Hadi Baligh

Sparse code multiple access

Multicarrier CDMA is a multiplexing approach in which modulated QAM symbols are spread over multiple OFDMA tones by using a generally complex spreading sequence. Effectively, a QAM symbol is repeated over multiple tones. Low density signature (LDS) is a version of CDMA with low density spreading sequence allowing us to take advantage of a near optimal ML receiver with practically feasible complexity. In this paper, we propose a new multiple access scheme so called sparse code multiple access (SCMA) which still enjoys the low complexity reception technique but with better performance compared to LDS. In SCMA, the procedure of bit to QAM symbol mapping and spreading are combined together and incoming bits are directly mapped to a multidimensional codeword of an SCMA codebook set. Each layer or user has its dedicated codebook. Shaping gain of a multidimensional constellation is the main source of the performance improvement in comparison to the simple repetition of QAM symbols in LDS. In general, SCMA codebook design is an optimization problem. A systematic sub-optimal approach is proposed here for SCMA codebook design.

Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogeneous Networks

We consider the interference management problem in a multicell MIMO heterogeneous network. Within each cell there is a large number of distributed micro/pico base stations (BSs) that can be potentially coordinated for joint transmission. To reduce coordination overhead, we consider user-centric BS clustering so that each user is served by only a small number of (potentially overlapping) BSs. Thus, given the channel state information, our objective is to jointly design the BS clustering and the linear beamformers for all BSs in the network. In this paper, we formulate this problem from a {sparse optimization} perspective, and propose an efficient algorithm that is based on iteratively solving a sequence of group LASSO problems. A novel feature of the proposed algorithm is that it performs BS clustering and beamformer design jointly rather than separately as is done in the existing approaches for partial coordinated transmission. Moreover, the cluster size can be controlled by adjusting a single penalty parameter in the nonsmooth regularized utility function. The convergence of the proposed algorithm (to a stationary solution) is guaranteed, and its effectiveness is demonstrated via extensive simulation.

SCMA Codebook Design

Multicarrier CDMA is a multiple access scheme in which modulated QAM symbols are spread over OFDMA tones by using a generally complex spreading sequence. Effectively, a QAM symbol is repeated over multiple tones. Low density signature (LDS) is a version of CDMA with low density spreading sequences allowing us to take advantage of a near optimal message passing algorithm (MPA) receiver with practically feasible complexity. Sparse code multiple access (SCMA) is a multi-dimensional codebook-based non-orthogonal spreading technique. In SCMA, the procedure of bit to QAM symbol mapping and spreading are combined together and incoming bits are directly mapped to multi-dimensional codewords of SCMA codebook sets. Each layer has its dedicated codebook. Shaping gain of a multi-dimensional constellation is one of the main sources of the performance improvement in comparison to the simple repetition of QAM symbols in LDS. Meanwhile, like LDS, SCMA enjoys the low complexity reception techniques due to the sparsity of SCMA codewords. In this paper a systematic approach is proposed to design SCMA codebooks mainly based on the design principles of lattice constellations. Simulation results are presented to show the performance gain of SCMA compared to LDS and OFDMA.

SCMA for downlink multiple access of 5G wireless networks

Sparse code multiple access (SCMA) is a new frequency domain non-orthogonal multiple-access technique which can improve spectral efficiency of wireless radio access. With SCMA, different incoming data streams are directly mapped to codewords of different multi-dimensional cookbooks, where each codeword represents a spread transmission layer. Multiple SCMA layers share the same time-frequency resources of OFDMA. The sparsity of codewords makes the near-optimal detection feasible through iterative message passing algorithm (MPA). Such low complexity of multi-layer detection allows excessive codeword overloading in which the dimension of multiplexed layers exceeds the dimension of codewords. Optimization of overloading factor along with modulation-coding levels of layers provides a more flexible and efficient link-adaptation mechanism. On the other hand, the signal spreading feature of SCMA can improve link-adaptation as a result of less colored interference. In this paper a technique is developed to enable multi-user SCMA (MU-SCMA) for downlink wireless access. User pairing, power sharing, rate adjustment, and scheduling algorithms are designed to improve the downlink throughput of a heavily loaded network. The advantage of SCMA spreading for lightly loaded networks is also evaluated.

Low Complexity Techniques for SCMA Detection

Sparse code multiple access (SCMA) is a codebook- based non-orthogonal multiplexing technique. In SCMA, the procedure of bit to QAM symbol mapping and spreading of CDMA are combined together and incoming bits are directly mapped to multi-dimensional codewords of SCMA codebook sets. Due to the sparse nature of codewords, SCMA enjoys the low complexity reception, taking advantage of a near optimal message passing algorithm (MPA). This makes SCMA a candidate for supporting massive connectivity in future 5G networks, where the number of users can potentially be higher than the codeword length (spreading factor). To this end, more efficient reception techniques are needed on top of what MPA delivers. In this paper, some complexity reduction techniques are presented to further reduce the SCMA decoding complexity. These techniques are considered from two perspectives: i) transmitter-side technique, by designing SCMA codebooks with a specific structure providing low complexity of detections, and ii) low complexity decoding techniques taking advantage of the SCMA codebook structure. The proposed techniques are evaluated in terms of both complexity and performance. It is shown that significant amount of complexity reduction is possible using the proposed techniques with negligible performance penalty, which paves the way of supporting various applications in future 5G systems using SCMA.

Joint transceiver design and user grouping in a MIMO interfering broadcast channel

Consider a MIMO interfering broadcast channel (multi-cellular network) where each base station transmits signals to the users in its own cell. The basic problem is to design linear transmit/receive beamformers that can maximize the system throughput in the presence of both inter and intra cell interference. To ensure user fairness in the system, we consider the joint user grouping, power allocation and beamformer design problem by maximizing a system utility which aims to strike a suitable trade-off between the user fairness and system throughput. We propose a simple algorithm to solve this nonconcave utility maximization problem and establish its convergence. The simulation results show that the proposed algorithm significantly outperforms the SVD-MMSE method and some other approaches in terms of system throughput while respecting user fairness. The proposed algorithm exhibits fast convergence and is amenable to distributed implementation with limited information exchange.

Cross-Layer Provision of Future Cellular Networks: A WMMSE-based approach

To cope with the growing demand for wireless data and to extend service coverage, future fifth-generation (5G) networks will increasingly rely on the use of low-power nodes to support massive connectivity in a diverse set of applications and services. To this end, virtualized and mass-scale cloud architectures are proposed as promising technologies for 5G in which all the nodes are connected via a backhaul network and managed centrally by such cloud centers. The significant computing power made available by the cloud technologies has enabled the implementation of sophisticated signal processing algorithms, especially by way of parallel processing, for both interference management and network provision. The latter two are among the major signal processing tasks for 5G due to an increased level of frequency sharing, node density, interference, and network congestion. This article outlines several theoretical and practical aspects of joint interference management and network provisioning for future 5G networks. A cross-layer optimization framework is proposed for joint user admission, user-base station (BS) association, power control, user grouping, transceiver design, as well as routing and flow control. We show that many of these cross-layer tasks can be treated in a unified way and implemented in a parallel manner using an efficient algorithmic framework called weighted minimum mean squared error (WMMSE). Some recent developments in this area are highlighted and future research directions are identified.

Radio access virtualization: Cell follows user

Virtual radio access (VRA) technology wherein groups of cooperative transmit points (TPs) form virtual TPs (VTPs) to serve user equipments (UEs) continue to be a thriving subject of research in future generations of wireless networks. In this paper, we propose a technique that uses UE-centric metrics to provide multiple partitions of a wireless network into VTP sets. Our technique guarantees that all UEs enjoy a required gain in at least one VTP; effectively eliminating the edge UE experience in the network. To further enhance the performance of the proposed VRA technique in practical scenarios wherein there is a large load imbalance in the network, we also introduce a new concept of soft UE-TP association in which each UE is partially associated with multiple TPs. The use of our soft association concept when forming VTP sets facilitates load-balancing among various TPs. Finally, a technique is also offered to select the best VTP set at each scheduling resource unit. Numerical simulations are used to demonstrate the performance of our virtualization techniques.

Long-term transmit point association for coordinated multipoint transmission by stochastic optimization

We consider the problem of long-term transmit point (TP) association in a heterogeneous network where CoMP (Coordinated Multiple Point) transmission scheme is supported. More specifically, the TP association is designed for a relatively long time period where only channel statistics is available, and each user equipment(UE) could be associated with a number of TPs. We formulate the problem as a two-stage stochastic optimization problem with ℓ1-norm regularization, and propose a stochastic sparse WMMSE (SS-WMMSE) algorithm to solve it. The simulation results show that the proposed algorithm significantly outperforms the traditional deterministic approach.

Modified Tomlinson-Harashima Precoding for Downlink MU-MIMO Channel with Arbitrary Precoder

Tomlinson-Harashima precoding (THP) for downlink MU-MIMO channel can be modeled as user signal perturbation (constellation expansion) followed by linear precoding. The effective linear precoder in standard THP is merely a function of the MU-MIMO channel, which does not provide the flexibility for user power allocation. A modified THP algorithm is proposed so that the effective linear precoder can be arbitrary. As a special case, zero-forcing THP (ZF-THP) with arbitrary user power allocation is considered for which optimal user power allocation is derived to maximize the weighted sum-rate of users.