Low Complexity WMMSE Power Allocation In NOMA-FD Systems

In this paper we study the problem of power and channel allocation with the objective of maximizing the system sum-rate for multicarrier non-orthogonal multiple access (NOMA) full duplex (FD) systems. Such an allocation problem is non-convex and, thus, with the goal of designing a low complexity solution, we propose a scheme based on the minimization of the weighted mean square error, which achieves performance reasonably close to the optimum and allows to clearly outperforms a conventional orthogonal multiple access approach. Numerical results assess the effectiveness of our algorithm.Comment: 5 pages conference paper, 3 figures. Submitted on ICASSP 202

Random Access in Massive MIMO by Exploiting Timing Offsets and Excess Antennas

Massive MIMO systems, where base stations are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of user equipments (UEs) increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this paper, a random access protocol is proposed that resolves collisions and performs timing estimation by simply utilizing the large number of antennas envisioned in Massive MIMO networks. UEs entering the network perform spreading in both time and frequency domains, and their timing offsets are estimated at the base station in closed-form using a subspace decomposition approach. This information is used to compute channel estimates that are subsequently employed by the base station to communicate with the detected UEs. The favorable propagation conditions of Massive MIMO suppress interference among UEs whereas the inherent timing misalignments improve the detection capabilities of the protocol. Numerical results are used to validate the performance of the proposed procedure in cellular networks under uncorrelated and correlated fading channels. With $2.5\times10^3$ UEs that may simultaneously become active with probability 1\% and a total of $16$ frequency-time codes (in a given random access block), it turns out that, with $100$ antennas, the proposed procedure successfully detects a given UE with probability 75\% while providing reliable timing estimates.Comment: 30 pages, 6 figures, 1 table, submitted to Transactions on Communication

Random Access in Uplink Massive MIMO Systems: How to exploit asynchronicity and excess antennas

Massive MIMO systems, where the base stations are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of users increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this work, we propose a random access procedure that resolves collisions and also performs timing, channel, and power estimation by simply utilizing the large number of antennas envisioned in massive MIMO systems and the inherent timing misalignments of uplink signals during network access and handover. Numerical results are used to validate the performance of the proposed solution under different settings. It turns out that the proposed solution can detect all collisions with a probability higher than 90%, at the same time providing reliable timing and channel estimates. Moreover, numerical results demonstrate that it is robust to overloaded situations.Comment: submitted to IEEE Globecom 2016, Washington, DC US

ML estimation of timing, integer frequency and primary sequence index in LTE systems

This paper addresses the problem of maximum likelihood (ML) estimation of slot timing, integer carrier frequency offset and primary sequence index for the downlink of Long Term Evolution (LTE) systems. The proposed algorithm is designed to exploit the knowledge of the pilot Zadoff-Chu sequence embedded in the primary synchronization signal (PSS). The estimation process is affected by the presence of a large set of nuisance parameters, which need to be estimated jointly with the parameters of interest. As a consequence, the exact ML solution is extremely complex and we have developed a suboptimal algorithm designed to provide a good balance between estimation accuracy and complexity. In particular, a key finding is a reduced-rank representation for the frequency response of the channel, which is required by the ML estimator but is not available at receiver prior to having acquired synchronization. Compared to existing alternatives, the resulting scheme exhibits improved accuracy in the estimation of all three parameters of interest

A Robust Maximum Likelihood Scheme for PSS Detection and Integer Frequency Offset Recovery in LTE Systems

Before establishing a communication link in a cellular network, the user terminal must activate a synchronization procedure called initial cell search in order to acquire specific information about the serving base station. To accomplish this task, the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink of a long term evolution (LTE) network. Since SSS detection can be performed only after successful identification of the primary signal, in this work, we present a novel algorithm for joint PSS detection, sector index identification, and integer frequency offset (IFO) recovery in an LTE system. The proposed scheme relies on the maximum likelihood (ML) estimation criterion and exploits a suitable reduced-rank representation of the channel frequency response, which proves robust against multipath distortions and residual timing errors. We show that a number of PSS detection methods that were originally introduced through heuristic reasoning can be derived from our ML framework by simply selecting an appropriate model for the channel gains over the PSS subcarriers. Numerical simulations indicate that the proposed scheme can be effectively applied in the presence of severe multipath propagation, where existing alternatives provide unsatisfactory performance

A Practical Scheme for Frequency Offset Estimation in MIMO-OFDM Systems

This paper deals with training-assisted carrier frequency offset (CFO) estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. The exact maximum likelihood (ML) solution to this problem is computationally demanding as it involves a line search over the CFO uncertainty range. To reduce the system complexity, we divide the CFO into an integer part plus a fractional part and select the pilot subcarriers such that the training sequences have a repetitive structure in the time domain. In this way, the fractional CFO is efficiently computed through a correlation-based approach, while ML methods are employed to estimate the integer CFO. Simulations indicate that the proposed scheme is superior to the existing alternatives in terms of both estimation accuracy and processing load

Periodic Preamble-Based Frequency Recovery in OFDM Receivers Plagued by I/Q Imbalance

The direct conversion receiver (DCR) architecture has received much attention in the last few years as an effective means to obtain user terminals with reduced cost, size, and power consumption. A major drawback of a DCR device is the possible insertion of I/Q imbalances in the demodulated signal, which can seriously degrade the performance of conventional synchronization algorithms. In this paper, we investigate the problem of carrier frequency offset (CFO) recovery in an OFDM receiver equipped with a DCR front-end. Our approach is based on maximum likelihood (ML) arguments and aims at jointly estimating the CFO, the useful signal component, and its mirror image. In doing so, we exploit knowledge of the pilot symbols transmitted within a conventional repeated training preamble appended in front of each data packet. Since the exact ML solution turns out to be too complex for practical purposes, we propose two alternative schemes which can provide nearly optimal performance with substantial computational saving. One of them provides the CFO in closed-form, thereby avoiding any grid-search procedure. The accuracy of the proposed methods is assessed in a scenario compliant with the 802.11a WLAN standard. Compared with existing solutions, the novel schemes achieve improved performance at the price of a tolerable increase of the processing load

DOA Estimation in the Uplink of Multicarrier CDMA Systems

We consider the uplink of a multicarrier code-division multiple-access (MC-CDMA) network and assume that the base station is endowed with a uniform linear array. Transmission takes place over a multipath channel and the goal is the estimation of the directions of arrival (DOAs) of the signal from the active users. In a multiuser scenario, difficulties are primarily due to the large number of parameters involved in the estimation of the DOAs which makes this problem much more challenging than in single-user transmissions. The solution we propose allows estimating the DOAs of different users independently, thereby leading to a significant reduction in the system complexity. In the presence of multipath propagation, however, estimating the DOAs of a given user through maximum-likelihood methods remains a formidable task since it involves a search over a multidimensional domain. Therefore, we look for simpler solutions and discuss two alternative schemes based on the SAGE and ESPRIT algorithms

An Improved Scheme for Initial Ranging in OFDMA-based Networks

An efficient scheme for initial ranging has recently been proposed by X. Fu et al. in the context of orthogonal frequency-division multiple-access (OFDMA) networks based on the IEEE 802.16e-2005 standard. The proposed solution aims at estimating the power levels and timing offsets of the ranging subscriber stations (RSSs) without taking into account the effect of possible carrier frequency offsets (CFOs) between the received signals and the base station local reference. Motivated by the above problem, in the present work we design a novel ranging scheme for OFDMA in which the ranging signals are assumed to be misaligned both in time and frequency. Our goal is to estimate the timing errors and CFOs of each active RSS. Specifically, CFO estimation is accomplished by resorting to subspacebased methods while a least-squares approach is employed for timing recovery. Computer simulations are used to assess the effectiveness of the proposed solution and to make comparisons with existing alternatives.Comment: 6 pages, 3 figures, To appear in the Proceedings of the 2008 IEEE International Conference on Communications, Beijing, May 19 - 23, 200