Experimental Investigation of Cooperative Schemes on a Real-Time DSP-Based Testbed

MULTIPATH fading is one of the major obstacles for the next generation wireless networks, which require high bandwidth efficiency services. Time, frequency, and spatial diversity techniques are used to mitigate the fading phenomenon [1]. Recently, cooperative communications for wireless networks have gained much interest due to its ability to mitigate fading in wireless networks through achieving spatial diversity, while resolving the difficulties of installing multiple antennas on small communication terminals. In cooperative communication, a number of relay nodes are assigned to help a source in forwarding its information to its destination, hence forming a virtual antenna array.

Various cooperative protocols have been proposed and analysed in the literature. In [2], Laneman et al. proposed two cooperative protocols: the amplify-and-forward (AF) protocol and the decode-and-forward (DF) protocol, where the relays would either purely amplify and retransmit the information to the destination, or decode the information first and then transmit these information bits to the destination. In [3], Anghel and Kaveh showed that the conventional maximum ratio combining (MRC) was the optimum detection scheme at the destination for the AF and it could achieve the full diversity order of , where is the number of relays. When it comes to the DF, the optimum maximum likelihood (ML) detector was proposed in [4, 5]. Furthermore, many suboptimum detection schemes have been proposed, including the -MRC [4, 6], the simple adaptive decode-and-forward scheme [7], the cooperative MRC (CMRC) [8], and the link-adaptive regeneration (LAR) [9]. Recently, many works have been devoted to improve the bandwidth efficiency of cooperative networks, including the distributed space-time codes [10] and the relay selection [11, 12]. Among those techniques, the relay selection is very attractive. The basic idea is to let the relay with the best channel condition relay the signals. Since only one relay is working at each time slot, a very strict time and carrier synchronisation among the relays is not needed. Furthermore, because the transmission of one information-bearing symbol is completed within two-time slots, the relay selection has higher bandwidth efficiency than the repetition-based cooperative strategy.

In [13] the authors implement a cooperative coding scheme [14]. The scheme is compared with a traditional noncooperative one while transmitting frames of a video clip. From the experiments, it is observed that cooperation increases the quality of the video clip. In [15], the authors perform detailed simulations of two variations of the decode-and-forward protocol [4, 16] using low-density parity check (LDPC) codes, and a direct transmission scheme. It is concluded that the cooperative schemes outperform the direct transmission. Most of the implementation work that has appeared in literature focus on implementing variations of a single protocol. Herein, we are presenting an experimental investigation of several cooperation schemes, some of which are sophisticated. We also put focus on presenting quantitative results and measurements in a relevant propagation environment.

Specifically, in this work we have implemented the well-known AF, DF, and CMRC protocols, where the signal received at the destination is combined according to the MRC detection rule. Furthermore we provide experimental results for some more techniques that have been recently proposed, including a DSTC scheme based on the Alamouti coding and a novel relay selection scheme. The implementations are made on a real-time DSP-based testbed. Finally, in the experiments, we compare the performance of the implemented schemes in terms of outage probability, complexity and a novel "implementation loss'' measure.

The paper is organised as follows. The implementation of the schemes is described in Section 2 of this paper. The experimental results are described in Section 3. The results show that, compared with direct transmission, the proposed cooperative schemes increase coverage. By means of "implementation loss'' analysis we show that the results are fairly close to the theoretical results. A more full discussion of the conclusions drawn are given in Section 4.

The testbed consists of four nodes, where each node has two antennas, two transmitters, and two receiver chains, a DSP board for processing, and a laptop PC for control. The symbol- and sample-rate used are 9600 Hz and 48 kHz, respectively. A picture of a node is shown in Figure 1 and a schematic is shown in Figure 2. As shown in Figure 2, the base-band processing is made on the DSK6713 board, which is a DSP board provided by Texas Instruments. The A/D and D/A converters receive and transmit a signal with 10 kHz carrier frequency. The up- and donwnconversion between RF (1766.6 MHz) and base-band is done in the transmitter (TXM) and receiver modules (RXM), respectively. More information about the hardware and software are given in [17, 18]. The system uses sharp crystal filters in both the transmitter and the receiver. This confines the transmit bandwidth to 9600 Hz with little leakage outside this bandwidth. However, these filers introduce intersymbol interference. The intersymbol interference is 15–20 dB weaker than the desired signal. This is negligible for QPSK but degrades the performance for higher-order constellations. In this paper only QPSK modulation is used.

The nodes act as source, relay, destination, base-station, or mobile-station in the implementations herein. One of the nodes is called the master. This node sends out a synchronisation signal which is detected by the other nodes. A sinusoid follows the synchronisation sequence enabling the other nodes to adjust their up- and downconversion frequencies. These synchronisation sequences are sent at a power level of 10 dBm while the actual data is sent at a power level of  dBm. The synchronisation is rough and gives a remaining error of one sample. The master can be any of the nodes. In our measurements the source is usually the master. However, in a few measurements the source could not be used since the path-loss to the destination was too high. In this case, relay 2 was instead used as the master.

The power level used for transmitting payload data is  dBm. This results in a transmitted power spectral density of  dBm/kHz. This is comparable to what can be expected to be the case in future wireless LAN-type applications which may use 20 dBm transmit power over a 100 MHz bandwidth, which also gives  dBm/kHz power spectral density. The higher power used for synchronisation can be motivated by the fact that when a wideband system is synchronized all the available power can be used for this purpose, while payload data would be transmitted on multiple subcarriers using only a fraction of the total available power used for a given subcarrier.

The residual synchronisation error of one sample has to be accounted for. This is done differently for different schemes and this is described in more details below.

There is a delay of typically 58 samples between the transmitter and the receiver. This delay is due to digital antialias filters in the D/A and A/D converters and (but to a less extent) delays in the analog hardware. This delay is taken into account by letting the transmitting frames be scheduled 12 symbols (which correspond to 60 samples) before the corresponding receive frames. These delays lead to a nonnegligible overhead when switching between transmit and receive mode. The delay could be brought down to 4 symbols if the antialias filters of the D/A and A/D converters were removed. Unfortunately, we were not able to do this. However, in the throughput figures, we account for this delay as 4 symbols instead of 12, to show a result that better reflects the performance if this small practical issue could be resolved.

There is also a problem when a node transmits and then starts to receive directly following the transmission. This leads to six symbols being interfered by transients from the powering down of the transmitter. This problem should be solvable with a better hardware design. Therefore, we do not take these six symbols into account when calculating the throughput.

A measurement campaign was conducted in an indoor office environment (see Figures 10 and 11). In the campaign a source (S), two relays (R1, R2), and a destination (D) were used, although relay R2 is only in DSTC and SR. Some of the positions of these nodes during the measurements are illustrated in Figure 12.

In order to be able to compare all five schemes with different options, a measurement procedure consisting of "measurement runs" was developed. Within each measurement run twenty-four different configurations were run in sequence. In Table 1 below we list the sequence of configurations in one measurement run. The reader may note that some configurations are identical. Each measurement run was conducted under stationary conditions, that is, there were no people moving on the floor plan and the source, the relays and the destination were all standing still. This is not a requirement for the schemes to work but it makes it more likely that the schemes see the same propagation channels. The fact that some configurations in one measurement run are identical can be used to verify the similarity of the channel conditions under which the different configurations are tested. A total of 47 measurement runs were conducted. The positions of the two relays and the destination were changed before every run.

Each scheme transmitted ten payload frames of 48 symbols. The channel estimates obtained during these frames were saved and made available for postprocessing. We also calculate the bit error rate (BER) and the number of clock-cycles used by the DSPs. In addition to these metrics, some scheme specific results are also measured. The noise level was measured and found to be very similar on all antenna branches of all the nodes. In Figures 8 and 9 the cumulative distribution of the SNR of all propagation paths that are involved in the schemes is shown (the SNR is calculated by dividing the channel estimate level with the noise level of the receiver in question). The curves show that the relay 2 generally has a better channel to the source while relay 1 has better channel to the destination. The worst channel is that between the source and the destination. It can also be noted that the SNRs are very low which represents challenging conditions.

In Section 3.1 we do a straightforward analysis of the measurement results at hand while in Section 3.2 we do an analysis which provides more insight and is less dependent on the scenario chosen.

We have implemented four well-known cooperative relaying schemes: amplify-and-forward (AF), detect-and-forward (DF), cooperative maximum-ratio combining (CMRC), and distributed space-time coding (DSTC), and one novel scheme selection relaying (SR), see Section 2.

In the novel scheme, SR, we select one out of two relays, on a "slow" basis, that is, we only aim to select the relay which has the best channel in average (taking into account both the source to relay and the relay to destination path), that is, we do not aim to track the fast fading but only the path loss.

For the DF and DSTC we introduced a feature "selective" where the relay only forwards a frame if its receive SNR is better than a threshold (4 dB), and otherwise stays silent. For all schemes except AF, we also introduced antenna diversity by means of maximum ratio combining.

We measured the performance of all five schemes plus direct transmission (which is a reference case), with and without antenna diversity and the "selective" options. The measurements were done in an indoor office environment under challenging conditions, that is, all links experienced low signal to noise ratios. As shown in Section 3.1, all schemes improved the coverage area over direct transmission. The feature "selective" helped improve the performance of DF and DSTC significantly. Using antenna diversity was also an effective means for improving performance. The greatest performance improvements were achieved using DSTC and SR which utilise two relays. We also analysed the implementation loss of our implementations. This was obtained by calculating the theoretical BER based on measured channels from the source to the relays, from the relays to destination, and the direct path from the source to the destination. The number obtained was compared with the actual BER. By doing so it was evident that DF and DSTC need the "selective" option to function properly. Doing so DF and DSTC have an implementation loss of around 5 dB, while CMRC, AF, and SR has an implementation loss of around 2.5 dB. Direct transmission has the smallest implementation loss of approximately 1 dB. It was noted that CMRC performs better than AF, when counting the number of frames with bit errors while AF performs better than CMRC when a few errors are allowed.

We implemented our system on a floating point DSP and used 0.6% of its resources for channel estimation and detection. When increasing the bandwidth of the system the load on the DSP should increase proportionally to the bandwidth expansions. Surprisingly, the implementation of the amplify and forward technique is not less computationally expensive than the other approaches. This is related to the fact that we are using a TDD system and therefore the relay needs to synchronise, store, and forward the received signal. Finally, the AF solution needs more memory than, for example, DF since it does not store decoded bits but rather signal samples.