Igor M. Guerreiro

Sequence-Based Rendezvous for Dynamic Spectrum Access

In the context of dynamic spectrum access (DSA), rendezvous refers to the ability of two or more radios to meet and establish a link on a common channel. In decentralized networks, this is often accomplished by each radio visiting potential channels in random fashion, in a process that we call blind random rendezvous. In this work, we propose the use of sequences that determine the order with which radios visit potentially available channels. Through sequence-based rendezvous, it is possible to: (i) establish an upper bound to the time to rendezvous (TTR); (ii) establish a priority order for channels in which rendezvous occurs; (Hi) reduce the expected TTR as compared to random rendezvous. We provide an example of a family of sequences and derive the expected time-to- rendezvous using this method. We also describe how the method can be adopted when one or more primary users are detected in the channels of interest.

A distributed approach to precoder selection using factor graphs for wireless communication networks

This paper addresses distributed parameter coordination methods for wireless communication systems. This proposes a method based on a message-passing algorithm, namely min-sum algorithm, on factor graphs for the application of precoder selection. Two particular examples of precoder selection are considered: transmit antenna selection and beam selection. Evaluations on the potential of such an approach in a wireless communication network are provided, and its performance and convergence properties are compared with those of a baseline selfish/greedy approach. Simulation results for the precoder selection examples are presented and discussed, which show that the graph-based technique generally obtains gain in sum rate over the greedy approach at the cost of a larger message size. Besides, the proposed method usually reaches the global optima in an efficient manner. Methods of improving the rate of convergence of the graph-based distributed coordination technique and reducing its associated message size are therefore important topics for wireless communication networks.

A graph-based approach for distributed parameter coordination in wireless communication networks

This paper addresses distributed parameters coordination methods for wireless communication systems founded on message-passing algorithms on graphs. This work provides evaluations on the potential of such an approach in a wireless communication network, and compares its performance and convergence properties with those of a baseline selfish/greedy approach. Simulation results for an example application, i.e. frequency reuse planning, is presented and discussed. The results show that graph-based techniques generally have higher probability of reaching (near) optimal solution than the greedy approach, though its rate of convergence tends to be slower and the message size is typically larger. Methods of improving the rate of convergence of graph-based distributed coordination techniques and reducing the associated message size are therefore important topics for future studies.

A distributed approach for antenna subset selection in MIMO systems

In this paper a novel antenna subset selection algorithm is proposed using a distributed approach. It is assumed that each base station in a group of base stations is linked to an associated terminal as a receiver-transmitter pair. These receiver-transmitter pairs reuse channel resources, such that each mobile terminal represents a source of other-cell interference (also referred to as multi-user interference or MUI) for other mobile terminals in neighboring cells that are reusing all or some of the same channel resources. Accordingly, the base stations implement a gaming-based algorithm to mitigate MUI for the multiple-input-multiple-output (MIMO) uplink signals received from their associated mobile terminals. Simulation results show that the proposed algorithm has a good performance in terms of average error probability consisting of a solution concept based on Nash equilibrium (NE) points.

Adaptation with reduced-size message pass to precoder selection in multi-cell MIMO systems

This paper addresses the optimization of a multicell network where each cell needs to select precoding matrices for beamforming in a distributed way. A modified version of the adaptive min-sum algorithm that considers reduced-size messages in the message-passing procedure is proposed. The message-passing technique, where each message is reduced to convey only part of usual information, is applied to maximize the system throughput leading to a faster adaptation procedure. Simulation results show this reduction leads to a small average performance loss in system throughput of approximately 6%, while generally reduces the message size in about 73%. Also, the proposed method still outperforms the baseline greedy technique.

Precoder selection scheme based on message-passing approach: a practical perspective

This work addresses a distributed technique to precoding matrices coordination in a multi-cell network. We propose an iterative method based on a message-passing algorithm in factor graphs. Finite precoder codebooks for different MIMO setups are adopted for beam forming purposes. Conversely, practical cellular networks usually solve the precoder selection problem in a non-iterative manner based on the best response method. Nevertheless, this method may not provide a near-optimal solution. For more realistic results, the wireless channel is modeled based on measured data that comprises spatial correlation effects. Evaluations on the potential of such an approach are provided and its performance is compared with the selfish/greedy approach. The capability of reaching the globally optimal solution is evaluated, as well as its performance per iteration. Simulation results for the precoder selection example are presented and discussed, which show that the graph-based technique generally obtains gain in system capacity over both the non-iterative and selfish approaches. Besides, the proposed method usually reaches the global optima in an efficient manner in terms of signaling load.

Graph-based power-efficient beam sweep for initial synchronization

This paper addresses the problem of initial synchronization of users in an indoor mm-Wave scenario. By using a massive number of antenna elements at access nodes, the resulting beams have narrow beamwidth. However, the transmission of individual narrow beams may cause poor coverage in some areas as the energy is concentrated over the direction of their main lobes. To cope with that, a beam sweep procedure using phased arrays is adopted. Access nodes simultaneously transmit individual beams until a certain area of interest is thoroughly scanned. The goal is to find the minimum power setting by adjusting the individual power levels so that users over the scanned area can observe a minimum received power level. The problem is formulated as a total consumed power minimization, suitably modeled for the standard min-sum algorithm. The proposed graph-based algorithm features some modifications in the message computation to decrease computational complexity, and adopts a random message-passing scheduling to deal with convergence issues. Simulation results indicate that the proposed algorithm usually outperforms a baseline iterative one, consuming about 13% less power in a typical simulation setup adopted.

Power-efficient beam sweeping for initial synchronization in mm-Wave wireless networks

This paper addresses the problem of initial synchronization of users in an indoor mm-Wave scenario. With the use of a massive number of antenna elements at access nodes, the resulting beams have narrow beam width. However, the transmission of individual narrow beams may cause poor coverage in some areas as the energy is concentrated over the direction of their main lobes. To cope with that, a beam sweep procedure using phased arrays is adopted. Access nodes simultaneously transmit individual beams until a certain area of interest is thoroughly scanned. Then, distant points are covered as each beam can radiate energy using an individual transmit power. The goal is to find the minimum power setting by adjusting the individual power levels so that users over the scanned area can observe a minimum received power level. Due to the combinatorial nature and high dimensionality, this paper describes a non-iterative two-stage algorithm to perform the beam sweeping with moderate complexity, which is compared with a baseline iterative selfish algorithm. Preliminary simulation results indicate that the two-stage algorithm may perform at least equally well as the baseline approach in terms of total transmit power, consuming about 7% less power in the used simulation setup, and without suffering from any convergence issue.

Distributed Optimization Techniques in Wireless Communication Networks

This chapter addresses distributed parameter coordination methods for wireless communication systems. We present two distributed algorithms for the problem of precoder selection. The first and simplest method is the greedy solution in which each communication node in the network acts selfishly. The second method and the focus of this chapter is based on a message-passing algorithm, namely min-sum algorithm, in factor graphs. Three kinds of precoding codebook are considered: transmit antenna selection, fixed-beam selection, and LTE precoder selection. Evaluations on the potential of such an approach in a wireless communication network are provided and its performance and convergence properties are compared with those of a baseline selfish/greedy approach. Simulation results are presented and discussed, which show that the graph-based technique generally obtains gain in sum rate over the greedy approach at the cost of a larger message size. For instance, the percentage gain in sum rate over the greedy is about 33 % within 5 iterations in a 7-cell network considering single-layer LTE precoders. Besides, the graph-based method usually reaches the global optimum in a efficient manner. Methods of improving the rate of convergence of graph-based distributed coordination technique and reducing its associated message size are therefore important topics for wireless communication networks.