Browsing by Subject "Wireless communication"

Now showing 1 - 5 of 5

Open Access
Controlling age of ınformation in a dual-server system with transmission freezing and preemption
(IEEE, 2024-12-16) Akar, Nail; Ulukuş, Şennur
We study age of information (AoI) in a status update system for the generate-at-will (GAW) scenario, consisting of a single information source, dual heterogeneous servers, and a monitor. For this system, stochastic hybrid systems (SHS) were used to obtain the mean AoI for the work-conserving zero wait (ZW) policy with out-of-order packet discarding at the monitor. In this paper, we propose a non-work-conserving freeze/preempt (F/P) policy for which the sampling and transmission process is frozen for an Erlang-distributed duration upon each new transmission, and out-of-order (obsolete) packets are preempted at the source, rather than being discarded at the monitor upon reception. We use the absorbing Markov chain (AMC) method to obtain the exact distributions of AoI and also the peak AoI (PAoI) processes, for the F/P policy. Numerical results are presented for the validation of the proposed analytical model and a comparative evaluation of ZW and F/P policies.
Open Access
Design of application specific processors for the cached FFT algorithm
(IEEE, 2006-05) Atak, Oğuzhan; Atalar, Abdullah; Arıkan, Erdal; Ishebabi, H.; Kammler, D.; Ascheid, G.; Meyr, H.; Nicola, M.; Masera, G.
Orthogonal frequency division multiplexing (OFDM) is a data transmission technique which is used in wired and wireless digital communication systems. In this technique, fast Fourier transformation (FFT) and inverse FFT (IFFT) are kernel processing blocks in an OFDM system, and are used for data (de)modulation. OFDM systems are increasingly required to be flexible to accommodate different standards and operation modes, in addition to being energy-efficient. A trade-off between these two conflicting requirements can be achieved by employing application-specific instruction-set processors (ASIPs). In this paper, two ASIP design concepts for the cached FFT algorithm (CFFT) are presented. A reduction in energy dissipation of up to 25% is achieved compared to an ASIP for the widely used Cooley-Tukey FFT algorithm, which was designed by using the same design methodology and technology. Further, a modified CFFT algorithm which enables a better cache utilization is presented. This modification reduces the energy dissipation by up to 10% compared to the original CFFT implementation.
Open Access
Federated learning and distributed inference over wireless channels
(2023-11) Tegin, Büşra
In an era marked by massive connectivity and a growing number of connected devices, we have gained unprecedented access to a wealth of information, enhancing the reliability and precision of intelligent systems and enabling the de-velopment of learning algorithms that are more capable than ever. However, this proliferation of data also introduces new challenges for centralized learning algorithms for the training and inference processes of these intelligent systems due to increased traffic loads and the necessity of substantial computational resources. Consequently, the introduction of federated learning (FL) and distributed inference systems has become essential. Both FL and distributed inference necessitate communication within the network, specifically, the transmission of model updates and intermediate features. This has led to a significant emphasis on their utilization over wireless channels, underscoring the pivotal role of wireless communications in this context. In pursuit of a practical implementation of federated learning over wireless fading channels, we direct our focus towards cost-effective solutions, accounting for hardware-induced distortions. We consider a blind transmitter scenario, wherein distributed workers operate without access to channel state information (CSI). Meanwhile, the parameter server (PS) employs multiple antennas to align received signals. To mitigate the increased power consumption and hardware cost, we leverage complex-valued, low-resolution digital-to-analog converters (DACs) at the transmitter and analog-to-digital converters (ADCs) at the PS. Through a combination of theoretical analysis and numerical demonstrations, we establish that federated learning systems can effectively operate over fading channels, even in the presence of low-resolution ADCs and DACs. As another aspect of practical implementation, we investigate federated learning with over-the-air aggregation over time-varying wireless channels. In this scenario, workers transmit their local gradients over channels that undergo time variations, stemming from factors such as worker or PS mobility and other transmission medium fluctuations. These channel variations introduce inter-carrier interference (ICI), which can notably degrade the system performance, particularly in cases of rapidly varying channels. We examine the effects of the channel time variations on FL with over-the-air aggregation, and show that the resulting undesired interference terms have only limited destructive effects, which do not prevent the convergence of the distributed learning algorithm. Focusing on the distributed inference concept, we also consider a multi-sensor wireless inference system. In this configuration, several sensors with constrained computational capacities observe common phenomena and engage in collaborative inference efforts alongside a central device. Given the inherent limitations on the computational capabilities of the sensors, the features extracted from the front part of the network are transmitted to an edge device, which necessitates sensor fusion for the intermediate features. We propose Lp-norm inspired and LogSumExp approximations for the maximum operation as a sensor fusion method, resulting in the acquisition of transformation-invariant features that also enable bandwidth-efficient feature transmission. As a further enhancement of the proposed method, we introduce a learnable sensor fusion technique inspired by the Lp-norm. This technique incorporates a trainable parameter, providing the flexibility to customize the sensor fusion according to the unique network and sensor distribution characteristics. We show that by encompassing a spectrum of behaviors, this approach enhances the adaptability of the system and contributes to its overall performance improvement.
Open Access
Random access over wireless links: optimal rate and activity probability selection
(IEEE, 2017-12) Duman, Tolga M.; Karakoç, N.
In this paper, we consider a random access scheme over wireless fading channels based on slotted ALOHA where each user independently decides whether to send a packet or not to a common receiver at any given time slot. To characterize the system throughput, i.e., the expected sum- rate, an information theoretic formulation is developed. We consider two scenarios: classical slotted ALOHA where no multi-user detection (MUD) capability is available and slotted ALOHA with MUD. Our main contribution is that the optimal rates and channel activity probabilities can be characterized as a function of the user distances to the receiver to maximize the system throughput. In addition, we address the issue of fairness among the users and provide solutions, which guarantee a minimum amount of individual throughput.
Open Access
Wireless monitoring of a structural beam to be used for post-earthquake damage assessment
(IEEE, 2018-05-06) Özbey, B.; Kurc, O.; Demir, Hilmi Volkan; Ertürk, Vakur B.; Altıntaş, Ayhan
Wireless monitoring of a standard reinforced concrete beam is shown in a simply supported beam experiment. The passive nested split-ring resonator (NSRR) probes are attached on the reinforcing bars (rebars) within the beam, and an antenna interrogates the probes from outside the beam. The results of the experiment show that the plastic deformation region strain/displacement can be detected by the wireless sensing system. The data collected by the system constitutes an important input for the assessment of the damage that can be observed after earthquakes.