Publications

MMSE based receiver design for MC-CDMA systems

Multicarrier code-division multiple-access (MC-CDMA) is a potentially attractive multiple access technique for future wireless communication systems. In this paper space-frequency minimum mean squared error based parallel interference cancellation receiver (SF-MMSE/PIC) is developed for MC-CDMA systems which produces the SF-MMSE combining as a byproduct. The signal processing of this new detector is jointly carried out in space and frequency domain which leads to the advantage of combating the interference from different sources simultaneously. Several representative simulation examples of the proposed SF-MMSE/PIC receiver are provided to demonstrate its powerful capability to suppress interference. In the fully loaded system, the proposed receiver can offer single user performance.

Infrastructure Sharing for Mobile Network Operators: Analysis of Trade-offs and Market

The conflicting problems of growing mobile service demand and underutilization of dedicated spectrum has given rise to a paradigm where mobile network operators (MNOs) share their infrastructure among themselves in order to lower their operational costs, while at the same time increase the usage of their existing network resources. We model and analyze such an infrastructure sharing system considering a single buyer MNO and multiple seller MNOs. Assuming that the locations of the BSs can be modeled as a homogeneous Poisson point process, we find the downlink signal-to-interference-plus-noise ratio (SINR) coverage probability for a user served by the buyer MNO in an infrastructure sharing environment. We analyze the trade-off between increasing the transmit power of a BS and the intensity of BSs owned by the buyer MNO required to achieve a given quality-of-service (QoS) in terms of the SINR coverage probability. Also, for a seller MNO, we analyze the power consumption of the network per unit area (i.e., areal power consumption) which is shown to be a piecewise continuous function of BS intensity, composed of a linear and a convex function. Accordingly, the BS intensity of the seller MNO can be optimized to minimize the areal power consumption while achieving a minimum QoS for the buyer MNO. We then use these results to formulate a single-buyer multiple-seller BS infrastructure market. The buyer MNO is concerned with finding which seller MNO to purchase from and what fraction of BSs to purchase. On the sellers' side, the problem of pricing and determining the fraction of infrastructure to be sold is formulated as a Cournot oligopoly market. We prove that the iterative update of each seller's best response always converges to the Nash Equilibrium.

Design study for a CDMA-based LEO satellite network: downlink system level parameters

The performance analysis of a new concept of a code-division multiple-access (CDMA) based low Earth orbit (LEO) satellite network for mobile satellite communications is presented and discussed. The starting point was to analyze the feasibility of implementing multisatellite and multipath diversity reception in a CDMA network for LEO satellites. The results are used to specify the design parameters for a system experimental test bed. Due to the extremely high Doppler, which is characteristic of LEO satellites, code acquisition is significantly simplified by using a continuous wave (CW) pilot carrier for Doppler estimation and compensation. The basic elements for the analysis presented are: the channel model, the pilot carrier frequency estimation for Doppler compensation, and multipath and multisatellite diversity combining.

Weighted sum-rate maximization for downlink OFDMA systems

We consider the weighted sum rate maximization problem in downlink orthogonal frequency division multiple access (OFDMA) systems. A low complexity suboptimal resource allocation algorithm is proposed for joint optimization of multiuser subcarrier assignment and power allocation. This algorithm is based on an approximated primal decomposition based method, which is inspired from exact primal decomposition techniques. The original nonconvex optimization problem is divided into two subproblems and can be solved independently. Simulations are provided to compare the performance of the proposed algorithm to exhaustive search based methods and Lagrange relaxation based suboptimal methods. Despite its reduced computational complexity, the proposed algorithm provides close to optimal performance.

Hybrid beamforming for single-user MIMO with partially connected RF architecture

Hybrid analog-digital beamforming has been recognized as a promising solution for a practical implementation of massive multiple-input multiple-output (MIMO) systems based on millimeter-wave technology. In this paper, three hybrid beamforming algorithms are proposed for single-user MIMO systems with partially connected radio frequency (RF) architecture, including a singular value decomposition (SVD) matching algorithm, an iterative orthogonalization algorithm, and a transmit-receive zero forcing (ZF) algorithm. The rate performance of the proposed algorithms is compared with fully digital and analog beamforming in a realistic geometry-based stochastic channel model. The simulation results show that the transmit-receive ZF is superior among hybrid methods, and it provides performance relatively close to that of the digital beamforming. In conclusion, carefully designed partially connected hybrid beamforming can obtain an excellent balance between hardware complexity and performance.

Vehicle clustering for improving enhanced LTE-V2X network performance

Vehicle-to-Everything (V2X) communication holds the promise for improving road safety and reducing road accidents by enabling reliable and low latency services for vehicles. Vehicles are among the fastest growing type of connected devices. Therefore, there is a need for V2X communication, i.e., passing of information from Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) and vice versa. In this paper, we focus on both V2I and V2V communication in a multi-lane freeway scenario, where coverage is provided by the Long Term Evolution Advanced (LTE-A) road side unit (RSU) network. Here, we propose a mechanism to offload vehicles with low signal-to-interference-plus-noise ratio (SINR) to be served by other vehicles, which have much higher quality link to the RSU. Furthermore, we analyze the improvements in the probabilities of achieving target throughputs and the performance is assessed through extensive system-level simulations. Results show that the proposed solution offloads low quality V2I links to stronger V2V links, and further increases successful transmission probability from 93% to 99.4%.

Generative AI-Based Probabilistic Constellation Shaping With Diffusion Models

Diffusion models are at the vanguard of generative AI research with renowned solutions such as ImageGen by Google Brain and DALL.E 3 by OpenAI. Nevertheless, the potential merits of diffusion models for communication engineering applications are not fully understood yet. In this paper, we aim to unleash the power of generative AI for PHY design of constellation symbols in communication systems. Although the geometry of constellations is predetermined according to networking standards, e.g., quadrature amplitude modulation (QAM), probabilistic shaping can design the probability of occurrence (generation) of constellation symbols. This can help improve the information rate and decoding performance of communication systems. We exploit the ``denoise-and-generate'' characteristics of denoising diffusion probabilistic models (DDPM) for probabilistic constellation shaping. The key idea is to learn generating constellation symbols out of noise, ``mimicking'' the way the receiver performs symbol reconstruction. This way, we make the constellation symbols sent by the transmitter, and what is inferred (reconstructed) at the receiver become as similar as possible, resulting in as few mismatches as possible. Our results show that the generative AI-based scheme outperforms deep neural network (DNN)-based benchmark and uniform shaping, while providing network resilience as well as robust out-of-distribution performance under low-SNR regimes and non-Gaussian assumptions. Numerical evaluations highlight 30% improvement in terms of cosine similarity and a threefold improvement in terms of mutual information compared to DNN-based approach for 64-QAM geometry.

Resource Optimization and Power Allocation in In-band Full Duplex (IBFD)-Enabled Non-Orthogonal Multiple Access Networks

In this paper, the problem of uplink (UL) and downlink (DL) resource optimization, mode selection and power allocation is studied for wireless cellular networks under the assumption of in-band full duplex (IBFD) base stations, non-orthogonal multiple access (NOMA) operation, and queue stability constraints. The problem is formulated as a network utility maximization problem for which a Lyapunov framework is used to decompose it into two disjoint subproblems of auxiliary variable selection and rate maximization. The latter is further decoupled into a user association and mode selection (UAMS) problem and a UL/DL power optimization (UDPO) problem that are solved concurrently. The UAMS problem is modeled as a many-to-one matching problem to associate users to small cell base stations (SBSs) and select transmission mode (half/full-duplex and orthogonal/non-orthogonal multiple access), and an algorithm is proposed to solve the problem converging to a pairwise stable matching. Subsequently, the UDPO problem is formulated as a sequence of convex problems and is solved using the concave-convex procedure. Simulation results demonstrate the effectiveness of the proposed scheme to allocate UL and DL power levels after dynamically selecting the operating mode and the served users, under different traffic intensity conditions, network density, and self-interference cancellation capability. The proposed scheme is shown to achieve up to 63% and 73% of gains in UL and DL packet throughput, and 21% and 17% in UL and DL cell edge throughput, respectively, compared to existing baseline schemes.

A New Approach on Analysis of IEEE 802.11 DCF in Non-Saturated Wireless Networks

Many performance evaluations for IEEE 802.11 distributed coordination function (DCF) have been formerly reported in the literature; most studies are based on saturation analysis, and a few models under a finite load condition adopt an M/G/l queuing system. However, using M/G/l queuing only considers the first moment of frame service time to derive the probability of transmission queue being vacant. In this paper, we model the DCF using parallel space-time Markov chain (PSTMC), in which frame arrivals are tracked by monitoring the transmission queue during transitions between successive states of the space-time Markov chain. The proposed framework provides the possibility of modeling the contention phase, backoff and post-backoff procedures, and the transmission queue status. The proposed framework is validated by the simulation results.

Effects of Relay Selection Strategies on the Spectral Efficiency of Wireless Systems with Half- and Full-duplex Nodes

This work proposes an analytical framework to study how relay selection strategies perform in half- and full-duplex deployments by combining renewal theory and stochastic geometry. Specifically, we assume that the network nodes -- operating in either half- or full-duplex mode -- are scattered according to a two-dimensional homogeneous Poisson point process to compute the relay selection cost by using a semi-Markov process. Our results show: ($i$) fixed relay outperforms the reactive option in either cases, ($ii$) the performance of both reactive and fixed relay strategies depends on the self-interference attenuation in full-duplex scenarios, evincing when they outperform the half-duplex option, and ($iii$) the reactive relay selection suffers from selecting relays at hop basis, while the fixed relay selection benefits most from the full-duplex communication.

Ultra reliable communication via opportunistic ARQ transmission in cognitive networks

This paper presents a novel opportunistic spectrum sharing scheme that applies ARQ protocol to achieve ultra reliability in the finite blocklength regime. A primary user shares its licensed spectrum to a secondary user, where both communicate to the same base station. The base station applies ARQ with the secondary user, which possess a limited number of trials to transmit each packet. We resort to the interweave model in which the secondary user senses the primary user activity and accesses the channel with access probabilities which depend on the primary user arrival rate and the number of available trials. We characterize the secondary user access probabilities and transmit power in order to achieve target error constraints for both users. Furthermore, we analyze the primary user performance in terms of outage probability and delay. The results show that our proposed scheme outperforms the open loop and non-opportunistic scenarios in terms of secondary user transmit power saving and primary user reliability.

Bandwidth Resource Competition in Cooperative Cognitive Wireless Communications

No abstract is provided for this article.

Waveform Optimization and Beam Focusing for Near-field Wireless Power Transfer with Dynamic Metasurface Antennas and Non-linear Energy Harvesters

No abstract is provided for this article.

Joint Sum Rate and Blocklength Optimization in RIS-aided Short Packet URLLC Systems

In this paper, a multi-objective optimization problem (MOOP) is proposed for maximizing the achievable finite blocklength (FBL) rate while minimizing the utilized channel blocklengths (CBLs) in a reconfigurable intelligent surface (RIS)-assisted short packet communication system. The formulated MOOP has two objective functions namely maximizing the total FBL rate with a target error probability, and minimizing the total utilized CBLs which is directly proportional to the transmission duration. The considered MOOP variables are the base station (BS) transmit power, number of CBLs, and passive beamforming at the RIS. Since the proposed non-convex problem is intractable to solve, the Tchebyshev method is invoked to transform it into a single-objective OP, then the alternating optimization (AO) technique is employed to iteratively obtain optimized parameters in three main sub-problems. The numerical results show a fundamental trade-off between maximizing the achievable rate in the FBL regime and reducing the transmission duration. Also, the applicability of RIS technology is emphasized in reducing the utilized CBLs while increasing the achievable rate significantly.

Power-throughput tradeoff in MIMO heterogeneous networks

We consider a single-macrocell heterogeneous multiple-input multiple-output network, where the macrocell shares the same frequency band with the femto network. The interference power to the macro users from the femto base stations is kept below a threshold to guarantee that the performance of the macro users does not degrade due to femto network. For this setting, we consider the problem of finding the set of all achievable power-rate tuples. Using the scalarization method, we cast the problem of finding the set of achievable power-rate tuples as a mathematical optimization problem. Using simulations we obtained the different sets of all achievable power-rate values, when the users are served by both macrocell and femtocells, and only by macrocell.

On Contract Design for Incentivizing Users in Cooperative Content Delivery With Adverse Selection

Cooperative content delivery using multiple air interfaces (CCDMI) is a powerful solution to mitigate congestion in cellular networks. In CCDMI, the operator distributes content to selected users that further distribute it locally among its nearby users. However, a user that is capable of contributing to CCDMI might act selfishly and refuse to participate. Although the operator can encourage user participation by offering incentives, it has incomplete information about the users' willingness to participate. In order to overcome this problem of adverse selection in CCDMI, we propose two contract-based methods under information asymmetry. In both methods, the operator designs a performance-based contract set for the users that are capable of local content distribution. Using a mathematical analysis, we show that the optimal contract under information asymmetry achieves close to optimal utility for the users and the operator, compared with the information symmetry case. Moreover, the users with high willingness to participate get positive utility and the users with low willingness get zero utility. Hence, by assigning contracts, the operator can motivate user participation, despite the information asymmetry between them. Our results verify that the proposed methods improve the system performance in terms of the utility of the operator and the users.

Enhanced performance of heterogeneous networks through full-duplex relaying

In this article, we focus on the uplink of a heterogeneous network composed of a macrocell and an underlaid femtocell. We address the problem of the interference caused by the macro user (MU) on the femtocell [femto base station (FBS) and users]. The femtocell is composed of an user, a femto relay, which can be seen as another FBS or a dedicated relay, and an FBS. We assume a full-duplex relay (FDR) node which is able to transmit and receive simultaneously while suffering from residual self-interference. We focus on the performance of the femtocell according to different positions of the MU user. We derive closed-form expressions for the outage probability and spectral efficiency (throughput) taking into account the self-interference of the FDR node. Moreover, we assume that the nodes are able to apply successive interference cancellation on the MU signal. Our results show that FDR can considerably enhance the performance of the femtocell, even in the presence of strong self-interference at the FDR, allowing the femtocell to operate in a high rate regime.

End-to-End Joint Waveform and Beamforming Optimization for RF Wireless Power Transfer with Hybrid Transmit Architecture and Non-Linear Energy Harvesters