Yuri C. B. Silva

Linear Transmit Beamforming Techniques for the Multigroup Multicast Scenario

In the context of next-generation wireless systems, it is expected that services targeted at mass content distribution will become widely popular. Multicast services, such as audio/video streaming and mobile television, have the characteristic that the same information has to be transmitted to a group of recipients, which may include user terminals as well as relay stations, in the case of relaying networks. This paper deals with the problem of multigroup multicast beamforming for multiantenna wireless cellular networks, which assumes that multiple multicast groups can share the same resource. The intergroup interference, which appears due to the resource sharing, needs to be suppressed by the beamforming algorithms. In this paper, new linear transmit beamforming techniques are proposed, which aim to provide a reasonable tradeoff between performance and computational complexity. These techniques correspond to extensions of known algorithms, such as zero forcing (ZF), minimum mean square error (MMSE), and signal-to-interference-plus-noise ratio (SINR) balancing, to the multicast case. Furthermore, new ldquomulticast-awarerdquo techniques that take into account the peculiarities of multicast transmission are proposed to improve performance. To provide the necessary mathematical framework for the analysis, a novel general multigroup multicast system model is proposed as well.

PARAFAC-PARATUCK Semi-Blind Receivers for Two-Hop Cooperative MIMO Relay Systems

In two-hop amplify-and-forward (AF) relay systems, a source node sends information to one or several relay nodes that amplify and retransmit the received signals to a destination node, without decoding. Such AF relaying-based cooperative communications allow to improve communication reliability due to increased channel gains and space diversity at the destination node. In this paper, we consider a two-hop AF cooperative scheme, with a simplified Khatri-Rao space-time (KRST) coding at transmission (source). We show that the third-order tensor of signals received by the destination node satisfies a PARAFAC decomposition for the direct link, and a PARATUCK2 decomposition for the relay-assisted link. This tensorial modeling enables a joint semi-blind estimation of transmitted symbols and channels of both hops. Three receivers that combine these two tensor models in different ways are proposed. An identifiability study for these receivers is carried out, from which sufficient conditions for joint symbol and channel recovery are derived. The performance of these receivers is illustrated by means of simulation results, and a comparison is made with recent supervised approaches that allow to estimate channels and symbols in two separated steps. Besides a joint semi-blind channel/symbol estimation, our approach gives a better BER performance due to coding at the transmitter.

Adaptive Beamforming and Spatial Multiplexing of Unicast and Multicast Services

This paper evaluates and compares different adaptive antenna techniques applied in the context of multicast services and presents a methodology for performing the spatial multiplexing of both unicast and multicast users. It is seen that adaptive beamforming is able to provide good results even for large groups of multicast users. A fair multicast beamforming algorithm is proposed, which focuses on the performance of the worst multicast user and particularly benefits from scenarios with strong line-of-sight. Additionally, grouping strategies that allow the allocation of the same resources to unicast and multicast users, and which make use of the proposed spatial multiplexing procedure, are shown to be more efficient than allocating separate resources to unicast and multicast users

Power Allocation in Multi-Carrier Networks with Unicast and Multicast Services

Since the provision of both unicast and multicast services is expected for the next generation of multi-carrier wireless systems, the allocation of resources for this combination of services is a relevant topic, which may have a significant impact on the system performance. The focus of this work lies on the allocation of power to the different downlink subchannels of a multi-carrier system containing both unicast and multicast users. The power allocation problem is analyzed considering on the one hand the maximization of the sum throughput and on the other hand the maximization of the minimum SNR. The solution of the former is presented, which depends on numerical optimization, and an algorithm similar to the waterfilling hypothesis testing is proposed for reducing the processing time, while for the latter a closed-form solution is demonstrated. A simplified power allocation algorithm based on multicast group quality criteria is also evaluated and shown to approximate the maximal achievable performance under certain circumstances.

SINR Balancing Combined with SDMA Grouping in CoMP Systems

SDMA grouping algorithms are usually employed in order to find a suitable set of User Equipments (UEs) for spatial multiplexing. The largest SDMA group is not always the best SDMA group in a given transmission such that higher gains might be achieved by dynamically adjusting the SDMA group size. Besides, algorithms that balance the SINR among different links might ensure a certain level of link quality and so provide a more reliable communication for the scheduled UEs. This paper provides system-level analyses for strategies of Radio Resource Allocation in CoMP systems, which consider dynamic SDMA grouping, joint precoding and power allocation for SINR balancing. Our results show that Sequential Removal Algorithms and SINR balancing provide gains of system spectral efficiency.

Adaptive antenna techniques applied to multicast Services in wireless networks

This paper evaluates and compares different adaptive antenna techniques applied in the context of multicast services. Traditional unicast algorithms, such as the matched filter, zero-forcing, TomlinsonHarashima precoding, and switched fixed beams are formulated for the multicast case. Algorithms which try to improve the performance of the worst user within the multicast group are also analyzed and a new algorithm called USMF is proposed. It is seen that the techniques which treat all the users alike do not perform well when compared to those which focus on the worst user. The spatial correlation of the channel is shown to have a significant impact on the results. The presence of line-of-sight is verified to be beneficial to the performance of the proposed algorithm and the switched fixed beams. Other aspects, such as the transmitter/receiver design and the impact of the multicast group size, are investigated as well. Index Terms – Multicast services, transmit processing, adaptive antennas.

Downlink beamforming and SINR balancing for the simultaneous provision of unicast/multicast services

The provision of multicast services is a relevant feature within the context of the further evolution of cellular communication systems. The scope of this paper lies on the application of adaptive antenna arrays in order to allow for space division multiple access (SDMA) in a scenario with both unicast and multicast users. A sub-optimum algorithmic solution is proposed for the problem of maximizing the minimum SINR perceived by the unicast/multicast users (SINR balancing), while satisfying the transmit power constraint. It is based on the unicast-only solution, which has been extended to the unicast/multicast case. It is shown that the proposed low-complexity algorithm provides a reasonable approximation to the optimal solution, outperforming diagonalization-based procedures such as block diagonalization.

Combined performance of packet scheduling and smart antennas for data transmission in EGPRS

The capacity of GERAN is expected to be limited by interference, particularly in urban areas, and by the quality of service (QoS) requirements demanded by the users. Smart antenna arrays employing beamforming techniques, commonly known as adaptive antennas (AA), are an efficient technology in mitigating interference in urban areas with low azimuth spread. In EGPRS, the packet data service of GERAN, resource scheduling is responsible for multiplexing users on shared physical channels in order to best fulfill QoS requirements. By using more efficient scheduling algorithms, the resulting QoS is enhanced and, ultimately, it may be exchanged for capacity. In this work, the QoS and capacity gains provided by an AA system and two scheduling algorithms in several EGPRS system configurations are shown. Furthermore, it is demonstrated that, when combined, a tighter reuse scheme, a base station AA system, and an enhanced scheduling algorithm can result in a capacity gain of up to approximately 450% over the reference scenario.

Performance of Joint Antenna and User Selection Schemes for Interference Alignment in MIMO Interference Channels

In multiuser MIMO systems, the transmitter can select a subset of antennas and/or users which have good channel conditions to maximize the system throughput using various selection criteria. Furthermore, the Interference Alignment (IA) method, which is based on the concept of precoding, can provide interference free dimensions. It offers different trade-offs between complexity and performance. The basic idea of Interference Alignment consists in precoding the transmitted signals such that they are aligned at the receiver where they constitute interference, while at the same time disjointed from the desired signal. We analyze the performance of antenna selection and multiuser diversity together in order to allow opportunistic IA using chordal and Fubini-Study distances. Analyses and simulations verify the behavior of the proposed scheme.

Clustering-based Assignment within CoMP systems

More and more Coordinated Multi-Point (CoMP) systems are attracting interest as a means to improve the performance of conventional cellular networks, particularly thanks to the joint processing approach. However, the large amount of signaling and computer operations required deserves special attention regarding both backhaul and radio resources constraints. Partitioning the set of transmission points into clusters is likely to reduce this coordination cost, but the search for the best formations of clusters may lead to expressive further computational efforts. Herein we introduce a novel approach, the Clustering-based Assignment Algorithm (CbAA), to cluster dynamically the transmission points on the downlink in order to transmit coherently to multiple users. When compared to static clustering, the proposed CbAA provided expressive gains in terms of system spectral efficiency. Compared to state-of-the-art dynamic clustering approaches, CbAA can waive the exhaustive search over all possible formations as well as the repetitive precoder calculations during the clustering procedure.