Hamdi Joudeh

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 multi-user multiple input simgle output (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 when CSIT errors decay with increased SNR. In this paper, 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 coupled with the weighted minimum mean square error 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 with conventional transmission with no rate-splitting.

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.

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 users 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 with conventional designs (NoRS). For the special case of nonscaling CSIT (e.g., fixed number of feedback bits), and contrary to NoRS, RS can achieve a nonsaturating 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.

Rate splitting for MIMO wireless networks: a promising PHY-layer strategy for LTE evolution

MIMO processing plays a central part in 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 toward enormous spectral and energy efficiency benefits in multiuser MIMO networks lies in a huge demand for accurate 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 article, we depart from this conventional approach and introduce 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, the impact on standard specifications, and operational challenges are also discussed.

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.

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.

AMMSE optimization for multiuser MISO systems with imperfect CSIT and perfect CSIR

In this paper, we consider the design of robust linear precoders for MU-MISO systems where users have perfect Channel State Information (CSI) while the BS has partial CSI. In particular, the BS has access to imperfect estimates of the channel vectors, in addition to the covariance matrices of the estimation error vectors. A closed-form expression for the Average Minimum Mean Square Error (AMMSE) is obtained using the second order Taylor Expansion. This approximation is used to formulate two fairness-based robust design problems: a maximum AMMSE-constrained problem and a power-constrained problem. We propose an algorithm based on convex optimization techniques to address the first problem, while the second problem is tackled by exploiting the close relationship between the two problems, in addition to their monotonie natures.

Achieving max-min fairness for MU-MISO with partial CSIT: A multicast assisted transmission

We address the max-min fairness design problem for a MU-MISO system with partial Channel State Information (CSI) at the Base Station (BS), consisting of an imperfect channel estimate and statistical knowledge of the estimation error, and perfect CSI at the receivers. The objective is to maximize the minimum Average Rate (AR) among users subject to a transmit power constraint. An unconventional transmission scheme is adopted where the Base Station (BS) transmits a common message in addition to the conventional private messages. In situations where the CSIT is not accurate enough to perform interference nulling, individual rates are assisted by allocating parts of the common message to different users according to their needs. The AR problem is transformed into an augmented AverageWeighted Mean Square Error (AWMSE) problem, solved using Alternating Optimization (AO). The benefits of incorporating the common message are demonstrated through simulations.

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 degrees of freedom (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.

System value-based optimum spreading sequence selection for high-speed downlink packet access (HSDPA) MIMO

This article proposes the use of system value-based optimization with a symbol-level minimum mean square error equalizer and a successive interference cancellation which achieves a system value upper bound (UB) close to the Gaussian UB for the high-speed downlink packet access system without affecting any significant computational cost. It is shown that by removing multi-code channels with low gains, the available energy is more efficiently used, and a higher system throughput is observed close to the system value UB. The performance of this developed method will be comparable to the orthogonal frequency division multiplexing-based long-term evolution scheme, without the need to build any additional infrastructure. Hence, reduce the cost of the system to both operators and consumers without sacrificing quality.