1,267 research outputs found
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
Scheduling for Multi-Camera Surveillance in LTE Networks
Wireless surveillance in cellular networks has become increasingly important,
while commercial LTE surveillance cameras are also available nowadays.
Nevertheless, most scheduling algorithms in the literature are throughput,
fairness, or profit-based approaches, which are not suitable for wireless
surveillance. In this paper, therefore, we explore the resource allocation
problem for a multi-camera surveillance system in 3GPP Long Term Evolution
(LTE) uplink (UL) networks. We minimize the number of allocated resource blocks
(RBs) while guaranteeing the coverage requirement for surveillance systems in
LTE UL networks. Specifically, we formulate the Camera Set Resource Allocation
Problem (CSRAP) and prove that the problem is NP-Hard. We then propose an
Integer Linear Programming formulation for general cases to find the optimal
solution. Moreover, we present a baseline algorithm and devise an approximation
algorithm to solve the problem. Simulation results based on a real surveillance
map and synthetic datasets manifest that the number of allocated RBs can be
effectively reduced compared to the existing approach for LTE networks.Comment: 9 pages, 10 figure
A Distributed Approach to Interference Alignment in OFDM-based Two-tiered Networks
In this contribution, we consider a two-tiered network and focus on the
coexistence between the two tiers at physical layer. We target our efforts on a
long term evolution advanced (LTE-A) orthogonal frequency division multiple
access (OFDMA) macro-cell sharing the spectrum with a randomly deployed second
tier of small-cells. In such networks, high levels of co-channel interference
between the macro and small base stations (MBS/SBS) may largely limit the
potential spectral efficiency gains provided by the frequency reuse 1. To
address this issue, we propose a novel cognitive interference alignment based
scheme to protect the macro-cell from the cross-tier interference, while
mitigating the co-tier interference in the second tier. Remarkably, only local
channel state information (CSI) and autonomous operations are required in the
second tier, resulting in a completely self-organizing approach for the SBSs.
The optimal precoder that maximizes the spectral efficiency of the link between
each SBS and its served user equipment is found by means of a distributed
one-shot strategy. Numerical findings reveal non-negligible spectral efficiency
enhancements with respect to traditional time division multiple access
approaches at any signal to noise (SNR) regime. Additionally, the proposed
technique exhibits significant robustness to channel estimation errors,
achieving remarkable results for the imperfect CSI case and yielding consistent
performance enhancements to the network.Comment: 15 pages, 10 figures, accepted and to appear in IEEE Transactions on
Vehicular Technology Special Section: Self-Organizing Radio Networks, 2013.
Authors' final version. Copyright transferred to IEE
Multi-User Ranging Code Detection in OFDMA System Using MMLD Algorithm for Improving Detection Performance
Successive user detection algorithm is used to observe the multi user ranging signals and calculate there corresponding parameters. Using IEEE 802.16 specification in Orthogonal Frequency Division Multiple Access (OFDMA), initial ranging method designed an algorithm called Moment Maximum Likelihood Detection (MMLD) to detect the codes assigned and predicting offset timing. The objective function which is derived from the Expectation Maximization (EM) algorithm is used in the MMLD to cancel the channel estimation errors and Multiple Access Interference (MAI). To reduce the MAI over the iteration, the Maximum Likelihood Estimation (MLE) algorithm is designed in the MMLD. The experimental results indicate that the system is highly accurate
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