Related papers: An Analytical Framework for Heterogeneous Partial …

4G wireless access systems require high spectral efficiency to support the ever increasing number of users and data rates for real time applications. Multi-antenna OFDM-SDMA systems can provide the required high spectral efficiency and…

We propose a new one-bit feedback scheme with scheduling decision based on the maximum expected weighted rate. We show the concavity of the $2$-user case and provide the optimal solution which achieves the maximum weighted rate of the…

It is well known that opportunistic scheduling algorithms are throughput optimal under full knowledge of channel and network conditions. However, these algorithms achieve a hypothetical achievable rate region which does not take into…

Code Division Multiple Access (CDMA) in which the spreading code assignment to users contains a random element has recently become a cornerstone of CDMA research. The random element in the construction is particular attractive as it…

In heterogeneous networks, achieving congestion avoidance is difficult because the congestion feedback from one subnetwork may have no meaning to source on other other subnetworks. We propose using changes in round-trip delay as an implicit…

Considering a heterogeneous network (HetNet) where both macro base station (BS) and small cell (SC) nodes are equipped with massive antennas, this paper studies the performance for multiple-input multiple-output (MIMO) downlinks when the…

Real networks often have severe degree heterogeneity, with the maximum, average, and minimum node degrees differing significantly. This paper examines the impact of degree heterogeneity on statistical limits of network data analysis.…

Non-orthogonal multiple access (NOMA) allows multiple users to simultaneously access the same time-frequency resource by using superposition coding and successive interference cancellation (SIC). Thus far, most papers on NOMA have focused…

In multicenter research, individual-level data are often protected against sharing across sites. To overcome the barrier of data sharing, many distributed algorithms, which only require sharing aggregated information, have been developed.…

We propose algorithms for cloud radio access networks that not only provide heterogeneous quality of-service (QoS) for rate- and, importantly, delay-sensitive applications, but also jointly optimize the frequency reuse pattern. Importantly,…

This work studies the problem of controlling the mean-field density of large-scale stochastic systems, which has applications in various fields such as swarm robotics. Recently, there is a growing amount of literature that employs…

Today, we have required to accommodate a large number of users under a single base station. This can be possible only if we have some flexibility over the spectrum. Previously we have lots of multiplexing methods to accommodate large number…

Multiple access (MA) design is investigated for facilitating the coexistence of the emerging semantic transmission and the conventional bit-based transmission in future networks. The semantic rate is considered for measuring the performance…

We consider a resource management problem in a multi-cell downlink OFDMA network, whereby the goal is to find the optimal per base station resource allocation and user-base station assignment. The users are assumed to be strategic/selfish…

We propose a versatile feedback scheme for both single- and multi-user multiple-input multiple-output (MIMO) frequency division duplex (FDD) systems. Particularly, we propose utilizing a Gaussian mixture model (GMM) with a reduced number of…

Deep learning systems are optimized for clusters with homogeneous resources. However, heterogeneity is prevalent in computing infrastructure across edge, cloud and HPC. When training neural networks using stochastic gradient descent…

In this paper, we define an underlying data generating process that allows for different magnitudes of cross-sectional dependence, along with time series autocorrelation. This is achieved via high-dimensional moving average processes of…

Opportunistic scheduling and beamforming schemes are proposed for multiuser MIMO-SDMA downlink systems with linear combining in this work. Signals received from all antennas of each mobile terminal (MT) are linearly combined to improve the…

A semi-centralized joint cell muting and user scheduling scheme for interference coordination in a multicell network is proposed under two different temporal fairness criteria. The main principle behind the proposed scheme is that a central…

The Expectation Maximization (EM) algorithm is the default algorithm for inference in latent variable models. As in any other field of machine learning, applications of latent variable models to very large datasets make the use of advanced…