Publications

Path Selection and Rate Allocation in Self-Backhauled mmWave Networks.

We investigate the problem of multi-hop scheduling in self-backhauled millimeter wave (mmWave) networks. Owing to the high path loss and blockage of mmWave links, multi-hop paths between the macro base station and the intended users via full-duplex small cells need to be carefully selected. This paper addresses the fundamental question: how to select the best paths and how to allocate rates over these paths subject to latency constraints. To answer this question, we propose a new system design, which factors in mmWave-specific channel variations and network dynamics. The problem is cast as a network utility maximization subject to a bounded delay constraint and network stability. The studied problem is decoupled into: (i) a path selection and (ii) rate allocation, whereby learning the best paths is done by means of a reinforcement learning algorithm, and the rate allocation is solved by applying the successive convex approximation method. Via numerical results, our approach ensures reliable communication with a guaranteed probability of 99.9999%, and reduces latency by 50.64% and 92.9% as compared to baselines.

Contention-based Geographic Forwarding Strategies for Wireless Sensors Networks

This paper studies combined relay selection and opportunistic geographic routing strategies for autonomous wireless sensor networks where transmissions occur over multiple hops. The proposed solution is built upon three constituent parts: (i) relay selection algorithm, (ii) contention resolution mechanism, and (iii) geographic forwarding strategy. Using probability generating function and spatial point process as the theoretic background, we propose an auction-based algorithm for selecting the relay node that relies on the network topology as side-information. Our results show that geographic solutions that iteratively exploit the local knowledge of the topology to ponder the algorithm operation outperforms established random approaches.

System Level Performance Evaluation of LTE-V2X Network

Vehicles are among the fastest growing type of connected devices. Therefore, there is a need for Vehicle-to-Everything (V2X) communication i.e. passing of information from a Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) and vice versa. In this paper, the main focus is on the communication between vehicles and road side units (RSUs) commonly referred to as V2I communication in a multi-lane freeway scenario. Moreover, we analyze network related bottlenecks such as the maximum number of vehicles that can be supported when coverage is provided by the Long Term Evolution Advanced (LTE-A) network. The performance evaluation is assessed through extensive system-level simulations. Results show that new resource allocation and interference mitigation techniques are needed in order to achieve the required high reliability requirements, especially when network load is high.

Exact error floor for downlink MC-CDMA with maximal ratio combining in correlated Nakagami fading channels

Relying on the method of characteristic function (CF) and residue calculation, we obtained an exact and closed-form error floor for downlink multicarrier code-division multiple access (MC-CDMA) with maximal ratio combining (MRC) in correlated Nakagami (1960) fading channels. Analysis results show that orthogonal spreading sequences (Walsh and orthogonal Gold sequences) perform better than non-orthogonal sequences (Gold sequences) and Walsh codes are the best. We also find that downlink MC-CDMA can benefit from the correlation between subcarriers.

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.

Hybrid Beamforming for mm-Wave Massive MIMO Systems with Partially Connected RF Architecture

To satisfy the capacity requirements of future mobile systems, under-utilized millimeter wave frequencies can be efficiently exploited by employing massive multiple input-multiple output (MIMO) technology with highly directive beamforming. Hybrid analog-digital beamforming has been recognised as a promising approach for large-scale MIMO implementations with a reduced number of costly and power-hungry radio frequency (RF) chains. In comparison to fully connected architecture, hybrid beamforming (HBF) with partially connected RF architecture is particularly appealing for the practical implementation due to less complex RF power division and combining networks. In this paper, we first formulate single- and multi-user rate maximization problems as weighted minimum mean square error (WMMSE) and derive solutions for hybrid beamformers using alternating optimization. The algorithms are designed for the full-array- and sub-array-based processing strategies of partially connected HBF architecture. In addition, we propose lower complexity sub-array-based zero-forcing algorithms. The performance of the proposed algorithms is evaluated in two different channel models, a simple geometric model and a realistic statistical model. The performance results of the WMMSE HBF algorithms are meant to reveal the potential of partially connected HBF and serve as upper bounds for lower complexity methods. Numerical results imply that properly designed partially connected HBF has the potential to provide an good compromise between hardware complexity and system performance in comparison to fully digital beamforming.

Low Complexity Iterative Algorithm for Finding the MIMO-OFDM Broadcast Channel Sum Capacity

This paper provides a novel low complexity and provably convergent algorithm to find the sum capacity for vector Gaussian broadcast channels. We formulate the problem in the context of a MIMO-OFDM system and discuss the simplifications provided by the block diagonal channel structure. The algorithm also provides the optimum set of covariance matrices for the dual multiple access channel, from which the transmit covariance matrices for the broadcast channel are easy to compute. The key idea of the algorithm is to iteratively maximize the sum capacity for randomly selected pairs of users whilst considering the other users' signals as noise. The proposed algorithm can be considered dual to the iterative water filling (IWF) algorithm used to maximize the sum capacity for the multiple access channel with individual power constraints, but unlike the recently proposed sum power constraint IWF, our proposed algorithm has lower complexity and does not require additional precautions to ensure the convergence. We have proved analytically that the proposed algorithm is convergent in probability and the computer simulations clearly show that the proposed algorithm converges faster than other known algorithms. Index Terms—Broadcast channels, MIMO systems, orthogonal frequency division multiplexing, iterative water-filling.

Denoising Diffusion Probabilistic Models for Hardware-Impaired Communications

Generative AI has received significant attention among a spectrum of diverse industrial and academic domains, thanks to the magnificent results achieved from deep generative models such as generative pre-trained transformers (GPT) and diffusion models. In this paper, we explore the applications of denoising diffusion probabilistic models (DDPMs) in wireless communication systems under practical assumptions such as hardware impairments (HWI), low-SNR regime, and quantization error. Diffusion models are a new class of state-of-the-art generative models that have already showcased notable success with some of the popular examples by OpenAI1 and Google Brain2. The intuition behind DDPM is to decompose the data generation process over small ``denoising'' steps. Inspired by this, we propose using denoising diffusion model-based receiver for a practical wireless communication scheme, while providing network resilience in low-SNR regimes, non-Gaussian noise, different HWI levels, and quantization error. We evaluate the reconstruction performance of our scheme in terms of mean-squared error (MSE) metric. Our results show that more than 25 dB improvement in MSE is achieved compared to deep neural network (DNN)-based receivers. We also highlight robust out-of-distribution performance under non-Gaussian noise.

Weighted sum-rate maximization for a set of interfering links via branch and bound

We consider the problem of weighted sum-rate maximization (WSRMax) for an arbitrary set of interfering links. This problem is known to be NP-hard; therefore, it is extremely difficult to solve even for a relative small number of links. The main contribution of this paper is to provide a solution method, based on the branch and bound technique, which solves WSRMax problem with an optimality certificate. At each step of the proposed algorithm, an upper and a lower bound are computed for the optimal value of the underlying problem. The algorithm terminates when the difference between the upper and the lower bound is smaller than a specified tolerance. The proposed algorithm can be further used to provide other performance benchmarks by back-substituting it into any network design method which relies on WSRMax. It is also very useful for evaluating the performance loss encountered by any heuristic algorithm.

Full-Duplex Non-Orthogonal Multiple Access Networks

No abstract is provided for this article.

Performance Analysis of IEEE 802.11 DCF in non-Saturated Single-hop Wireless Local Area Networks

Many performance evaluations for distributed coordination function (DCF) for IEEE 802.11 Wireless LANs have been previously reported in the literature; most studies based on are 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.

Space-Time Turbo Coded Modulation: Design and Applications

A design method for recursive space-time trellis codes and parallel-concatenated space-time turbo coded modulation is proposed that can be applied to an arbitrary existing space-time trellis code. The method enables a large, systematic increase in coding gain while preserving the maximum transmit diversity gain and bandwidth efficiency property of the considered space-time trellis code. Applying the above method to Tarokh et al. space-time trellis codes, significant performance improvements can be obtained even with extremely short input information frames. The application of space-time turbo coded modulation to the space-frequency domain is also proposed in this paper. Exploiting the bandwidth efficient orthogonal frequency division modulation (OFDM), multiple transmit antennas and large frequency selectivity offered by typical low mobility indoor environments, the proposed space-frequency turbo coded modulation performs within 2.5dB of the outage capacity for a variety of practical wideband multiple-input multiple-output (MIMO) radio channels.

Efficient packetised CDMA system for a high mobility urban environment

A CDMA system for a high mobility environment is considered. The radio channel examined is a multipath Rayleigh fading channel with intersymbol interference (ISI) applicable to a heavily built up urban environment. In such environments, the maximum number of simultaneous users is seriously limited by the hostile propagation conditions and the rapidly changing multiple access interference (MAI) from other users. This paper examines a practical implementation of an improved LMS-LMMSE receiver for wideband CDMA systems operating over a fast fading channel. The numerical results with very short spreading sequences demonstrate that the modified adaptive algorithm improves the performance of the adaptive LMMSE receiver remarkably in fading channels. The performance is compared to that of a standard LMS receiver.

Implementation of Ultra-Fast Polar Decoders

Polar codes are used in the 5G standard, and due to their low-complexity decoding algorithm and the ability to achieve symmetric channel capacity, they are receiving increased research interest for beyond 5G networks as well. In our recent work, we have introduced new subcodes and their decoding algorithms for fast decoding of polar codes with short to moderate blocklengths. In this paper, we study the algorithms from a hardware implementation point of view. Moreover, some new subcodes are also introduced to further prune the binary decoder tree. A hardware architecture of the algorithms using resource sharing and multiplexing techniques is presented. The FPGA implementation results show that a polar code of length <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$N=102A$</tex> , rate <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathcal{R}=1/2$</tex> with two Processing Element <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(P_{\mathrm{e}})$</tex> values of 128 and 256 achieves 42.5% and 47.6% lower latency comparing to the original Fast-SSC algorithm. The proposed decoder architecture offers an information throughput of 393 Mbps for the same code with <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P_{e}=128$</tex> .

A 6G White Paper on Connectivity for Remote Areas

In many places all over the world rural and remote areas lack proper connectivity that has led to increasing digital divide. These areas might have low population density, low incomes, etc., making them less attractive places to invest and operate connectivity networks. 6G could be the first mobile radio generation truly aiming to close the digital divide. However, in order to do so, special requirements and challenges have to be considered since the beginning of the design process. The aim of this white paper is to discuss requirements and challenges and point out related, identified research topics that have to be solved in 6G. This white paper first provides a generic discussion, shows some facts and discusses targets set in international bodies related to rural and remote connectivity and digital divide. Then the paper digs into technical details, i.e., into a solutions space. Each technical section ends with a discussion and then highlights identified 6G challenges and research ideas as a list.

Partially Permuted Multi-Trellis Belief Propagation for Polar Codes

Belief propagation (BP) is an iterative decoding algorithm for polar codes which can be parallelized effectively to achieve higher throughput. However, because of the presence of error floor due to cycles and stopping sets in the factor graph, the performance of the BP decoder is far from the performance of state of the art cyclic redundancy check (CRC) aided successive cancellation list (CA-SCL) decoders. It has been shown that successive BP decoding on multiple permuted factor graphs, which is called the multi-trellis BP decoder, can improve the error performance. However, when permuting the entire factor graph, since the decoder dismisses the information from the previous permutation, the number of iterations required is significantly larger than that of the standard BP decoder. In this work, we propose a new variant of the multi-trellis BP decoder which permutes only a subgraph of the original factor graph. This enables the decoder to retain information of variable nodes in the subgraphs, which are not permuted, reducing the required number of iterations needed in-between the permutations. As a result, the proposed decoder can perform permutations more frequently, hence being more effective in mitigating the effect of cycles which cause oscillation errors. Experimental results show that for a polar code with block length 1024 and rate 0.5 the error performance gain of the proposed decoder at the frame error rate of 10^(-6) is 0.25 dB compared to multi-trellis decoder based on full permutations. This performance gain is achieved along with reduced latency in terms of the number of iterations.

Multi-Timescale Resource Reservation and Allocation Through Meta Distribution for Network Operators to Enable eMBB and URLLC Coexistence

Secrecy Outage Performance of MIMO Wiretap Channels with Multiple Jamming Signals

In this paper, assuming an interference-limited eavesdropper scenario, the secrecy outage performance ofmultiple-input multiple-output wiretap channels with transmit antenna selection is investigated. Considering that the transmitter (Tx) and the receiver (Rx) are equipped with NA and NB antennas, respectively, while the passive eavesdropper is set with NE antennas, closed-form expressions for the secrecy outage probability and non-zerosecrecy rate are derived. In our analysis, both maximal-ratio combining (MRC) and selection combining (SC) are employed at the Rx, while the eavesdropper uses a MRC scheme. The derived outage expressions hold for arbitrary power distributed jamming signals and some of their special cases (i.e., distinct power distributed and equal power distributed jamming signals) are presented. An asymptotic analysis is carried out to show the impact of the number of jamming signals and number of antennas on the secrecy outage performance. Interestingly, our results show thatthe diversity order equals to min(M,NANB), with M denoting the number of jamming signals. This allows us to conclude that the number of jamming signals at the eavesdropper limits the secrecy performance via diversity such that a high number of antennas does not imply necessarily in a performance improvement, unless for a large number of jamming signals.