Adaptive antenna subset selection can improve the expected theoretical capacity of a multiple-input, multiple-output (MIMO) wireless channel, whilst maintaining the tractable complexity of the lower order MIMO system. This paper seeks to explore the effects of delayed selection using measured indoor channel data at 5.2GHz, reflecting more accurately the situation facing a real-time system. Several selection schemes are considered and results show that delayed selection, while not as effective as instantaneous selection, can still improve the expected capacity by a significant margi

Beach, MA

Murray, B

English

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                          Murray, B., & Beach, M. A. (2005). Delayed adaptive antenna subsetselection in measured wireless MIMO channels. (pp. 7 p). (COST 273),(TD(05)108).Link to publication record in Explore Bristol ResearchPDF-documentUniversity of Bristol - Explore Bristol ResearchGeneral rightsThis document is made available in accordance with publisher policies. Please cite only the publishedversion using the reference above. Full terms of use are available:http://www.bristol.ac.uk/pure/about/ebr-terms.htmlTake down policyExplore Bristol Research is a digital archive and the intention is that deposited content should not beremoved. However, if you believe that this version of the work breaches copyright law please contactopen-access@bristol.ac.uk and include the following information in your message:• Your contact details• Bibliographic details for the item, including a URL• An outline of the nature of the complaintOn receipt of your message the Open Access Team will immediately investigate your claim, make aninitial judgement of the validity of the claim and, where appropriate, withdraw the item in questionfrom public view.EUROPEAN COOPERATIONIN THE FIELD OF SCIENTIFICAND TECHNICAL RESEARCH—————————————————EURO-COST—————————————————COST 273 TD(05)108Lisbon, Portugal2005/Nov/09-11SOURCE: Centre for Communications Research,University of Bristol,U.K.Delayed adaptive antenna subset selection in measured wireless MIMOchannelsBen MurrayCentre for Communications ResearchMerchant Ventures BuildingWoodland roadBristolBS8 1UBU.K.Phone: + 44 117 331 5053Fax:   + 44 117 954 5206Email: ben.murray@bristol.ac.ukDelayed adaptive antenna subset selectionin measured wireless MIMO channelsB. Murray, M. A. Beach Centre for Communications Research, University of Bristol, U.K.ben.murray@bristol.ac.ukAbstract: Adaptive  antenna  subset  selection  can  improve  the  expected  theoretical  capacity  of  amultiple-input, multiple-output (MIMO) wireless channel, whilst maintaining the tractable complexity ofthe  lower  order  MIMO system.  This  paper  seeks  to  explore  the  effects  of  delayed  selection  usingmeasured indoor channel data at 5.2GHz, reflecting more accurately the situation facing a real-timesystem. Several selection schemes are considered and results show that delayed selection, while not aseffective as instantaneous selection, can still improve the expected capacity by a significant margin.IntroductionThe large potential increase in capacity over conventional single antenna systems offered by MIMOwireless systems [1] relies upon the availability of suitable spatial channels [2]. While these channelsare not always consistently present [3], antenna subset  selection offers a relatively simple way toimprove the chances of finding a more favourable MIMO channel, and can improve the reliability ofa wireless transmission. Gains of several b/s/Hz were seen [4] in the 90% capacity1 when selectionwas applied to a measured indoor 2x2 MIMO wireless channel. This paper investigates delayed subset selection on a 2x2 MIMO radio system with four transmitantennas  and  four  receive  antennas.  Selection  allows  the  2x2  system to  gain  improved  capacitywithout  requiring  the  extra  processing  channels  necessary  for  higher-order  MIMO  wirelesstransmission. In a real system however, selection is not likely to be instantaneous, as the signal mustbe received before it can be processed.Measured dataTwo sources of measured channel data were analysed with delayed subset  selection. Both sets ofchannel data were measured indoors, at a center frequency of 5.2GHz and 120MHz bandwidth, usingthe Medav RUSK BRI wideband multi-channel sounder. One set of data was the same as that used in[4],[5]. This was measured in the wireless lab at the University of Bristol (UoB) between two PDAform factor antenna units, as shown in Figure 1, one of which was rotated during the measurements.Each unit had two forward facing slot antennas of different polarities, a side facing slot antenna, andan upward facing slot antenna. Further details concering these PDA units and the measurements takencan be found in [4] and [5]. Results using this data are referred to as PDA-data. The other set of data was recorded using two laptop form-factor units, as shown in Figure 2, whichsported four antennas of the same type as those used on the PDA units. Each laptop unit had the fourantennas placed around the screen section, two upward facing with the same polarity, and one oneach side facing outwards. The laptop units were placed in various locations within the UoB wirelesslab  and  adjoining  office  environment.  They  remained  stationary  for  the  majority  of  themeasurements,  while  the  office  and  lab  environments  around  them changed  as  people  moved,simulating normal laptop usage in a typical  workplace.  Results  using this  data  are referred to aslaptop-data.1 In this paper, the 90% capacity refers to the capacity that a system is expected to achieve at least ninety percentof the time.   Figure 1. PDA unit and measurement location diagram  Figure 2. Laptop form-factor unit and antenna closeup.Delayed and periodic selectionThe analysis herein considered a 4x4 antenna system from which a 2x2 antenna subset was selectedfor transmission.  The selection system is described fully in [4] and is  summarised here for yourconvenience. There are thirty six possible combinations of 2x2 antenna subsets within a 4x4 antennasystem. Three switching metrics were used to perform selection. Received signal strength indicator(RSSI) selection chose the subset with the largest total received power. Singular value decomposition(SVD) selection chose the subset giving the largest minimum singular value. Capacity (Cap) selectionchooses the subset resulting in the largest theoretical capacity.Delay was introduced into the simulation by applying the antenna subset choice from each sample toa future sample, as opposed to applying the selection instantaneously. The number of samples bywhich the selection was delayed was variable. The results in this paper are shown for zero and fivesamples worth of delay. This simulated the processing time, often required in a real system, betweenreceiving  channel  information  and being  able  to  apply  the  knowledge  gained  from this  channelinformation at the receiver. Periodic selection was also tested where the system did not process the data to make a selection forevery sample.  Rather  a  selection  decision was only made once every  x samples,  where  x was avariable quantity. This was comparable to a real system where the radio did not have knowledge ofthe full  channel  all  of  the time and was receiving on the previously selected channel  subset  forseveral samples. The radio would then update the selection by periodically sampling the full  4x4channel to determine which antennas to use for the next group of received samples.ResultsFigure  3  displays the  complimentary cumulative  distribution  of  expected theoretical  capacity  forPDA-data with varying amounts of delay introduced during the selection process. The 90% capacitiesfor PDA-data can be found in Table 1. Figure 4 shows the expected capacities of the antenna subsetsfor the laptop-data, and the associated 90% capacities are displayed in Table 2.As expected, delay reduced the effectiveness of the antenna selection and reduced the improvementin 90% capacity when compared with the zero delay case. It did still show an improvement of severalb/s/Hz over the average expected capacity of the fixed channels available. PDA-data, with a delay of5 samples, achieved approximately 2.5 b/s/Hz improvement over the average channel for receivedsignal strength indicator (RSSI) based selection, 2.9 b/s/Hz for singular value decomposition (SVD)based selection and 3.2 b/s/Hz for selection by capacity. With no delay the improvements were 3.3b/s/Hz for RSSI, 4.4 b/s/Hz for SVD, and 4.8 b/s/Hz for capacity selection. Selection by capacity wasthe  optimal  selection  method for  this  comparison.  Longer  delays  typically  reduced the  expectedcapacity further, but even with 5 samples of delay a significant improvement over the average fixedchannel was still seen. The resulting 90% capacities are given in Table 1.For the  laptop-data,  an improvement  was also  observed for  the  90% capacities  of  the  selection-enhanced subsets over those of the the average fixed antenna subset values. The detrimental effect ofdelay on the selected laptop-data capacities was not as pronounced as is was for the PDA-data. Thelaptop-data typically showed a few dominant fixed antenna subsets. This was probably due to the factthat the laptop form-factor units remained relatively stationary and the environment did not changecontinuously as it would have done for the PDA units, which were rotated during their measurements.Other PDA-data and laptop-data tested showed similar improvements in 90% capacity when selectionwas employed with and without delay. Introducing a periodic selection process resulted in similardrops in improvement when compared to selection with zero delay. The resulting expected capacitieswith periodic delay are shown in Figure 5 for PDA-data and in Figure 6 for laptop-data.Table  1  and Table  2  show the  90% capacity  values  for  PDA-data  and laptop-data  respectively.Figures are shown for selection with zero delay and selection with a delay of five samples. The finalcolumns show the 90% capacity values for selection with a periodic delay of three,  meaning theselected subset was only updated every third sample.Channel 90% capacity, delay=0 90% capacity, delay=5 90% capacity, period=3Worst case fixed 5.8 5.8 5.8Best case fixed 9.5 9.5 9.5Average fixed 7.3 7.3 7.3Capacity choice 12.1 10.5 11.4SVD choice 11.7 10.2 10.9RSSI choice 10.7 9.9 10.4Table 1. 90% capacity data for PDA dataChannel 90% capacity, delay=0 90% capacity, delay=5 90% capacity, period=3Worst case fixed 5.6 5.6 5.6Best case fixed 11.9 11.9 11.9Average fixed 7.9 7.9 7.9Capacity choice 13.4 13.1 13.3SVD choice 13.0 12.6 12.9RSSI choice 12.7 12.5 12.6Table 2. 90% capacity data for laptop dataFigure 3. Expected capacity for PDA-data without delay (black) and with a delay of 5 samples (grey)Figure 4. Expected capacity for laptop-data without delay (black) and with a delay of 5 samples (grey)Figure 5. Expected capacity for PDA-data selection with periodic delayFigure 6. Expected capacity for laptop-data selection with periodic delayPeriodic selection introduced a slight decrease in improvement for the PDA-data and for the laptop-data, when compared to selection with zero delay. It did still provide a significant improvement overthe expected capacity of the average fixed subset. The decrease in improvement because of periodicselection was not as pronounced for laptop-data as it was for PDA-data. The laptop-data showed lessvariable channels and selection decisions would have been valid for a reasonable number of samples.In some cases  one  antenna  subset,  out  of  the  thirty-six  available,  prevailed  almost  uniquely  asproviding the  greatest  capacity throughout  the measurement  set.  Without  selection however,  thissubset might not have been realised, and subset selection is still a useful tool for such conditions.ConclusionsIn MIMO applications where user devices are equipped with more antenna elements than MIMOprocessing channels, dynamic antenna subset selection can provide an increase in expected capacity.Delayed  antenna  subset  selection,  whilst  not  being  as  effective  as  instantaneous  antenna  subsetselection  in  all  cases,  still  improved  the  90% capacity  of  the  measured  indoor  wireless  MIMOchannels tested by several b/s/Hz, over that of the average fixed antenna subset. For situations wherethe channel was not varying constantly, and where the transceiver units were relatively stationary,delayed antenna subset selection produced an improvement over the average fixed subsets almostequal to that of subset selection without any delay. These results show that dynamic subset selectioncould be a useful method of improving some real-time wireless MIMO systems for a minimal costwhilst exhibiting tractable complexity.AcknowledgementsThe Author would like to thank T. Horseman for his input regarding real-world radio issues and M.Hunukumbure for  useful  discussions  concerning channel  measurements  and data  processing.  Thework reported in this paper has formed part of the OSIRIS project within the 3C Research programmeof convergent technology research for digital media processing and communications whose fundingand support is gratefully acknowledged. For more information please visit www.3cresearch.co.uk.References[1] G.J. Foschini, M.J. Gans, “On limits of wireless communication in a fading environment whenusing multiple antennas”, Wireless Personal Communications, Vol. 6, No. 3, 1998, pp.311-335.[2] D-S. Shiu, G. J. Foschini, M. J. Gans, and J. M. Kahn, “Fading Correlation and its effect on theCapacity  of  Multi-Element  Antenna  Systems”,  IEEE International  conference  on  Universalpersonal communications (ICUPC’98), vol. 1, pp. 429–433, October 1998.[3] C. Williams et al, “Antenna Array Technology and MIMO Systems”, doc 8366CR2, deliverableto  Ofcom,  June  04,  pages  50,  126-139,  147-148,http://www.ofcom.org.uk/research/technology/ses/ses2003-04/ay4476b/[4] B. Murray, M. A. Beach, “Adaptive Antenna Subset Selection in MIMO Channels”, 3g2005,London, November 2005.[5] M. A. Beach, M. Hunukumbure, C. Williams, G. S. Hilton, P. Urwin-Wright, M. Capstick, andB.  Kemp,  “An  experimental  evaluation  of  three  candidate  MIMO array  designs  for  PDAdevices”, COST 273/284 Workshop, June 2004.

Adaptive Antenna Subset Selection

An experimental evaluation of three candidate MIMO array designs for PDA devices”, COST 273/284 Workshop,

Antenna Array Technology and MIMO Systems”, doc 8366CR2, deliverable to Ofcom,

Fading Correlation and its effect on the Capacity of Multi-Element Antenna Systems”,

On limits of wireless communication in a fading environment when using multiple antennas”,

Delayed adaptive antenna subset selection in measured wireless MIMO channels

Delayed adaptive antenna subset selection in measured wireless MIMO channels

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