69,701 research outputs found
The Practical Challenges of Interference Alignment
Interference alignment (IA) is a revolutionary wireless transmission strategy
that reduces the impact of interference. The idea of interference alignment is
to coordinate multiple transmitters so that their mutual interference aligns at
the receivers, facilitating simple interference cancellation techniques. Since
IA's inception, researchers have investigated its performance and proposed
improvements, verifying IA's ability to achieve the maximum degrees of freedom
(an approximation of sum capacity) in a variety of settings, developing
algorithms for determining alignment solutions, and generalizing transmission
strategies that relax the need for perfect alignment but yield better
performance. This article provides an overview of the concept of interference
alignment as well as an assessment of practical issues including performance in
realistic propagation environments, the role of channel state information at
the transmitter, and the practicality of interference alignment in large
networks.Comment: submitted to IEEE Wireless Communications Magazin
Cooperative Symbol-Based Signaling for Networks with Multiple Relays
Wireless channels suffer from severe inherent impairments and hence
reliable and high data rate wireless transmission is particularly challenging to
achieve. Fortunately, using multiple antennae improves performance in wireless
transmission by providing space diversity, spatial multiplexing, and power gains.
However, in wireless ad-hoc networks multiple antennae may not be acceptable
due to limitations in size, cost, and hardware complexity. As a result, cooperative
relaying strategies have attracted considerable attention because of their abilities
to take advantage of multi-antenna by using multiple single-antenna relays.
This study is to explore cooperative signaling for different relay networks,
such as multi-hop relay networks formed by multiple single-antenna relays and
multi-stage relay networks formed by multiple relaying stages with each stage
holding several single-antenna relays. The main contribution of this study is the
development of a new relaying scheme for networks using symbol-level
modulation, such as binary phase shift keying (BPSK) and quadrature phase shift
keying (QPSK). We also analyze effects of this newly developed scheme when it
is used with space-time coding in a multi-stage relay network. Simulation results
demonstrate that the new scheme outperforms previously proposed schemes:
amplify-and-forward (AF) scheme and decode-and-forward (DF) scheme
Uplink CoMP under a Constrained Backhaul and Imperfect Channel Knowledge
Coordinated Multi-Point (CoMP) is known to be a key technology for next
generation mobile communications systems, as it allows to overcome the burden
of inter-cell interference. Especially in the uplink, it is likely that
interference exploitation schemes will be used in the near future, as they can
be used with legacy terminals and require no or little changes in
standardization. Major drawbacks, however, are the extent of additional
backhaul infrastructure needed, and the sensitivity to imperfect channel
knowledge. This paper jointly addresses both issues in a new framework
incorporating a multitude of proposed theoretical uplink CoMP concepts, which
are then put into perspective with practical CoMP algorithms. This
comprehensive analysis provides new insight into the potential usage of uplink
CoMP in next generation wireless communications systems.Comment: Submitted to IEEE Transactions on Wireless Communications in February
201
Cooperative Compute-and-Forward
We examine the benefits of user cooperation under compute-and-forward. Much
like in network coding, receivers in a compute-and-forward network recover
finite-field linear combinations of transmitters' messages. Recovery is enabled
by linear codes: transmitters map messages to a linear codebook, and receivers
attempt to decode the incoming superposition of signals to an integer
combination of codewords. However, the achievable computation rates are low if
channel gains do not correspond to a suitable linear combination. In response
to this challenge, we propose a cooperative approach to compute-and-forward. We
devise a lattice-coding approach to block Markov encoding with which we
construct a decode-and-forward style computation strategy. Transmitters
broadcast lattice codewords, decode each other's messages, and then
cooperatively transmit resolution information to aid receivers in decoding the
integer combinations. Using our strategy, we show that cooperation offers a
significant improvement both in the achievable computation rate and in the
diversity-multiplexing tradeoff.Comment: submitted to IEEE Transactions on Information Theor
- …