The general system model obeys the same topology as depicted in Figure 3.1, i.e. a sourceMT (s-MT) communicates with a target MT (t-MT) via a given number of relaying MTs(r-MTs). Spatially adjacent r-MTs are grouped into relaying Virtual Antenna Arrays (rVAAs), the exact configuration of which has been thoroughly explained in Chapter 3. Thesystem configurations described there-in are sufficiently precise for dealing with the capacityof such networks.However, the deployment of realistic transceivers requires further explanations of howsuch system would work in reality. It is hence the aim of this section to provide this missinginformation. Of interest here are the transmitter and receiver used, as well as the prevailingcommunication channel.4.2.1 Transceiver ModelThe functional blocks of the transceivers forming the distributed-MIMO multi-stage relayingnetwork are depicted in Figure 4.1. The top of Figure 4.1 relates to the source VAAcontaining the s-MT; the middle relates to an arbitrary relaying VAA tier; and the bottomrelates to the target VAA containing the t-MT. In the figure, each VAA tier is shownto consist of three terminals; it is, however, understood that any reasonable number ofterminals can be accommodated.Specifically, the information source passes the information to a cooperative transceiver,which relays the data to spatially adjacent r-MTs belonging to the same VAA. Again, thisis assumed to happen over an air interface distinct from the interface used for inter-stage
communication or an air interface not requiring any optimisation, and is not considered
further. It is also assumed that these cooperative links are error-free due to the short communication distances. Each of the terminals in the VAA perform distributed encoding of
the information according to some prior specified rules. That information is then transmitted from the spatially distributed terminals after having been synchronised. Note that the
problem related to synchronisation is beyond the scope of this thesis.
Any of the relaying VAA tiers functions as follows. First, each r-MT within that VAA
receives the data which is optionally decoded before being passed onto the cooperative
transceiver. Ideally, every terminal cooperates with every other terminal; however, any
amount of cooperation is feasible. If no decoding is performed, then an unprocessed or
a sampled version of the received signal is exchanged with the other r-MTs. Note that
unprocessed relaying is equivalent to transparent relaying. After cooperation, appropriate decoding is performed. The obtained information is then re-encoded in a distributed
manner, synchronised and re-transmitted to the following relaying VAA tier.
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1st Tier VAA
source-MT
r-MT #2
r-MT #1
Information
Source
Cooperative
Transceiver
Cooperative
Transceiver
Cooperative
Transceiver Synchr.
Synchr.
Synchr.
Transmitter
Transmitter
Transmitter
Distributed
Encoder
Distributed
Encoder
Distributed
Encoder
V-th Tier VAA
target-MT...
r-MT #2...
r-MT #1...
Cooperative
Transceiver
Cooperative
Transceiver
Cooperative
Transceiver
Receiver
Receiver
Receiver
Optional
Decoder
Optional
Decoder
Optional
Decoder
Distributed
Decoder
Information
Sink
v-th Tier VAA
r-MT #2
r-MT #3
r-MT #1
Cooperative
Transceiver
Cooperative
Transceiver
Cooperative
Transceiver Synchr.
Synchr.
Synchr.
Transmitter
Transmitter
Transmitter
Receiver
Receiver
Receiver
Optional
Decoder
Optional
Decoder
Optional
Decoder
Distributed
Transcoder
Distributed
Transcoder
Distributed
Transcoder
Figure 4.1: Functional blocks of the source VAA (top), the vth relaying VAA (middle) and
the target VAA (bottom).
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As for the target VAA, the functional blocks are exactly the opposite to the source VAA.
All terminals receive the information, possibly decode it, then pass it onto the cooperative
transceivers which relay the data to the target terminal. The data is processed and finally
delivered to the information sink.
The functional blocks of the distributed transcoder, i.e. encoder and decoder, are now
elaborated on in more detail. To this end, the encoder and decoder are shown in Figure 4.2.
Generally, the role of a channel encoder is to insert sufficient redundancy into the signal
to mitigate the detrimental effects of noise and the fading channel. The insertion of redundancy decreases the data rate, where (with a good channel code) a decrease in rate comes
along with an increase in coding gain. Together with the additional complexity, these need
to be traded-off to yield optimum performance in terms of the BER versus Eb/N0, where
Eb is the information bit energy and N0 is the noise power spectral density.
The channel code is traditionally accomplished by means of a convolutional code, which
‘convolutes’ the redundancy into the original signal stream. Nowadays, it is considered to
be a low complexity code and is often found to be available within communication chip-sets.
Another class of codes are the block codes. These generate the redundant information from
the original data stream, after which it is inserted into it. A more complex class of codes
are turbo codes, which were shown to operate near the Shannon capacity. For a proper
functioning and mathematical description of these codes, refer to [67].
Cooperative Encoder
Binary
Information Bits
Channel
Encoder
Space-Time
Encoder
Encoded
Inform. Symbols
to each Antenna
Control #1 Control #2
Cooperative Decoder
direct symbols
Space-Time
Decoder
Channel
Decoder
Control #3 Control #4
cooperative symbols Binary
Information Bits
Figure 4.2: Distributed Encoder and Decoder.
143
The channel encoder may also consist of two or more concatenated codes, which are
preferably connected by interleavers which break long error sequences. For example, trellis
codes are known to produce a cluster of errors, which could then be corrected by appropriate
block codes.
A channel encoder within a distributed encoder does not normally differ from a nondistributed encoder; however, it is generally possible to design channel codes which reflect
the distributed nature of the encoding process. Example trellis codes are introduced in [31],
where the encoder requires some form of control as to decide which code to employ.
The role of a space-time encoder is to utilise the additional spatial dimension created by
sufficiently spaced antenna elements to increase the system performance. If each antenna
element is used to transmit independent data streams, then such spatial multiplexing technique is referred to as BLAST [30]. Clearly, the data rate of such a system increases linearly
with the number of transmit antennas; however, the lack of spatial redundancy makes it
more susceptible to noise and interference when compared to coding techniques described
below.
If, instead, the additional spatial domain is used to provide redundant information, then
such a spatial encoding technique is referred to as space-time coding. The computationally
simple space-time block codes (STBCs) have already been introduced in Chapter 2, where
they were shown to orthogonalise the MIMO channel. More complex codes are space-time
trellis codes (STTCs), or space-time turbo codes. Note that space-time codes (STCs) can
also be concatenated with an outer channel code to yield additional performance gains as
described above.
The functionality of distributed space-time codes (STCs) differs from a traditional deployment because only a fraction of the entire space-time codeword is transmitted from any
of the spatially distributed terminals. The transmission across all terminals then yields the
complete space-time codeword. Therefore, a control signal to each distributed space-time
encoder is essential, as it tells each of them which fraction of the entire space-time codeword
to pass onto the transmitting antenna(s). This is indicated as Control #2 in Figure 4.2.
This control information is assumed to be available to the space-time encoder, and is thus
not discussed further in this thesis.
The cooperative decoder can be realised as the inversion of all processes at the cooperative transmitter. Here, the space-time decoder is fed with the signals directly received from
the available antenna(s), as well as the information received via the cooperative links from
adjacent terminals. Again, a control signal is needed which specifies the type of information
fed into the space-time decoder, to allow for optimum decoding. For example, the control
signal could inform the decoder that the relayed signals are a one bit representation of the
sampled soft information available at the respective cooperative relaying terminals.
144
After the space-time decoding process, the information is passed on to the channel
decoder which performs the inverse proces
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