232 research outputs found
Linear Precoders for Non-Regenerative Asymmetric Two-way Relaying in Cellular Systems
Two-way relaying (TWR) reduces the spectral-efficiency loss caused in
conventional half-duplex relaying. TWR is possible when two nodes exchange data
simultaneously through a relay. In cellular systems, data exchange between base
station (BS) and users is usually not simultaneous e.g., a user (TUE) has
uplink data to transmit during multiple access (MAC) phase, but does not have
downlink data to receive during broadcast (BC) phase. This non-simultaneous
data exchange will reduce TWR to spectrally-inefficient conventional
half-duplex relaying. With infrastructure relays, where multiple users
communicate through a relay, a new transmission protocol is proposed to recover
the spectral loss. The BC phase following the MAC phase of TUE is now used by
the relay to transmit downlink data to another user (RUE). RUE will not be able
to cancel the back-propagating interference. A structured precoder is designed
at the multi-antenna relay to cancel this interference. With multiple-input
multiple-output (MIMO) nodes, the proposed precoder also triangulates the
compound MAC and BC phase MIMO channels. The channel triangulation reduces the
weighted sum-rate optimization to power allocation problem, which is then cast
as a geometric program. Simulation results illustrate the effectiveness of the
proposed protocol over conventional solutions.Comment: 30 pages, 7 figures, submitted to IEEE Transactions on Wireless
Communication
Resource allocation and optimization techniques in wireless relay networks
Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the
useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay
network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The
secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource
allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks
Mathematical optimization and signal processing techniques for cooperative wireless networks
The rapid growth of mobile users and emergence of high data rate multimedia and interactive services have resulted in a shortage of the radio spectrum. Novel solutions are therefore required for future generations of wireless networks to enhance capacity and coverage. This thesis aims at addressing this issue through the design and analysis of signal processing algorithms. In particular various resource allocation and spatial diversity techniques have
been proposed within the context of wireless peer-to-peer relays and coordinated base station (BS) processing.
In order to enhance coverage while providing improvement in capacity, peer-to-peer relays that share the same frequency band have been considered and various techniques for designing relay coefficients and allocating powers optimally are proposed. Both one-way and two-way amplify and forward (AF) relays have been investigated. In order to maintain fairness, a signal-to-interference plus noise ratio (SINR) balancing criterion has been adopted. In order to improve the spectrum utilization further, the relays within the context of cognitive radio network are also considered. In this case, a cognitive peer-to-peer relay network is required to achieve SINR balancing while maintaining the interference leakage to primary receiver below a certain threshold.
As the spatial diversity techniques in the form of multiple-input-multipleoutput (MIMO) systems have the potential to enhance capacity significantly, the above work has been extended to peer-to-peer MIMO relay networks. Transceiver and relay beamforming design based on minimum mean-square error (MSE) criterion has been proposed. Establishing uplink downlink MSE duality, an alternating algorithm has been developed. A scenario where multiple users are served by both the BS and a MIMO relay is considered and a joint beamforming technique for the BS and the MIMO relay is proposed. With the motivation of optimising the transmission power at both the BS and the relay, an interference precoding design is presented that takes into account the knowledge of the interference caused by the relay to the users served by the BS.
Recognizing joint beamformer design for multiple BSs has the ability to reduce interference in the network significantly, cooperative multi-cell beamforming design is proposed. The aim is to design multi-cell beamformers to maximize the minimum SINR of users subject to individual BS power constraints. In contrast to all works available in the literature that aimed at balancing SINR of all users in all cells to the same level, the SINRs of users in each cell is balanced and maximized at different values. This new technique takes advantage of the fact that BSs may have different available transmission powers and/or channel conditions for their users
A Novel Antenna Selection Scheme for Spatially Correlated Massive MIMO Uplinks with Imperfect Channel Estimation
We propose a new antenna selection scheme for a massive MIMO system with a
single user terminal and a base station with a large number of antennas. We
consider a practical scenario where there is a realistic correlation among the
antennas and imperfect channel estimation at the receiver side. The proposed
scheme exploits the sparsity of the channel matrix for the effective selection
of a limited number of antennas. To this end, we compute a sparse channel
matrix by minimising the mean squared error. This optimisation problem is then
solved by the well-known orthogonal matching pursuit algorithm. Widely used
models for spatial correlation among the antennas and channel estimation errors
are considered in this work. Simulation results demonstrate that when the
impacts of spatial correlation and imperfect channel estimation introduced, the
proposed scheme in the paper can significantly reduce complexity of the
receiver, without degrading the system performance compared to the maximum
ratio combining.Comment: in Proc. IEEE 81st Vehicular Technology Conference (VTC), May 2015, 6
pages, 5 figure
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