IEEE C802.16m-07/164
Project
IEEE 802.16 Broadband Wireless Access Working Group <http://ieee802.org/16>
Title
Cooperative Relaying with Spatial Diversity and Multiplexing
Date
Submitted
2007-08-29
Source(s)
Wei Ni, Gang Shen, Shan Jin
Alcatel-Lucent Research and Innovation
F. Boccardi, K. Yu, A. Alexiou
Voice: + 86-21-50554550
Fax: + 86-21-50554554
mailto: {wei.a.ni, gang.a.shen, shan.jin}@alcatelsbell.com.cn
Voice: +44 1793 776620
Fax: +44 1793 776725
mailto: {fb, kaiyu, alexiou}@alcatel-lucent.com
Bell Laboratories, Alcatel-Lucent
Re:
IEEE 802.16m Requirements - Elaboration of Coopertaive Relaying Techniques
Abstract
Two cooperative relaying schemes are proposed for different propagation environments and
application scenarios. The adaptive distributed pre-coding (ADP) scheme is used for spatial
diversity and multi-user spatial multiplexing. The limited channel information feedback is
required to guarantee the performance at the low complexity of the terminals. Data splitting
algorithm (DSA) is a method to be exploited in correlated channels by sending independent
streams via source-destination link and/or different relays, and the data rate of a single terminal
can be increased. These schemes make cooperative relaying efficient in multi-hop 4G networks.
Purpose
For 802.16m discussion and eventual adoption for standardization
Notice
Release
Patent
Policy
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<http://standards.ieee.org/board/pat>.
Cooperative Relaying with Spatial Diversity and Multiplexing
Wei Ni, Gang Shen, Shan Jin
Alcatel-Lucent Research and Innovation
F. Boccardi, K. Yu, A. Alexiou
Bell Laboratories, Alcatel-Lucent
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1. Introduction
Conventional relaying systems employ repeaters to amplify and simply forward the radio signal in a relay chain,
whereas in the future multi-hop networks, the decode-and-forward relay stations (RS) will be used for not only
good signal quality but also network agility and robustness. Cooperative relaying hereby turns out to be a hot
topic since it is a new derivative technique of the multi-hop physical layer. This idea is to exploit two
fundamental features of the wireless medium: its broadcast nature, and its ability to achieve diversity or
multiplexing through providing independent channels.
While the broadcast nature is frequently considered to be a drawback as it leads to mutual interferences in a
wireless network, the concepts of cooperative relaying aim at benefiting from the fact that a signal, once
transmitted, can be received and usefully forwarded by multiple RSs. Moreover, by using truly intermediate RSs
one can benefit for a reduction of the end-to-end path loss.
Cooperative relaying is principally a distributed multiple-input-multiple-output (MIMO) system in multi-hop
environments, as shown in Figure 1, where the same time-frequency resource within a frame is assigned to
multiple RSs in relay links. In this document, two techniques of cooperative relaying are proposed. Adaptive
Distributed Pre-coding (ADP) is used for diversity or multiplexing gain, as well as the simplicity of both the RS
and the MS. Data Splitting Algorithm (DSA) is applied for achieving high spectral efficiency.
RS3
RS1
1st
3rd hop
hop
BS
2nd hop
MS
RS2
RS4
Fig. 1: Cooperative relay in multi-hop wireless networks
In the ADP scheme, multiple RSs work collaboratively as a virtual array to improve the signal quality or the
capacity of the system, owing to spatial diversity or multiplexing. Furthermore, it potentially simplifies handoff
between RSs.
This concept can achieve the following advantages:

Low computational complexity and ease of implementation where limited channel information is
required.

Performance improvement via diversity without the bandwidth loss.
Therefore, ADP, possessing the capability to achieve diversity or the boost of data rate, to simplify the intra-cell
handoff, is very promising for 4G.
The second DSA method is proposed for high data throughput relay transmissions with multiple antennas,
which is particularly appealing for correlated channels. Its basic idea is to send multiple independent spatial data
streams directly to the destination and to different relays and then to collect all of them at the destination. The
relays are selected using an opportunistic approach: an available spatial mode is allocated to a given relay only if
it involves a sum-rate improvement. Due to this “relay diversity” effect the overall throughput grows as a
function of the number of candidate relays.
Spatially decomposing the channels is implemented in the second method and by accessing the single modes
with a technique previously proposed for multi-user MIMO downlink transmissions and here extended to multi-2-
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antenna relay transmissions.
2. System Description
2.1 Adaptive Distributed Pre-coding (ADP)
ADP can work at two modes, one is spatial diversity mode (SD) and the other is spatial multiplexing (SM). In
the former work mode, ADP is an adaptive selection and combination of localized Space-Time Coding (STC)
and distributed STC (DSTC). It applies to both uplink and downlink for spatial diversity with the minimum
additional complexity.
DSTC uses space-time codes across different physical signal sources. For rate 1 codes, using existing
modulation methods, there is no increase in backhaul communication compared with standard relaying
techniques. By implementing STC across different physical transmitting stations, it is possible to achieve
diversity. Therefore, each signal source like RS plays the role of different transmit antennas in the regular STC
and the received signals from the different sources are different, such that RSs work as remote antennas of the
BS and the MS respectively. For example, the MS in Figure 2(a) transmits signals to two RSs and consequently
these RSs forward signals cooperatively to the BS by using DSTC techniques in the uplink.
A theoretical analysis reveals that no diversity gain is available if received powers of RSs are seriously
unbalanced. Furthermore, the symbol-level synchronization between the cooperative RSs is required according
to the definition of space-time code. Thus in some cases, the selected regular STC outperforms distributed STC
a lot due to the aforementioned reason as implied in Figure 2(b).
With the concern of power balance and synchronization, ADP selects localized STC or DSTC for cooperative
relaying via a pre-coding technique, as shown in Figure 3. In this cooperative scheme, transmit diversity as well
as array gain is expected to maximize the received Signal-Noise-Ratio (SNR).
Hop 2
Hop 1
(a) Virtual remote antenna array
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x1, x2
RS1
x2*, -x1*
STC over single RS
BS
x1, x2
y2*, -y1*
MS1
y1, y2
y1, y2
RS2
MS2
RS3
Cooperative relaying –
ADP over 2 RS
(b) A 2-hop uplink example of ADP
Fig. 2: The SD-mode ADP for cooperative relaying
h2
x2 x1
STBC
x2 x1
STBC
h3
Pre-coding
RS1
h1
h4
RS2 or BS
Fig.3: Joint pre-coded SD-mode ADP for cooperative relaying
In the SM work mode, the concept of “virtual BS” is introduced and ADP exploits pre-coding techniques for
spatial multiplexing gain for single or multiple MSs, as shown in Figure 4. This idea can also be applied to
multi-point-to-multi-point links within multi-hop networks beyond three hops in either the uplink or downlink.
RS1
MS1
BS
Virtual BS
MS2
RS2
Fig.4: An exemplary SM-mode ADP cooperative relaying
Figure 4 gives a downlink example of the proposed cooperative relaying networks. Owing to the good channel
between the highly mounted RSs and the BS, the light-of-sight (LOS) propagation is expectable in most cases.
Various transmission methods can be exploited to implement the communication on this hop, for example,
beam-forming, point-to-point MIMO or multi-user MIMO.
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The SM mode greatly benefits from the medium to large number of transmit antennas over multiple cooperative
RSs and the interference between the MSs can be mitigated in advance soundly using multi-user MIMO
techniques. Consequently, the throughput of the whole cell is greatly increased owing to cooperative relaying.
ADP can be easily extended to the scenarios with more hops. Figure 5 illustrates a downlink application
example of ADP for the last hop. Another application scenario is the Multi-Points-to-Point (MP2P) case as
indicated in Figure 6 where ADP is used not only for the last hop but also for the intermediate hops. Higher
spatial diversity or multiplexing gain is expectable and consequently improves capacity. The coherent
combining can also be implemented for higher array gain as denoted by the dash line in either uplink or
downlink.
RS1
BS
MS
RS2
ADP
Fig.5: ADP method for the last hop
BS
RS1
RS3
MS
RS2
ADP
Fig. 6: ADP method for networks beyond two hops
Generally, cooperative relaying has limited impacts on the wireless systems, except that some updates are
required. For example, in the SD mode, the system should be capable of collecting the channel qualities of all
potential hops involved and hereby making a selection between the regular STC and DSTC, so that the support
of MAC layer and its protocol is necessary. Bit error ratio (BER) and packet error ratio (PER) are used to verify
the performance of cooperative relaying.
Figure 7 (a) and (b) presents the simulation results of ADP, and for the purpose of comparison, regular STBC,
selective regular STBC and distributed STBC are simulated as well, based on IEEE 802.16e downlink PUSC.
Two RSs are involved in the simulations; each equipped with 2 antennas spaced 4 wavelengths in-between.
Simultaneously 2 antennas of total 4 are working cooperatively in different transmission modes. The MS lies in
the middle of the two RSs with two receive antennas spaced 0.5 wavelengths to perform maximum ratio
combining (MRC) for receive diversity. IEEE 802.11n channel model E is applied to evaluate the performance
of ADP where information bits are coded with 1/3-rate convolutional code (CC) and modulated with 16QAM.
Figure 7 (a) and (b) illustrate the BER and the PER performance of ADP, respectively. Especially, the
significant PER improvement can be observed by around 4.3 dB and 3.1 dB, respectively comparing to the
regular STBC and the selective STBC, owing to spatial diversity.
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Fig. 7(a): BER performance of ADP SD mode
Fig. 7(b): PER performance of ADP SD mode
2.2 Solution for correlated MIMO channels — data splitting algorithm (DSA)
The basic idea of DSA is to send multiple independent spatial data streams via direct link between sourcedestination and/or different relays and to collect them at the destination. We implement this idea by spatially
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decomposing the channels and by accessing the single modes. The relays are selected using an opportunistic
approach: an available spatial mode is allocated to a given relay only if it involves a sum-rate improvement. Due
to this “relay diversity” effect the overall throughput grows as a function of the number of candidate relays.
RS
MS
BS
RS
Fig.8: Graphical representation of the considered system
We consider a system with one source (S), one destination (D) and r relays (R) as shown in Fig.8. Each relay
uses a decoding and forwarding policy. Moreover each node is equipped with multiple antennas, and more
specifically Ns, Nd and Nr antennas are deployed respectively at the source, at the destination and at each of the
relays. We assume an infinite buffer at the source side. We represent the channel response between each couple
of transmit/receive antennas as a complex coefficient, in order to model the frequency response of a given
carrier in an OFDM system.
The transmission can be divided in two phases. During the first phase (downlink phase) the source transmits to a
set {R1, …, Rr, D} of nodes. During the second phase (uplink phase) a second set of nodes {{\ D}S}
transmits to the destination
The transmission protocol is summarized in the following table.
Time slot 1 (downlink phase)
Time slot 2 (uplink phase)
S
 D
Table 1: Transmission protocol
This approach is particularly appealing for correlated channels, where, due to the low rank of the channel matrix,
is not possible to achieve the maximum number of independent transmitted streams (Nmax = min(Ns, Nd)): in
this case by transmitting independent streams via source-destination link and/or multiple relays, the
multiplexing gain can be recovered.
In order to simulate the performance of the proposed scheme we consider a scenario with r=9 relays. Let d be
the distance between source and destination and let (0, 0) and (0, d) be the spatial coordinates of source and
destination, respectively.
The spatial coordinates of the four relays are given by (d/4,-d/4), (d/4,0), (d/4,d/4), (d/2,-d/4), (d/2,0), (d/2,d/4),
(3d/4,-d/4), (3d/4,0), (3d/4,d/4) (see Fig.9).
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S
R3
R6
R9
R2
R5
R8
R1
R4
D
R7
Fig.9: Relay deployment used for the simulations.
The distance between source and destination is a parameter fixed such that the SNR at the destination has a
given value. Each node is equipped with Ns = Nd = Nr = 8 antennas. For simulating the signal propagation
between the different nodes we used the WINNER channel generator, and in particular the propagation scenario
B1 (typical urban microcell), modified such that all the nodes have the same height of 3 meters. We considered
both line-of-sight (LOS) and not line-of-sight (NLOS) propagation, with 0.5λ and 2λ antenna element distance.
The performance is given in terms of throughput [bit/s/Hz] vs source destination SNR. We compare four
different techniques:

the proposed DSA under the per-relay power constraint;

the proposed DSA algorithm performance under the common power constraint;

the “best relay selection” scheme, obtained by selecting the best relay and transmitting at the closed
loop capacity in each of the two links (source to relay and relay to destination);

the direct link transmission scheme, obtained by using the closed loop capacity formula of the link
between source and destination.
In Fig.10(a) a propagation scenario without line of sight is considered, for 0.5λ antenna element spacing
(dash/dotted line) and 2λ antenna element spacing (continuous line). We note that with correlated channels (0.5λ
case) the DSA gives a not negligible gain with respect to best relay selection scheme and direct link
transmission scheme, in the entire SNR region.
Let's for the moment consider the case of common power constraint. In this case the gain is due to two factors.
The first factor is that by splitting the streams between different relays, the effective degrees of freedom (EDOF)
is not limited by the rank of a single link channel (effective degrees of freedom gain). The second factor is that
the proposed greedy relay/eigenmode allocation scheme at each channel generation selects the best set of spatial
channels (multirelay diversity gain). When we consider a per-relay power constraint, to the already described
two factors that occur also in the case of common power constraint, we add also the effect of the power gain in
the uplink phase. When the channel is not correlated this power gain still involves a performance improvement
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at low SNR, whereas by directly transmitting all the streams to the destination (direct link transmission) we are
already able to exploit all the effective degrees of freedom.
In Fig.10(b) the same scenario is considered for a LOS case. We note that with correlated channels (0.5λ case)
the DSA gives a not negligible gain with respect to best relay selection scheme and direct link transmission
scheme, in the whole SNR region. In this case the effect of effective degrees of freedom gain and multirelay
diversity gain are even more pronounced and involve a big advantage of the DSA over the two baselines, for
both (0.5λ case) antenna element spacing and (2λ case) antenna element spacing.
45
BESTRLY
DIRECT PATH
DSASPC
DSAIPC
40
sum rate [bit/s/Hz]
35
30
25
20
15
10
5
0
2
4
6
8
10
12
SNR [dB]
14
16
18
20
Fig.10(a): Performance comparison between the proposed DSA algorithm under the per-relay power constraints,
common power constraint (DSASPC: DSA algorithm with common power constraint, and DSAIPC: DSA algorithm
with per-relay power constraint), best relay selection scheme and direct link transmission scheme. In each node 8
antennas has been considered with an element spacing of 0.5 λ continuous line) and 2 λ ((dash/dotted line). A WINNER
B1 propagation scenario has been considered without LOS.
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40
BESTRLY
DIRECT PATH
DSASPC
DSAIPC
35
sum rate [bit/s/Hz]
30
25
20
15
10
5
0
2
4
6
8
10
12
SNR [dB]
14
16
18
20
Fig.10(b): Performance comparison between the proposed DSA algorithm under the per-relay power constraints,
common power constraint, best relay selection scheme and direct link transmission scheme. In each node 8 antennas has
been considered with an element spacing of 0.5 λ (continuous line) and 2 λ (dash/dotted line). A WINNER B1
propagation scenario has been considered with LOS.
3. Summary
Cooperative relaying methods, ADP and DSA, are proposed for spatial diversity and multiplexing as well as
the simplicity and efficiency, and simulation results verified the great improvement. With these schemes,
multiple RSs can work collaboratively for better signal quality and performance in various propagation
environments.
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