**6. Visible light communications: the new challenge**

Visible light communications (VLC), first proposed by researchers at Keio University in Tokyo [18, 19] have prompted the interest of the scientific community in the last few years [7, 11, 17, 25, 29]. There have also been regulatory efforts made on this technology that have led to the appearance of a standard [13]. These new VLC systems, using visible LED lamps to simultaneously transmit information together with their normal use as illumination devices, share the same advantages as their infrared counterparts [15]. They are also eye-safe (visible light is not harmful to the human eye), which enables the use of higher transmission powers. However, the main drawback is the limited transmission bandwidth of current LED devices, typically several MHz, and whose enhancement has been one of the main issues addressed by researchers [23, 24]. Zeng et al. [29] have proposed the use of MIMO schemes based on imaging receivers in order to obtain high capacity VLC networks. Additionally, the OFDM technique has been proved to be a feasible candidate to obtain these high-speed networks [20], demonstrating impressive experimental data rates for short-range communications [27, 28].

Therefore, it appears to be clear that combining OFDM technique and imaging reception could be an interesting research field for the future. Table 3 shows the main parameters of a simulation scenario in which MIMO-OFDM, based on imaging reception, is evaluated. Fig. 9 illustrates the images of the LED arrays on the pixelated imaging receiver at two different positions in the room at a height of 0.75 m, which have been obtained by using a paraxial optic approach, as in the work by Zeng et al. [29]. The performance results of the multi-user LS receiver for these two positions of the detector array are compared in Fig. 10. In order to carry out a fair comparison, the BER performance is shown versus the maximum SNR observed at the receiving pixels for the emissions from the lamp *l* = 6, which is located the furthest from the detector, when this is positioned close to the corner (Fig. 9(b)), i.e. max(SNR(*l*=6,pos=b) *<sup>j</sup>* ), *j* = 1, . . . , *P*. Here, the case labelled as *L* = 6 is referred to the aggregate system BER (considering those of all the users *l* = 1, . . . , *L* jointly). Regarding those labelled as *L* = 1, they represent the single-user performances for the user *l* = 6 (the worst). Finally, *P*min denotes the number of receiving channels (pixels) required for a correct joint demodulation, which is always 8 (those illuminated by the lamps, see Fig. 9). We can observe that the detector, when located close to a corner, requires more than 40 dB in the SNR to make the BER drop below 10−<sup>6</sup> when considering the aggregate performance. This represents a SNR loss of roughly 20 dB with respect to its corresponding single-user scenario. In contrast, evaluated under the same illumination conditions (versus the maximum SNR(*l*=6,pos=b) *<sup>j</sup>* ), the receiver at the centre of the room requires more than 15 dB less electrical power to obtain the same aggregate performance. Although these SNR values could be practical in a VLC


410 Optical Communication Multiple-Input Multiple-Output (MIMO) Optical Wireless Communications <sup>19</sup> Multiple-Input Multiple-Output (MIMO) Optical Wireless Communications 411

**Table 3.** Parameters for simulation

18 Will-be-set-by-IN-TECH

Outside the OFDM context, there are other multiple works addressing MIMO techniques for indoor wireless optical communications, which are generally applied in conjunction with conventional optical modulation schemes (on-off keying, pulse-position modulation, etc.). The main idea of an important group of them relies on creating many nearly-ideal and independent channels between a specific user and receiver by using multibeam transmitters and angle-diversity receivers [1, 14]. Imaging receivers have also been proposed to greatly increase the number of receiving channels at a reduced cost [6, 16], hence providing higher data rates [3, 29]. Sometimes, the distinctive spatial nature of the channel, which is unique, between a specific transmitter and the receiver is exploited to carry additional information as

Visible light communications (VLC), first proposed by researchers at Keio University in Tokyo [18, 19] have prompted the interest of the scientific community in the last few years [7, 11, 17, 25, 29]. There have also been regulatory efforts made on this technology that have led to the appearance of a standard [13]. These new VLC systems, using visible LED lamps to simultaneously transmit information together with their normal use as illumination devices, share the same advantages as their infrared counterparts [15]. They are also eye-safe (visible light is not harmful to the human eye), which enables the use of higher transmission powers. However, the main drawback is the limited transmission bandwidth of current LED devices, typically several MHz, and whose enhancement has been one of the main issues addressed by researchers [23, 24]. Zeng et al. [29] have proposed the use of MIMO schemes based on imaging receivers in order to obtain high capacity VLC networks. Additionally, the OFDM technique has been proved to be a feasible candidate to obtain these high-speed networks [20], demonstrating impressive experimental data rates for short-range communications [27, 28]. Therefore, it appears to be clear that combining OFDM technique and imaging reception could be an interesting research field for the future. Table 3 shows the main parameters of a simulation scenario in which MIMO-OFDM, based on imaging reception, is evaluated. Fig. 9 illustrates the images of the LED arrays on the pixelated imaging receiver at two different positions in the room at a height of 0.75 m, which have been obtained by using a paraxial optic approach, as in the work by Zeng et al. [29]. The performance results of the multi-user LS receiver for these two positions of the detector array are compared in Fig. 10. In order to carry out a fair comparison, the BER performance is shown versus the maximum SNR observed at the receiving pixels for the emissions from the lamp *l* = 6, which is located the furthest from the detector, when this is positioned close to the corner (Fig. 9(b)), i.e.

*<sup>j</sup>* ), *j* = 1, . . . , *P*. Here, the case labelled as *L* = 6 is referred to the aggregate

*<sup>j</sup>* ), the

system BER (considering those of all the users *l* = 1, . . . , *L* jointly). Regarding those labelled as *L* = 1, they represent the single-user performances for the user *l* = 6 (the worst). Finally, *P*min denotes the number of receiving channels (pixels) required for a correct joint demodulation, which is always 8 (those illuminated by the lamps, see Fig. 9). We can observe that the detector, when located close to a corner, requires more than 40 dB in the SNR to make the BER drop below 10−<sup>6</sup> when considering the aggregate performance. This represents a SNR loss of roughly 20 dB with respect to its corresponding single-user scenario. In contrast, evaluated under the same illumination conditions (versus the maximum SNR(*l*=6,pos=b)

receiver at the centre of the room requires more than 15 dB less electrical power to obtain the same aggregate performance. Although these SNR values could be practical in a VLC

in optical spatial modulation [22].

max(SNR(*l*=6,pos=b)

**6. Visible light communications: the new challenge**

**Figure 9.** Images of the LED arrays on the detector at two positions

environment, it is evident that moving towards corners degrades enormously the aggregate performance due to the long distances and low inclination of the rays coming from the furthest lamps. Hence, it would be a more efficient solution to employ higher-order modulation modes (greater values of *B*) for the lamps closer to the receiver and lower ones for those further away, even deactivating them as necessary, by using adaptive OFDM schemes [9]. In any case, what seems apparent, according to these preliminary results, is that MIMO-OFDM with imaging reception is a promising technique, which is worthy of further work.

**Figure 10.** Performance comparison of multi-user LS detection based on imaging reception for two positions of the detector array

## **7. Conclusions**

In this chapter, the employment of multi-user LS detection in conjunction with angle-diversity receivers and OFDM modulation technique for wireless optical communication has been evaluated. The MIMO optical channel model, which can be determined by using Monte Carlo-based ray-tracing algorithms, has been described in detail. This algorithm allows us to determine LOS and multiple-bounce reflection contributions to the received optical power at the photodetector, which enables a more accurate analysis of the proposed system performance. The multi-user detector, which is based on the linear combining of the incoming signals at its receiving branches, is shown to have a performance very close to that of the optimum ML detector. Additionally, it has been observed that strategies to find the truly significant receiving branches, during the data retrieving for a specific user, can be applied to reduce the complexity of the demodulation problem while maintaining and, even improving, the system performance. The results have also shown that aggregate high data rates can be obtained for indoor wireless optical communications at practical signal-to-noise ratios. Finally, the proposed multi-user OFDM system has been assessed for a visible-light communication scenario, where imaging reception is assumed. The preliminary results show that the previous scheme is an attractive candidate for developing high-capacity VLC networks, but further research still needs to be carried out.
