arXiv subjects

Hamdi Joudeh

Publications and source records attributed to Hamdi Joudeh.

At least 37 records · Page 2Linked to original sources

arXiv2019

On the Optimality of Treating Inter-Cell Interference as Noise: Downlink Cellular Networks and Uplink-Downlink Duality

We consider the information-theoretic optimality of treating inter-cell interference as noise (multi-cell TIN) in downlink cellular networks. We focus on scenarios modeled by the Gaussian interfering broadcast channel (IBC), comprising $K$ mutually interfering Gaussian broadcast channels (BCs), each formed by a base station communicating independent messages to an arbitrary number of users. We establish a new power allocation duality between the IBC and its dual interfering multiple access channel (IMAC), which entails that the corresponding generalized degrees-of-freedom regions achieved through multi-cell TIN and power control (TINA regions) for both networks are identical. As by-products of this duality, we obtain an explicit characterization of the IBC TINA region from a previously established characterization of the IMAC TINA region; and identify a multi-cell convex-TIN regime in which the IBC TINA region is a polyhedron (hence convex) without the need for time-sharing. We then identify a smaller multi-cell TIN regime in which the IBC TINA region is optimal and multi-cell TIN achieves the entire capacity region of the IBC, up to a constant gap. This is accomplished by deriving a new genie-aided outer bound for the IBC, that reveals a novel BC-type order that holds amongst users in each constituent BC (or cell) under inter-cell interference, which in turn is not implied by previously known BC-type orders (i.e. degraded, less noisy and more capable orders). The multi-cell TIN regime that we identify for the IBC coincides with a corresponding multi-cell TIN regime previously identified for the IMAC, hence establishing a comprehensive uplink-downlink duality of multi-cell TIN in the GDoF (and approximate capacity) sense.

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arXiv2019

Centralized and Decentralized Cache-Aided Interference Management in Heterogeneous Parallel Channels

We consider the problem of cache-aided interference management in a network consisting of $K_{\mathrm{T}}$ single-antenna transmitters and $K_{\mathrm{R}}$ single-antenna receivers, where each node is equipped with a cache memory. Transmitters communicate with receivers over two heterogenous parallel subchannels: the P-subchannel for which transmitters have perfect instantaneous knowledge of the channel state, and the N-subchannel for which the transmitters have no knowledge of the instantaneous channel state. Under the assumptions of uncoded placement and separable one-shot linear delivery over the two subchannels, we characterize the optimal degrees-of-freedom (DoF) to within a constant multiplicative factor of $2$. We extend the result to a decentralized setting in which no coordination is required for content placement at the receivers. In this case, we characterize the optimal one-shot linear DoF to within a factor of $3$.

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arXiv2019

On the Optimality of Treating Inter-Cell Interference as Noise in Uplink Cellular Networks

In this paper, we explore the information-theoretic optimality of treating interference as noise (TIN) in cellular networks. We focus on uplink scenarios modeled by the Gaussian interfering multiple access channel (IMAC), comprising $K$ mutually interfering multiple access channels (MACs), each formed by an arbitrary number of transmitters communicating independent messages to one receiver. We define TIN for this setting as a scheme in which each MAC (or cell) performs a power-controlled version of its capacity-achieving strategy, with Gaussian codebooks and successive decoding, while treating interference from all other MACs (i.e. inter-cell interference) as noise. We characterize the generalized degrees-of-freedom (GDoF) region achieved through the proposed TIN scheme, and then identify conditions under which this achievable region is convex without the need for time-sharing. We then tighten these convexity conditions and identify a regime in which the proposed TIN scheme achieves the entire GDoF region of the IMAC and is within a constant gap of the entire capacity region.

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arXiv2019

DoF Region of the MISO BC with Partial CSIT: Proof by Inductive Fourier-Motzkin Elimination

We provide a fresh perspective on the problem of characterizing the DoF region of the $K$-user MISO BC with arbitrary levels of partial CSIT. In a previous achievability proof, Piovano and Clerckx characterized all faces describing a polyhedral outer bound region, and then with the aid of mathematical induction, prescribed a scheme based on rate-splitting with flexible assignment of common DoF and power levels to achieve each such face. We propose an alternative approach in which we deal directly with the region achievable through rate-splitting and employ a Fourier-Motzkin procedure to eliminate all auxiliary variables, hence reducing the achievable region to the known outer bound. A key insight emerging from our proof is that tuning only one power variable, as well as assigning the common DoF, is sufficient to achieve the entire DoF region, as opposed to $K$ power variables previously employed.

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arXiv2019

On Multi-Cell Uplink-Downlink Duality with Treating Inter-Cell Interference as Noise

We consider the information-theoretic optimality of treating inter-cell interference as noise in downlink cellular networks modeled as Gaussian interfering broadcast channels. Establishing a new uplink-downlink duality, we cast the problem in Gaussian interfering broadcast channels to that in Gaussian interfering multiple access channels, and characterize an achievable GDoF region under power control and treating inter-cell interference as (Gaussian) noise. We then identify conditions under which this achievable GDoF region is optimal.

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arXiv2018

Generalized Degrees of Freedom of the Symmetric Cache-Aided MISO Broadcast Channel with Partial CSIT

We consider the cache-aided MISO broadcast channel (BC) in which a multi-antenna transmitter serves $K$ single-antenna receivers, each equipped with a cache memory. The transmitter has access to partial knowledge of the channel state information. For a symmetric setting, in terms of channel strength levels, partial channel knowledge levels and cache sizes, we characterize the generalized degrees of freedom (GDoF) up to a constant multiplicative factor. The achievability scheme exploits the interplay between spatial multiplexing gains and coded-multicasting gain. On the other hand, a cut-set-based argument in conjunction with a GDoF outer bound for a parallel MISO BC under channel uncertainty are used for the converse. We further show that the characterized order-optimal GDoF is also attained in a decentralized setting, where no coordination is required for content placement in the caches.

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arXiv2018

On the Optimality of Treating Interference as Noise for Interfering Multiple Access Channels

In this paper, we look at the problem of treating interference as noise (TIN) in the Gaussian interfering multiple access channel (IMAC). The considered network comprises $K$ mutually interfering multiple access channels (MACs), each consisting of two transmitters communicating independent messages to one receiver. We define the TIN scheme for this channel as one in which each MAC performs a power controlled version of its capacity-achieving strategy while treating interference from all other MACs as noise. We characterize an achievable generalized degrees-of-freedom (GDoF) region under the TIN scheme and identify a regime of parameters (in terms of channel strength levels) where this region is optimal.

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arXiv2018

SWIPT Signalling over Complex AWGN Channels with Two Nonlinear Energy Harvester Models

Simultaneous Wireless Information and Power Transfer (SWIPT) is subject to nonlinearity at the energy harvester that leads to significant changes to transmit signal designs compared to conventional wireless communications. In this paper, the capacity of a discrete time, memoryless and complex Additive White Gaussian Noise (AWGN) channel in the presence of a nonlinear energy harvester at the receiver is studied. Considering the two common nonlinear energy harvester models introduced in the literature, two sets of constraints are considered. First the capacity is studied under average power (AP), peak amplitude (PA) and receiver delivery power (RDP) constraints. The RDP constraint is modelled as a linear combination of even-moment statistics of the channel input being larger than a threshold. It is shown that the capacity of an AWGN channel under AP and RDP constraints is the same as the capacity of an AWGN channel under an AP constraint, however, depending on the two constraints, it can be either achieved or arbitrarily approached. It is also shown that under AP, PA and RDP constraints, the amplitude of the optimal inputs is discrete with a finite number of mass points. Next, the capacity is studied under AP, PA and output outage probability (OOP) constraints. OOP is modelled as satisfying a certain probability inequality for the amplitude of the received signal being outside of a given interval. Similarly, it is shown that the amplitude of the optimal input is discrete with a finite number of mass points.

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arXiv2017

On the DoF of Parallel MISO BCs with Partial CSIT: Total Order and Separability

We study the degrees of freedom (DoF) of a $K$-user parallel MISO broadcast channel with arbitrary levels of partial CSIT over each subchannel. We derive a sum-DoF upperbound which depends on the average CSIT quality of each user. This upperbound is shown to be tight under total order, i.e. when the order of users with respect to their CSIT qualities is preserved over all subchannels. In this case, it is shown that separate coding over each subchannel is optimum in a sum-DoF sense.

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arXiv2017

Rate-Splitting for Max-Min Fair Multigroup Multicast Beamforming in Overloaded Systems

In this paper, we consider the problem of achieving max-min fairness amongst multiple co-channel multicast groups through transmit beamforming. We explicitly focus on overloaded scenarios in which the number of transmitting antennas is insufficient to neutralize all inter-group interference. Such scenarios are becoming increasingly relevant in the light of growing low-latency content delivery demands, and also commonly appear in multibeam satellite systems. We derive performance limits of classical beamforming strategies using DoF analysis unveiling their limitations; for example, rates saturate in overloaded scenarios due to inter-group interference. To tackle interference, we propose a strategy based on degraded beamforming and successive interference cancellation. While the degraded strategy resolves the rate-saturation issue, this comes at a price of sacrificing all spatial multiplexing gains. This motivates the development of a unifying strategy that combines the benefits of the two previous strategies. We propose a beamforming strategy based on rate-splitting (RS) which divides the messages intended to each group into a degraded part and a designated part, and transmits a superposition of both degraded and designated beamformed streams. The superiority of the proposed strategy is demonstrated through DoF analysis. Finally, we solve the RS beamforming design problem and demonstrate significant performance gains through simulations.

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arXiv2017

On Coded Caching in the Overloaded MISO Broadcast Channel

This work investigates the interplay of coded caching and spatial multiplexing in an overloaded Multiple-Input-Single-Output (MISO) Broadcast Channel (BC), i.e. a system where the number of users is greater than the number of transmitting antennas. On one hand, coded caching uses the aggregate global cache memory of the users to create multicasting opportunities. On the other hand, multiple antennas at the transmitter leverage the available CSIT to transmit multiple streams simultaneously. In this paper, we introduce a novel scheme which combines both the gain derived from coded-caching and spatial multiplexing and outperforms existing schemes in terms of delivery time and CSIT requirement.

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arXiv2016

Overloaded Multiuser MISO Transmission with Imperfect CSIT

A required feature for the next generation of wireless communication networks will be the capability to serve simultaneously a large number of devices with heterogeneous CSIT qualities and demands. In this paper, we consider the overloaded MISO BC with two groups of CSIT qualities. We propose a transmission scheme where degraded symbols are superimposed on top of spatially-multiplexed symbols. The developed strategy allows to serve all users in a non-orthogonal manner and the analysis shows an enhanced perfomance compared to existing schemes. Moreover, optimality in a DoF sense is shown.

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arXiv2016

Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach

This paper considers the Sum-Rate (SR) maximization problem in downlink MU-MISO systems under imperfect Channel State Information at the Transmitter (CSIT). Contrary to existing works, we consider a rather unorthodox transmission scheme. In particular, the message intended to one of the users is split into two parts: a common part which can be recovered by all users, and a private part recovered by the corresponding user. On the other hand, the rest of users receive their information through private messages. This Rate-Splitting (RS) approach was shown to boost the achievable Degrees of Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS strategy is married with linear precoder design and optimization techniques to achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs. Precoders are designed based on partial CSIT knowledge by solving a stochastic rate optimization problem using means of Sample Average Approximation (SAA) coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical results show that in addition to the ESR gains, the benefits of RS also include relaxed CSIT quality requirements and enhanced achievable rate regions compared to conventional transmission with NoRS.

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arXiv2016

Robust Transmission in Downlink Multiuser MISO Systems: A Rate-Splitting Approach

We consider a downlink multiuser MISO system with bounded errors in the Channel State Information at the Transmitter (CSIT). We first look at the robust design problem of achieving max-min fairness amongst users (in the worst-case sense). Contrary to the conventional approach adopted in literature, we propose a rather unorthodox design based on a Rate-Splitting (RS) strategy. Each user's message is split into two parts, a common part and a private part. All common parts are packed into one super common message encoded using a public codebook, while private parts are independently encoded. The resulting symbol streams are linearly precoded and simultaneously transmitted, and each receiver retrieves its intended message by decoding both the common stream and its corresponding private stream. For CSIT uncertainty regions that scale with SNR (e.g. by scaling the number of feedback bits), we prove that a RS-based design achieves higher max-min (symmetric) Degrees of Freedom (DoF) compared to conventional designs (NoRS). For the special case of non-scaling CSIT (e.g. fixed number of feedback bits), and contrary to NoRS, RS can achieve a non-saturating max-min rate. We propose a robust algorithm based on the cutting-set method coupled with the Weighted Minimum Mean Square Error (WMMSE) approach, and we demonstrate its performance gains over state-of-the art designs. Finally, we extend the RS strategy to address the Quality of Service (QoS) constrained power minimization problem, and we demonstrate significant gains over NoRS-based designs.

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arXiv2016

A Rate-Splitting Strategy for Max-Min Fair Multigroup Multicasting

We consider the problem of transmit beamforming to multiple cochannel multicast groups. The conventional approach is to beamform a designated data stream to each group, while treating potential inter-group interference as noise at the receivers. In overloaded systems where the number of transmit antennas is insufficient to perform interference nulling, we show that inter-group interference dominates at high SNRs, leading to a saturating max-min fair performance. We propose a rather unconventional approach to cope with this issue based on the concept of Rate-Splitting (RS). In particular, part of the interference is broadcasted to all groups such that it is decoded and canceled before the designated beams are decoded. We show that the RS strategy achieves significant performance gains over the conventional multigroup multicast beamforming strategy.

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arXiv2016

Rate Splitting for MIMO Wireless Networks: A Promising PHY-Layer Strategy for LTE Evolution

MIMO processing plays a central part towards the recent increase in spectral and energy efficiencies of wireless networks. MIMO has grown beyond the original point-to-point channel and nowadays refers to a diverse range of centralized and distributed deployments. The fundamental bottleneck towards enormous spectral and energy efficiency benefits in multiuser MIMO networks lies in a huge demand for accurate channel state information at the transmitter (CSIT). This has become increasingly difficult to satisfy due to the increasing number of antennas and access points in next generation wireless networks relying on dense heterogeneous networks and transmitters equipped with a large number of antennas. CSIT inaccuracy results in a multi-user interference problem that is the primary bottleneck of MIMO wireless networks. Looking backward, the problem has been to strive to apply techniques designed for perfect CSIT to scenarios with imperfect CSIT. In this paper, we depart from this conventional approach and introduce the readers to a promising strategy based on rate-splitting. Rate-splitting relies on the transmission of common and private messages and is shown to provide significant benefits in terms of spectral and energy efficiencies, reliability and CSI feedback overhead reduction over conventional strategies used in LTE-A and exclusively relying on private message transmissions. Open problems, impact on standard specifications and operational challenges are also discussed.

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arXiv2016

A Rate-Splitting Approach To Robust Multiuser MISO Transmission

For multiuser MISO systems with bounded uncertainties in the Channel State Information (CSI), we consider two classical robust design problems: maximizing the minimum rate subject to a transmit power constraint, and power minimization under a rate constraint. Contrary to conventional strategies, we propose a Rate-Splitting (RS) strategy where each message is divided into two parts, a common part and a private part. All common parts are packed into one super common message encoded using a shared codebook and decoded by all users, while private parts are independently encoded and retrieved by their corresponding users. We prove that RS-based designs achieve higher max-min Degrees of Freedom (DoF) compared to conventional designs (NoRS) for uncertainty regions that scale with SNR. For the special case of non-scaling uncertainty regions, RS contrasts with NoRS and achieves a non-saturating max-min rate. In the power minimization problem, RS is shown to combat the feasibility problem arising from multiuser interference in NoRS. A robust design of precoders for RS is proposed, and performance gains over NoRS are demonstrated through simulations.

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arXiv2015

Sum Rate Maximization for MU-MISO with Partial CSIT using Joint Multicasting and Broadcasting

In this paper, we consider a MU-MISO system where users have highly accurate Channel State Information (CSI), while the Base Station (BS) has partial CSI consisting of an imperfect channel estimate and statistical knowledge of the CSI error. With the objective of maximizing the Average Sum Rate (ASR) subject to a power constraint, a special transmission scheme is considered where the BS transmits a common symbol in a multicast fashion, in addition to the conventional private symbols. This scheme is termed Joint Multicasting and Broadcasting (JMB). The ASR problem is transformed into an augmented Average Weighted Sum Mean Square Error (AWSMSE) problem which is solved using Alternating Optimization (AO). The enhanced rate performance accompanied with the incorporation of the multicast part is demonstrated through simulations.

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