Random Matrix Theory applied to the Estimation of Collision Multiplicities

This paper presents two techniques in order to estimate the collision multiplicity, i.e., the number of users involved in a collision [1]. This estimation step is a key task in multi-packet reception approaches and in collision resolution techniques. The two techniques are proposed for IEEE 802.11 networks but they can be used in any OFDM-based system. The techniques are based on recent advances in random matrix theory and rely on eigenvalue statistics. Provided that the eigenvalues of the covariance matrix of the observations are above a given threshold, signal eigenvalues can be separated from noise eigenvalues since their respective probability density functions are converging toward two different laws: a Gaussian law for the signal eigenvalues and a Tracy-Widom law for the noise eigenvalues. The first technique has been designed for the white noise case, and the second technique has been designed for the colored noise case. The proposed techniques outperform current estimation techniques in terms of mean square error. Moreover, this paper reveals that, contrary to what is generally assumed in current multi-packet reception techniques, a single observation of the colliding signals is far from being sufficient to perform a reliable estimation of the collision multiplicities

Estimation of Collision Multiplicities in IEEE 802.11-based WLANs

Abstract—Estimating the collision multiplicity (CM), i.e. the number of users involved in a collision, is a key task in multipacket reception (MPR) approaches and in collision resolution (CR) techniques. A new technique is proposed for IEEE 802.11 networks. The technique is based on recent advances in random matrix theory and rely on eigenvalue statistics. Provided that the eigenvalues of the covariance matrix of the observations are above a given threshold, signal eigenvalues can be separated from noise eigenvalues since their respective probability density functions are converging toward two different laws: a Gaussian law for the signal eigenvalues and a Tracy-Widom law for the noise eigenvalues. The proposed technique outperforms current estimation techniques in terms of underestimation rate. Moreover, this paper reveals that, contrary to what is generally assumed in current MPR techniques, a single observation of the colliding signals is far from being sufficient to perform a reliable CM estimation

Model Order Selection for Collision Multiplicity Estimation

The collision multiplicity (CM) is the number of users involved in a collision. The CM estimation is an essential step in multi-packet reception (MPR) techniques and in collision resolution (CR) methods. We propose two techniques to estimate collision multiplicities in the context of IEEE 802.11 networks. These two techniques have been initially designed in the context of source separation. The first estimation technique is based on eigenvalue statistics. The second technique is based on the exponentially embedded family (EEF). These two techniques outperform current estimation techniques in terms of underestimation rate (UNDER). The reason for this is twofold. First, current techniques are based on a uniform distribution of signal samples whereas the proposed methods rely on a Gaussian distribution. Second, current techniques use a small number of observations whereas the proposed methods use a number of observations much greater than the number of signals to be separated. This is in accordance with typical source separation techniques

Random Access Protocols for Massive MIMO

5G wireless networks are expected to support new services with stringent requirements on data rates, latency and reliability. One novel feature is the ability to serve a dense crowd of devices, calling for radically new ways of accessing the network. This is the case in machine-type communications, but also in urban environments and hotspots. In those use cases, the high number of devices and the relatively short channel coherence interval do not allow per-device allocation of orthogonal pilot sequences. This article motivates the need for random access by the devices to pilot sequences used for channel estimation, and shows that Massive MIMO is a main enabler to achieve fast access with high data rates, and delay-tolerant access with different data rate levels. Three pilot access protocols along with data transmission protocols are described, fulfilling different requirements of 5G services

Fair Coexistence of Scheduled and Random Access Wireless Networks: Unlicensed LTE/WiFi

We study the fair coexistence of scheduled and random access transmitters sharing the same frequency channel. Interest in coexistence is topical due to the need for emerging unlicensed LTE technologies to coexist fairly with WiFi. However, this interest is not confined to LTE/WiFi as coexistence is likely to become increasingly commonplace in IoT networks and beyond 5G. In this article we show that mixing scheduled and random access incurs and inherent throughput/delay cost, the cost of heterogeneity. We derive the joint proportional fair rate allocation, which casts useful light on current LTE/WiFi discussions. We present experimental results on inter-technology detection and consider the impact of imperfect carrier sensing.Comment: 14 pages, 8 figures, journa

Non-Orthogonal Signal and System Design for Wireless Communications

The thesis presents research in non-orthogonal multi-carrier signals, in which: (i) a new signal format termed truncated orthogonal frequency division multiplexing (TOFDM) is proposed to improve data rates in wireless communication systems, such as those used in mobile/cellular systems and wireless local area networks (LANs), and (ii) a new design and experimental implementation of a real-time spectrally efficient frequency division multiplexing (SEFDM) system are reported. This research proposes a modified version of the orthogonal frequency division multiplexing (OFDM) format, obtained by truncating OFDM symbols in the time-domain. In TOFDM, subcarriers are no longer orthogonally packed in the frequency-domain as time samples are only partially transmitted, leading to improved spectral efficiency. In this work, (i) analytical expressions are derived for the newly proposed TOFDM signal, followed by (ii) interference analysis, (iii) systems design for uncoded and coded schemes, (iv) experimental implementation and (v) performance evaluation of the new proposed signal and system, with comparisons to conventional OFDM systems. Results indicate that signals can be recovered with truncated symbol transmission. Based on the TOFDM principle, a new receiving technique, termed partial symbol recovery (PSR), is designed and implemented in software de ned radio (SDR), that allows efficient operation of two users for overlapping data, in wireless communication systems operating with collisions. The PSR technique is based on recovery of collision-free partial OFDM symbols, followed by the reconstruction of complete symbols to recover progressively the frames of two users suffering collisions. The system is evaluated in a testbed of 12-nodes using SDR platforms. The thesis also proposes channel estimation and equalization technique for non-orthogonal signals in 5G scenarios, using an orthogonal demodulator and zero padding. Finally, the implementation of complete SEFDM systems in real-time is investigated and described in detail

Successive interference cancellation in vehicular networks to relieve the negative impact of the hidden node problem

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores (Telecomunicações). Universidade do Porto. Faculdade de Engenharia. 201