically adjusts the resolution of each ADC based on the corresponding channel gain. The proposed method effectively allocates higher-resolution ADCs to antennas experiencing stronger channel gains while minimizing the resolution for weaker channels, thereby improving the overall EE. Simulation results demonstrate that the proposed method achieves near-optimal EE performance comparable to the brute-force approach but with significantly lower …

The radio spectrum is a scarce and extremely valuable resource that demands careful real-time monitoring and dynamic resource allocation. Dynamic spectrum access (DSA) is a new paradigm for managing the radio spectrum, which requires AI/ML-driven algorithms for optimum performance under rapidly changing channel conditions and possible cyber-attacks in the electromagnetic domain. Fast sensing across multiple directions using array processors, with subsequent AI/ML-based algorithms for the sensing and perception of waveforms that are measured from the environment is critical for providing decision support in DSA. As part of directional and wideband spectrum perception, the ability to finely channelize wideband inputs using efficient Fourier analysis is much needed. However, a fine-grain fast Fourier transform (FFT) across a large number of directions is computationally intensive and leads to a high chip area and power consumption. We address this issue by exploiting the recently proposed approximate discrete Fourier transform (ADFT), which has its own sparse factorization for real-time implementation at a low complexity and power consumption. The ADFT is used to create a wideband multibeam RF digital beamformer and temporal spectrum-based attention unit that monitors 32 discrete directions across 32 sub-bands in real-time using a multiplierless algorithm with low computational complexity. The output of this spectral attention unit is applied as a decision variable to an intelligent receiver that adapts its center frequency and frequency resolution via FFT channelizers that are custom-built for real-time monitoring at high …

We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab’s EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1–6 s warning window, slightly behind the 1.5–6.75 s of the internet-based performance of CRISiSLab’s system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration.

In this paper, we design a resource block (RB) oriented power pool (PP) for semi-grant-free non-orthogonal multiple access (SGF-NOMA) in the presence of residual errors resulting from imperfect successive interference cancellation (SIC). In the proposed method, the BS allocates one orthogonal RB to each grant-based (GB) user, and determines the acceptable received power from grant-free (GF) users and calculates a threshold against this RB for broadcasting. Each GF user as an agent, tries to find the optimal transmit power and RB without affecting the quality-of-service (QoS) and ongoing transmission of the GB user. To this end, we formulate the transmit power and RB allocation problem as a stochastic Markov game to design the desired PPs and maximize the long-term system throughput. The problem is then solved using multi-agent (MA) deep reinforcement learning algorithms, such as double deep Q …

Signal propagation in wireless communication undergoes an effect called shadowing (or shadow fading) depending on the built and natural surroundings that impede propagation. Thus, the fixed surroundings contribute to a level of correlation in shadow fading over a given distance in space, which is referred to as spatial correlation in shadow fading. This paper propose a method to simulate homogeneous spatial-correlation in shadow fading in the 2D space with a roughly specified decorrelation distance, using a 2D convolutional process having a 2D linear time invariant system. Such methods are commonly used in image processing. Simulation results are presented to verify the gener ated correlated spatial process for the shadowing component, and further insights are drawn through 2D spatial autocorrelation values. The proposed method for a single transmitter can be repeated for multiple transmitters that …

Cycling is a popular leisure and fitness activity, making it a prime candidate for emerging virtual and augmented reality applications. This paper details the design, development, and testing of a competitive virtual cycling platform that allows two players to compete regardless of their geographical location on customized stationary bicycles. They wear head-mounted Virtual Reality (VR) devices to immerse themselves in a 360° video experience. Video playback responds to their cycling speed and head orientation. Competitors' locations are displayed on a map within their VR dashboard. The platform's functionality is tested on 4G and 5G networks and an experimental 4G network implemented on software-defined radios. To evaluate the system's usability, the critical metric of end-to-end delay is measured for the different communication architectures. Delays of under 100ms, crucial for preventing motion sickness, are …

The radio spectrum is a scarce and extremely valuable resource that demands careful real-time monitoring and dynamic resource allocation. Dynamic spectrum access (DSA) is a new paradigm for managing the radio spectrum, which requires AI/ML driven algorithms for optimum performance under rapidly changing channel conditions and possible cyber attacks in the electromagnetic domain. Fast sensing across multiple directions using array processors, with subsequent AI/ML based algorithms for sensing and perception of the waveforms that are measured from the environment is critical for providing decision support in DSA. As part of directional and wideband spectrum perception, the ability to finely channelize wideband inputs using efficient Fourier analysis is much needed. However, a fine-grain fast Fourier transform (FFT) across a large number of directions is computationally intensive and leads to high chip area and power consumption. We address this issue by exploiting recently proposed approximate discrete Fourier transforms (ADFT) which has its own sparse factorization for real-time implementation at low complexity and power consumption. The ADFT is used to create a wideband multi-beam RF digital beamformer and temporal spectrum-based attention unit which monitors 32 discrete directions across 32 sub-bands in real-time using a multiplierless algorithm having low computational complexity. The output of this spectral attention unit is applied as a decision variable to an intelligent receiver that adapts its center frequency and frequency resolution via FFT channelizers that are custom-built for real-time monitoring at high …

Wi-Fi has become a cost-effective sensing mechanism due to its widespread availability. Channel State Information (CSI) from the OFDM-based physical layer of Wi-Fi contains rich information for sensing static and dynamic channel conditions, and hence for sensing activities within the channel. Numerous applications which combine CSI-based sensing with machine learning (ML) available for both indoor and outdoor environments. We extend the use of CSI- based Wi-Fi sensing to a unique setting: a confined environment. An industrial beverage cooler is specifically considered. We address the challenges of sensing device placement in such confined environments, where line-of-sight obstruction and near-field effects play a key role in CSI stability. We compensate for these effects by introducing novel combinations of data preprocessing techniques and input feature definitions. We demonstrate an accuracy of 89 …

The radio spectrum is a scarce and vital resource. Every country in the world has sovereign control over its spectrum. Demand for the spectrum in terms of mobile communication-related applications is increasing continuously. As a result, Mobile network operators (MNO) are keen to acquire additional spectrum bands to deploy in mobile networks. 5G technology, as the latest generation of mobile telephony with many advanced features has opened many doors to other industries such as virtual reality, the Internet of Things(IoT), smart cities, smart health care, etc. and demand for them is trending. As a result of its technological advancements and the economic benefits of 5th generation technology (5G), network operators are keen to migrate to 5G. Due to the excessive demand for the spectrum, the true value of the spectrum has gone up drastically. Therefore, understanding the true value of spectrum has become a …

Prioritization of data streams in cellular vehicle-to-everything (C-V2X) may lead to unfavorable packet delays in low-priority streams. This paper studies allocating multiple candidate single-subframe resources (CSRs) per vehicle as a solution. It proposes a methodology to determine the number of CSRs for each vehicle based on the total number of neighboring vehicles, and to assign the multiple data streams among them for simultaneous transmission. The numerical results highlight the achievable delay gains of the proposed approach, and its negligible impact on packet collisions.

This paper proposes a novel approach that utilizes differential encoding to overcome the channel estimation problem in communication systems with low-resolution quantization receivers. For differentially encoded data, we derive the maximum likelihood detection rule for the canonical block-2 detectors, employing just two consecutive quantized observations at the channel output and without any receiver-side channel state information. We establish the optimality of this maximum likelihood detection rule within the class of block- detectors, where , under the condition that , with and denoting the number of quantization bits and input alphabet size, respectively. The derived detector has a simple and easily implementable structure, comparing the quantization region indices of consecutive observations to determine the transmitted message index. By leveraging the structure of the derived optimum …

Dynamic spectrum access is recognized as a potential solution to the problem of spectrum scarcity. Consequently, a significant amount of research has been conducted on spectrum allocation. In this study, we present a multi-traffic class queue-based spectrum allocation solution. The proposed solution is designed for a scenario where communication and other systems do not necessarily require agility in the frequency bands they operate in. The spectrum sensing and forecasting processes are carried out over relatively long time periods compared to the actual transmission rates. The study considers two traffic classes: priority and non-priority. Three packet handling strategies are presented and their average queuing delay performances are compared. While all three strategies yield satisfactory results under low/medium traffic conditions, Strategy 3 exhibits the greatest flexibility in terms of delay performance …

This paper derives the optimum detection rule for communication systems with n-bit phase quantization when data is differentially encoded at the transmitter. The proposed approach avoids the channel estimation problem at the receiver. First, a maximum likelihood detection rule for block-2 detectors utilizing only two consecutive quantized observations at the channel output is obtained. Second, it is shown that the derived maximum likelihood detection rule continues to be optimum for the class of block-L detectors for L ≥ 3 when n = log 2 M, where M is the input alphabet size. Finally, utilizing the structure of the derived optimum detector, a message error probability expression is obtained for Rayleigh fading wireless channels. A simulation study is performed to illustrate the performance of the optimum detectors as well as the performance loss due to the lack of channel knowledge at the receiver. The proposed …

Indoor cycling is a concept that has emerged with technological advancements to serve multiple purposes such as fitness, virtual tourism, and leisure. Commercial solutions have been developed to serve different user groups, with emphasis on corresponding aspects of user experience. This paper proposes a novel approach to indoor cycling, combining key features including real-world 360-degree view, immersive environment, real-time interaction between the real and virtual worlds and dynamic resistance control to simulate changes in elevation. In the proposed solution, a mobile application provides an immersive cycling environment by playing 360-degree videos on a Virtual Reality headset. The environment responds to user movements such as head rotation and cycling speed changes, and in return replicates the actual resistance to the rider using automatic resistance control. These components are …

Penetration of Intelligent Transport Systems (ITS) applications is slow, particularly in developing countries, mainly due to the costs associated with the two state-of-the-art technologies, Dedicated Short-Range Communication (DSRC) and Cellular-V2x (c-V2x).As a solution, this paper presents a DSRC/Wi-Fi hybrid system and evaluates its performance experimentally. Communication within the Wi-Fi segment is via customized beacons serving a similar function as roadside alerts in DSRC, but with a configurable repetition interval. The results show that Wi-Fi beacons can be received over a 200m range with a packet delivery rate of more than 50%. Considering the effective range and the information update rate, we illustrate several applications that are feasible with the hybrid system in Vehicle-to-Vehicle (V2V) and Infrastructure-to-Vehicle (I2V) modes. With our novel hardware design, the expected functionality can …

Mobile users may experience frequent service outages or poor quality of service in rural areas due to the scarcity of base stations in the proximity. Therefore, a cost effective and flexible solution is introduced in this paper with unmanned aerial vehicles (UAVs) and terrestrial base stations (TBSs), coexisting under a stochastic network with the combination of millimeter waves and non-orthogonal access (NOMA) techniques. This is achieved by deploying both the UAVs (millimeter wave frequencies) and TBSs (sub-6 GHz frequencies) in the same system, and selecting the transmitter based on a user association scheme. The maximum signal-to-interference-plus-noise ratio (SINR) and the closest transmitter user association schemes are compared using extensive simulations to identify the most suitable scheme in terms of the outage probability and the achievable downlink rate. The results show that the closest …

This letter investigates the exploitation of an intelligent reflecting surface (IRS) to communicate securely in a two-way network consisting of an untrusted user. In particular, the transmit powers and the phase shift at each element of the IRS are optimized to maximize the sum-secrecy rate, such that the IRS-reflected and non-IRS-reflected signals are added destructively at the untrusted user. The proposed iterative algorithm converges rapidly to a feasible solution of high accuracy with a few iterations. Numerical results demonstrate sum-secrecy rate gains up to 120% compared to naive or partially optimized schemes.

Dynamic adjustment of signal timing based on the number of pedestrians waiting at a crossing results in safer and more efficient intersections. Traditionally, such information is obtained through push-buttons or vision-based techniques. Though counting is possible with the latter, the techniques are associated with privacy concerns, are affected by poor lighting, and equipment is costly and bulky. We present a novel alternative that uses Wi-Fi Channel State Information (CSI) processed through a Deep Neural Network (DNN) model. The amplitude and phase of 51 Orthogonal Frequency Division Multiplexing sub carriers in the IEEE802.11n standard are captured with two ESP32 devices. Of the candidate DNNs trained with the CSI data, a ID-Convolutional Neural Network is experimentally demonstrated to count up to 12 pedestrians with an accuracy of 79 % at the current level of training. This can be generalized to …

This paper investigates the communication reliability for single-input-multiple-output wireless systems with low-resolution phase quantizers. First, the maximum-likelihood detector with -bit phase quantization is derived when there are antennas at the receiver. Then, three low-complexity antenna selection strategies for data detection are proposed and their symbol error probability performance is characterized. It is shown that having 3 or more bits is sufficient to attain the full diversity order , achievable with infinite-bit quantizers, for quadrature phase shift keying modulation under Rayleigh fading. In particular, it is established that the proposed low-complexity max-distance and max-norm antenna selection strategies perform the same as the maximum-likelihood detector in terms of the asymptotic system reliability for . On the other hand, the diversity order decreases dramatically from to when is …

Supporting parallel multi-priority data streams is vital for maintaining the quality of service (QoS) in vehicle-to-everything (V2X) communication. Hence, the European telecommunications standard institute (ETSI) has defined four packet types, with varying priority levels, to be used as broadcast packets in such communication. This paper studies the medium access control (MAC) layer performance of IEEE 802.11p and cellular-V2X (C-V2X) Mode 4 using discrete-time Markov chain (DTMC) based models, while considering parallel multi-priority data streams. The overall model consists of four queue models with their respective traffic generators, which are appropriately linked with the DTMCs modeling the MAC layer operations of IEEE 802.11p and C-V2X Mode 4. Closed-form solutions for the steady-state probabilities of the models are obtained, which are then utilized to derive expressions for key performance …

The acquisition of channel state information is an essential step in enabling intelligent reflecting surfaces (IRSs) for wireless communications. In this letter, we introduce a novel procedure to estimate the cascaded channel between the base station (BS), IRS, and users in a multi-user multiple-input single-output system. The common BS-IRS channel, over which all users transmit, is leveraged to decompose the cascaded channel into a series of rank-1 matrices. Low-rank matrix recovery methods are utilized to improve upon the linear minimum mean-squared error estimate of the cascaded channel. A theoretical upper bound for the mean-square error (MSE) of the proposed estimator is derived. Numerical results reveal that the proposed techniques outperform the existing counterparts in terms of the MSE and scale with the number of BS antennas.

In this paper, we investigate antenna selection strategies for multi-antenna wireless communication systems with low-resolution quantizers. We propose three sub-optimum but low-complexity antenna selection strategies and characterize their symbol error probability performance. We show that the strategy that selects the diversity branch with channel rotated constellation points being furthest away from the decision boundary is the best strategy in terms of symbol error probability. Using numerical analysis, we provide evidence to suggest that this selection strategy achieves the same diversity order as the optimum maximum likelihood (ML) detector under the same operating conditions. An extensive simulation study is performed to illustrate the accuracy of the derived results.

In this letter, we propose a physical-layer security (PLS) scheme for millimeter-wave systems. Our scheme employs analog beamforming with random frequency variation (RFV) for transmitted symbols. We derive the exact closed-form expression of the secrecy rate of our RFV scheme. Furthermore, we verify the superior performance of RFV scheme compared to previously proposed PLS schemes. In particular, the RFV scheme provides higher secrecy rate for more than 70% of the angular range, when the bandwidth is 10% of the carrier frequency. Furthermore, there is no array gain loss at the legitimate user, compared to previously proposed PLS schemes.

Unmanned aerial vehicles (UAVs) commonly referred to as drones are becoming the attractive solution that provides wireless connectivity in a situation wherever the standard terrestrial base station is burden with high data traffic or unreachable in a disaster scenario. Our work examines the problem of best deployment of the UAVs as an aerial base station to empower wireless coverage to the users in the coverage less area. The foremost contributions of this study incorporate couple of strategies to deploy the ABSs and associate the UEs to the best ABS, where the total spectral efficiency of the network is maximized. Approaches will be chosen considering the prevailing environmental condition and system constraints. The first strategy uses an unsupervised clustering algorithm to determine the 2D positioning of the UAV ((x, y) coordinates) and a stable marriage approach is used for UE assignment by …

Deployment of unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) has been considered to be a feasible solution to provide network coverage in scenarios where the conventional terrestrial network is overloaded or inaccessible due to an emergency situation. This article studies the problem of optimal placement of the UAVs as ABSs to enable network connectivity for the users in such a scenario. The main contributions of this work include a less complex approach to optimally position the UAVs and to assign user equipment (UE) to each ABS, such that the total spectral efficiency (TSE) of the network is maximized, while maintaining a minimum QoS requirement for the UEs. The main advantage of the proposed approach is that it only requires the knowledge of UE and ABS locations and statistical channel state information. The optimal 2-dimensional (2D) positions of the ABSs and the UE assignments are found using K-means clustering and a stable marriage approach, considering the characteristics of the air-to-ground propagation channels, the impact of co-channel interference from other ABSs, and the energy constraints of the ABSs. Two approaches are proposed to find the optimal altitudes of the ABSs, using search space constrained exhaustive search and particle swarm optimization (PSO). The numerical results show that the PSO-based approach results in higher TSE compared to the exhaustive search-based approach in dense networks, consuming similar amount of energy for ABS movements. Both approaches lead up to approximately 8-fold energy savings compared to ABS placement using naive exhaustive search.