SpaceHub: A Smart Relay System for Smart Home

Meng Meng1,2 ∗, Lizhao You1,3 ∗, Kun Tan1, Jiansong Zhang1, Wenjie Wang2

1Microsoft Research Asia, Beijing, China2Xi’an Jiaotong University, Xi’an, China

3The Chinese University of Hong Kong, Hong Kong, China{v-memeng,kuntan,jiazhang}@microsoft.com,yl013@ie.cuhk.edu.hk,wjwang@xjtu.edu.cn

ABSTRACTWith the proliferation of smart wireless devices in ourhomes, the cross-technology interference increasingly be-comes an important issue. This paper presents a novelsmart relay system, called SpaceHub, which leveragesan multi-antenna relay node to mitigate cross-technologyinterference for all communicating devices which mayonly have single antenna. In SpaceHub, the relay nodeoverhears wireless communications in the air, separatesthe collided signals, and forwards the separated (cleaned)signals to their intended receivers without a prior knowl-edge of the wireless signal structures. The core compo-nent of SpaceHub is a blind signal separator that con-structs spatial filters using the angle-of-arrival informa-tion of collided signals. We have implemented Space-Hub on a software radio platform and our evaluationshows SpaceHub signal separator can suppress the in-terference up to 23dB, and is robust against the poweror relative locations of interfering signals.

Categories and Subject DescriptorsC.2.1 [Computer Communication Networks]: Net-work Architecture and Design–Wireless communication

KeywordsRelay; Antenna Array; Spatial Filter; Internet of Things

1. INTRODUCTIONOver last few years, we have witnessed a prolifera-

tion of wireless technologies that increasingly becomeubiquitous in our everyday life. With this global wave

∗This work was performed while Meng Meng and LizhaoYou were research interns at Microsoft Research Asia.

Permission to make digital or hard copies of all or part of this work forpersonal or classroom use is granted without fee provided that copies arenot made or distributed for profit or commercial advantage and that copiesbear this notice and the full citation on the first page. To copy otherwise, torepublish, to post on servers or to redistribute to lists, requires prior specificpermission and/or a fee.HotNets ’15 November 16–17 2015, Philadelphia, PA USACopyright 2015 ACM 978-1-4503-4047-2/15/11 ...$15.00http://dx.doi.org/10.1145/2834050.2834073.

of Internet-of-Things (IoT), more and more intelligentdevices are deployed in our home and interconnectedwith many heterogeneous wireless technologies. How-ever, most of these wireless technologies are crowded inthe same unlicensed frequency bands. For example, Wi-Fi, ZigBee, Bluetooth, Digital cordless phone, and manyother proprietary wireless technologies for surveillancecamera or remote controller, all operate on the same2.4GHz ISM band. Consequently, interference amongthese wireless technologies may result in unreliable com-munication or low network throughput.

Some conventional coexisting technologies try to addmore redundancy [5] to tolerate more interference. Someother technologies manage to avoid interference by schedul-ing transmissions over different channels [11,12] or timeslots [4, 13]. However, these solutions are not very ef-fective. Adding redundancy reduces the communicationdata rate and thus sacrifices the spectrum efficiency. Atthe same time, the scheduling based solutions essen-tially divide the limited wireless capacity to each user.The throughput of each user will drop with increasingnumber of competitors.

Recently, several research has explored to use MIMOcapability to handle cross-technology interference [2,10].These solutions require one or both communication side(s)to equip multiple antennas and use a portion of degree-of-freedom (DoF) to nullify interference. However, asadding multiple antennas significantly adds device size,cost and power consumption, none of them could sup-port all wireless communications inside a smart home,where many IoT devices are just small sensors and em-bedded actuators and infeasible to add multiple anten-nas.

In this paper, we present a novel system, named Space-Hub, that utilizes MIMO technologies to mitigate cross-technology interference even if all communicating de-vices have only single antenna. Our idea is to deploya multi-antenna relay that overhears wireless communi-cations in the air, separates the collided signals if any,and forwards the separated (cleaned) signals to theirintended receivers.

One primary design goal of SpaceHub is to be wire-less technology agnostic, which can enable following niceproperties: First, the existing wireless devices can beeasily configured to work with SpaceHub. Neither thehardware structure nor the physical layer setting of thedevice needs to be modified. Second, SpaceHub canhelp any emerging wireless technology without a prioriknowledge of its physical/MAC layer design. Finally,SpaceHub improves the spectrum efficiency of all wire-less technologies with spatial multiplexing even if allcommunicating devices are only with single antenna.

Being wireless technology agnostic is not trivial. Con-ventional MIMO systems need to measure the wirelesschannel coefficients from known symbol structures (e.g.,preambles), and these channel coefficients are critical toseparate mixed signals. However, for SpaceHub, it is in-feasible to perform such measurements as the wirelesssignals in question are unknown. To this end, one coretechnique in SpaceHub is a blind signal separator thatcan reliably separate multiple spatial streams withouta priori knowledge of the signal structure. Our signalseparator is motivated by the Angle-of-Arrival (AoA)detection mechanism used in wireless localization sys-tems [3,9]. But unlike previous work, SpaceHub utilizesthis AoA information to construct a set of spatial fil-ters to separate signals arrived from different directions.Further, SpaceHub identifies the multi-path reflectionsfrom a same source and combine them to enhance thesignal strength. Finally, with a proper antenna place-ment and a cancellation technique, SpaceHub can alsoseparate signals from different sources even if they arecoming along close directions.

We have implemented SpaceHub on Sora MIMO kit.Evaluation results show our separation algorithm couldimprove the SINR of collided signal by an average of15dB (up to 23dB). The signal separator is robust againstthe interference signal strength as well as the relative lo-cations of interfering sources – even the signals arrivingfrom the same direction can be precisely separated. Fi-nally, We also observe about 4dB SINR improvementto combine multipath components of one signal sourcefrom several different directions.

In summary, our contributions are: 1) To our bestknowledge, SpaceHub is the first smart wireless relaysystem that uses multi-antenna technology to mitigatecross-technology wireless interference and separate col-lided signals. 2) We design a novel blind signal sepa-rator. 3) We implement and evaluate SpaceHub on asoftware radio platform.

2. BACKGROUND2.1 MIMO Primer

Conventionally, a 2 × 2 MIMO system works as fol-lows. Two transmit antennas send signal s1(t) and s2(t)respectively, then the received signals on each receiver

antenna can be expressed as

x1(t) = h11s1(t) + h12s2(t)

x2(t) = h21s1(t) + h22s2(t)

where hik represents the channel coefficient from trans-mit antenna k to receiver antenna i.

If the receiver knows the channel coefficient hik, itcan separate the two unknown signals, i.e., s1(t) ands2(t), by solving the above equations. In a conventionalMIMO system, to estimate hik, the transmitter needsto send a training signal (i.e., preamble) that is knownto the receiver in advance.

Unfortunately, in SpaceHub, we cannot assume thatthe signal structure is always available (i.e., being wire-less technology agnostic). As a consequence, we can-not acquire channel coefficients through such measure-ments. To address this challenge, we observe that sig-nals from different sources may be distinguished throughtheir spatial locations. Essentially, we can design a spa-tial filter which can only receive the signal from an in-terested direction but attenuate all signals from otherdirections.

2.2 AoA EstimationThe basic idea in SpaceHub is to utilize the difference

in angles of arriving (AoA) from multiple transmittersto separate the concurrent signal streams. Therefore,AoA estimation is a basic component of the SpaceHub.In the following, we introduce the widely used MUSICalgorithm [6] which is employed in our design.

Consider a simple case in Fig.1. There is a receiverwith M antennas evenly spaced on a straight line. Theantenna separation is λ/2 (half-wavelength).Two signalsources are placed far apart, and the distances fromeach source to the first antenna of AP are d1 and d2,respectively. The signal from each source has a line-of-sight path to the AP antenna array, with attenuationsa1 and a2 and angles of incidence θ1 and θ2.

Assume that xi(t) is the received signal at ith antennaat time t, we get the receiver vector X(t)

x1(t)x2(t)

...xM (t)

=

1 1

e−jπcosθ1 e−jπcosθ2

......

e−j(M−1)πcosθ1 e−j(M−1)πcosθ2

[a1e− j2πd1λ 0

0 a2e− j2πd2λ

] [s1(t)s2(t)

]+

n1(t)n2(t)

...nM (t)

(1)

If we define array steering vector a(θ) as

a(θ) = [1 e−jπcosθ . . . e−j(M−1)πcosθ]T (2)

we can see that the value of a(θ) only depends on theincoming signal’s direction.

MUSIC algorithm exploits the eigenspace of data’s co-variance matrix Rx = E{XXH}, where (.)H representsthe Hermitian of a vector(the conjugate transpose). As-suming the incident signals are uncorrelated to noise,MUSIC splits the eigenspace of R into signal-subspaceand noise-subspace. While the eigenvectors Us corre-sponding to the largest D eigenvalues span the signal-subspace, the remaining M − D eigenvectors Un spanthe orthogonal space, saying noise-subspace. Note thatall array steering vectors a(θ) which describe D signals,are orthogonal to the noise-subspace.

Thus, MUSIC plots the spatial spectrum as

PMUSIC(θ) =1

aH(θ)UnUHn a(θ)(3)

when θ is a signal direction, the denominator becomeszero and yields a sharp peak in the spatial spectrum.

Figure 1: Two geographically separated signalsources to a receiver antenna array.

3. SpaceHub ARCHITECTURE

Figure 2: SpaceHub overview.

SpaceHub leverages a MIMO relay node to separateand forward collided signals from multiple wireless trans-mitters. Commonly, this MIMO relay can be integratedtogether into a Wi-Fi access point (AP), as shown inFig. 2.

SpaceHub keeps monitoring the wireless medium, andemploys a blind signal separation technique onto thereceived signals. The signal separation starts from theAoA estimation, where SpaceHub searches the spatialspectrum and finds directions of all incoming signals.

Then, for each direction in which a signal is detected,SpaceHub constructs a Spatial Filter to steer the an-tenna array to amplify the signal from this direction,but attenuate signals from other directions. After ex-tracting signals from all directions, SpaceHub furtherclusters these signals into groups, so that each groupcontains multi-path components from a same sender.These multi-path components may come from differ-ent directions (due to reflections), but should be com-bined together to reconstruct the original wireless sig-nal. Clearly, if SpaceHub finds more than one group,there is a collision.

After all signals are separated (and combined), Space-Hub relays them to their intended receivers. In this pa-per, since SpaceHub is integrated with a Wi-Fi AP, itwill first detects Wi-Fi signals according to the physicallayer features. All Wi-Fi signals are just fed to localdecoder (Fig 2), but other signals are amplified and for-warded to their destinations.

There can be two possible ways to forward signals.Firstly, SpaceHub can directly broadcast all relay sig-nals one by one. But this will take n time slots to npackets in a collided transmission. Alternatively, Space-Hub could leverage its multi-antenna capability to for-ward multiple signals simultaneously using beamform-ing. In §4.2, we will discuss how to enable this beam-forming forward, but leave the implementation and de-tailed evaluation as our future work.

There are also two points worth noting. First, theAoA method has a fundamental limitation to distin-guish different signals from the same direction. There-fore, if two wireless devices are aligned in the same di-rection with respect to SpaceHub’s antenna array, Space-Hub may not be able to separate their collided sig-nals. We address this issue by augmenting SpaceHubwith a second antenna array and an intelligent cancel-lation algorithm (§4.1). Second, the relay behavior ofSpaceHub will interact with some existing MAC pro-tocols. For example, Wi-Fi requires the receiver tosend a synchronous ACK after receiving a data packetwithout performing carrier-sensing. This synchronousmay collide into other on-going relay transmissions ofSpaceHub. To remedy this, we need slightly modifica-tions on these MAC protocols to sense wireless channelfor ACK packets as well1. This is similar to previouswork [14, 15] that requires MAC to be relay friendly.We note that ACK-to-ACK collision may not be an is-sue here as SpaceHub can help to separate and forwardACK packets as well. However, a complete MAC designis defered as our future work.

4. SpaceHub DESIGN1The ACK timeout mechanism at the sider side may alsoneed to modify slightly to accommodate the increased delayin ACK.

4.1 Blind Signal SeparationRecall that SpaceHub uses a spatial filter to separate

signals from different directions. The spatial filter isto steer the array’s beam pattern in one direction byforming a linear combination of the antenna outputs

sk(t) =

M−1∑n=0

w∗nxn(t) = WHX (4)

For our separation purpose, the spatial filter should beable to suppress other signals (i.e., interfering sources)as much as possible. We adopt an optimal filter thatmaximizes signal to noise plus interference ratio (SINR).

Assume the desired signal s0(t) is from direction a(θ0),and sk(t)(k = 1, · · · , D−1) represents other signals con-sidered as interference sources. The optimal weight isWopt = γR−1u a(θ0), where Ru is the covariance matrixof noise and interference, and γ = 1

aH(θ0)R−1u a(θ0)

is a

constant scale.However, applying above filter is not enough to ex-

tract each unique signal from collision signals. We willpresent further processing in the following sections.

4.1.1 Multipath Identification and CombinationSome separated signal streams may contain multi-

path components from the same transmitter. Simplyforwarding all of them is clearly a waste of resource(e.g., time slots). Instead, in SpaceHub, we combineeach signal stream’s multipath components to enhancethe source signal.

Identification: Before combination, SpaceHub needsto first identify the source of each separated signal stream.The core idea is that all separated signal copies from oneunique source should show a strong correlation, whereassignal streams from different sources are uncorrelated.Therefore, SpaceHub clusters all the separated signalstreams into several groups according to their cross cor-relation. Each group is considered as multipath compo-nents of a single source, and then combined into a singlesignal stream. However, a problem may occur when aseparated signal contains components from two distinctsources (combined copy), i.e., two sources are in thesame direction for SpaceHub. In this case, this com-bined copy will be identified as a path of two signals bymistake. We will discuss how to further differentiate acombine copy from a pure signal in Sec.4.1.2.

Combination: We use a maximal ratio combina-tion algorithm to combine the multipath components.Considering a signal s1(t) which propagates along twopaths before arriving at the antenna array, after sepa-

ration we obtain two copies y1(t) = a1e− j2πd1λ s1(t) and

y2(t) = a2e− j2πd2λ s1(t), where a1 and a2 are real number

scalars. Their cross correlation is

R12(τ) = E{y∗1(t)y2(t+ τ)}

= a1a2ej2π(d2−d1)

λ E{y∗1(t)y1(t+ τ)}(5)

let τ = 0, the phase offset ∆β can be estimated byarctanR12(0). Then the signal after maximal ratio com-bination is

s1(t) = s1(t) + ej∆βs2(t) (6)

4.1.2 Signal Separation from Same DirectionSince the spatial filter extracts signals based on AoA

difference, it has an inherent limitation to differentiatesignals coming from the same direction.

In SpaceHub, we leverage multiple phase arrays tofurther separate independent signals from one direction.The intuition is that, the AoA profiles vary from onelocation to another. The signals mixed in the AoA pro-files in one phase array may be separable in the profile ofanother array with high probability. SpaceHub jointlyprocesses the signals from two separate phase array an-tennas to reduce the occurrence of inseparable signals.

To illustrate our algorithm, let us consider two phasearrays and two sources in the same direction. For phasearray P, assume the signal copy y1(t) separated fromangle θ1i is a combined signal of source s1(t) and s2(t).For phase array P’, the best case is that we can separatethe two pure signal copies s1(t) and s2(t) respectively.If so, we can just discard this combined signal copy atarray P. However, in some cases, we may just obtain onepure s1(t) but another signal, s2(t), may be combinedwith another different source. Assume y′1(t) is the solesignal s1(t) from angle θ2i . In this way, the receivedsignals can be written as

y1(t) = α1s1(t) + α2s2(t) + n1

y′1(t) = α3s1(t) + n2

where αi(i = 1, 2, 3) denotes the remaining complexscalar after spatial filter, which are unknown.

Cancellation: We exploit the independence of s1(t)and s2(t) to obtain s2(t) from combined signal copyy1(t). Specifically, we can compute a complex scalarh such that y1(t) − hy′1(t) is uncorrelated with y′1(t).Therefore, we can have E{(y1(t) − hy′1(t))y′1(t)} = 0.That is

h =E{y1(t)y′1(t)}E{y′1(t)y′1(t)}

(7)

and the relay can obtain the forwarding signal s2(t) =y1(t)− hy′1(t).

Identification: Another question is how SpaceHubknows y1(t) is the combined signal copy of s1(t) ands2(t). Similar to the identification of multipath signals,SpaceHub applies a preprocessing algorithm to clustersignal copies based on cross correlation results. In par-ticular, SpaceHub identifies the combined copy from the

pure one based on the following observation: For signalcopy yk(t) obtained from phase array P, all the signalsfrom phase array P’ coherent with yk(t) form a groupG′(k) = {y′i(t)|i = 1, 2...}. yk(t) is a combined copy ifand only if there exist two signal copies within y′i un-correlated with each other.

Then, SpaceHub clusters all pure copies from onephase array into several groups by their correlation re-lationships as discussed in Sec. 4.1.1.

4.2 Beamforming ForwardingWe briefly discuss simultaneous signal forwarding us-

ing beamforming. To achieve beamforming, we need toaddress following two practical issues.

First, we need to figure out the destination of a signalstream. It is not straightforward as the signal struc-ture is not available, and therefore we will not be ableto identify the destination by decoding the MAC ad-dress. However, we still can leverage several wirelessproperties to design a learning scheme. For example, assignal streams from different wireless technologies havedistinct physical layer patterns, SpaceHub can classifysignal streams into different groups according to theirphysical layer features. Moreover, since many wirelesstechnologies require ACK from receivers, this MAC be-havior can be utilized to link a source device to a des-tination device. Once it needs to forward a signal fromsource i, it will find all devices connected to source i,and beamform the signal to all these devices. The sig-nal’s intended destination will receive this packet, andother receivers will reject it.

Second, we need a new precoding technique that doesnot require channel coefficients. Again, it is due to thefact SpaceHub is wireless technology agnostic. How-ever, we can reconstruct the precoding filter using AoAinformation similar to the separation filter. We deferthis beamforming forwarding as our future work.

5. EVALUATIONWe implement SpaceHub on latest Sora MIMO kits

[7]. There are total 14 antennas2 that are connectedto a back-end server through Ethernet. These antennasform two phase subarrays. The distance between twosubarrays is about 1 meter. The distance between twoantennas in each subarray is 6 centimeters. We adopta trace-driven approach to evaluate the separation per-formance in this section.

5.1 Spatial FilterMethod: A Wi-Fi device and a Zigbee device are

placed around the antenna array, and are activated tosend packets periodically on an overlapped channel (i.e.,

2With four Sora MIMO kits, we can equip 16 antennas intotal. However, for each phase array, we need a special ra-dio to calibrate initial phase. So the number of antennasconstituted in each phase array is 7.

channel 9 for Wi-Fi, and channel 20 for Zigbee). Wechoose Zigbee signal as the test signal, and choose Wi-Fi signal as the interference. We measure the SINR ofZigbee signal as

EzigbeeEwifi+En

, where Ezigbee and Ewifi are

Zigbee and Wi-Fi signal power, and En is the noise.To compute the original Zigbee SINR before separa-

tion, we let Wi-Fi and Zigbee send their signals alone,and measure Ezigbee, Ewifi and En directly. To com-pute the Zigbee SINR after separation, we let Wi-Fi andZigbee transmit simultaneously, and apply the spatialfilter defined in Sec. 4.1 to get the overall power ES.I.N .Then, we silence Zigbee signal, and apply the same filterto get the interference plus noise power EI.N .

We conduct two sets of experiments. First, we fix theangle between two devices, and vary the transmissionpower of Wi-Fi from 5dB to 25dB. For each case, wecapture 5 traces and each trace contains around 100mssignal. From these received packets, we pick up 8 col-lision packets for signal separation and SINR evalua-tion. Second, we fix the transmission power of Wi-Fi at10dB, and vary the angle between two devices from 10◦

to 120◦. For each angle, we do similar measurements asabove. In both experiments, the Zigbee SNR is 10dB.

Results: The results are shown in Fig. 3. We cansee that the original Zigbee SINR shows a sharp reduc-tion along with increasing interfering power in Fig. 3(a).However, our separation algorithm restores the signalSINR to around 10dB, although the SINR decreasesslightly as the interference increases. Meanwhile, Fig. 3(b)shows our separation also works for various angles. Therestored SINR is around 10dB. These results indicatethat our separation algorithm is robust again interfer-ing power and angles.

-15

-10

-5

0

5

10

15

5 10 15 20 25

SNR of Interference (WiFi) (Unit: dB)

Original Zigbee SINR Zigbee SINR after Separation

Zigb

ee

SIN

R (

Un

it:

dB

)

(a) Vary interfer power

-5

0

5

10

15

20

10 30 60 90 120

Angle Between Zigbee and WiFi (Unit: degree)

Original Zigbee SINR Zigbee SINR after Separation

Zigb

ee

SIN

R (

Un

it:

dB

)

(b) Vary devices angle

Figure 3: The SINR comparision of Zigbee

5.2 Multipath Identification AccuracyMethod: We place Wi-Fi and Zigbee devices ran-

domly in 9 different locations. For each location, they

send packets periodically with random SNR values. WhenZigbee keeps silent, we record the arriving angles of sep-arated signal copies as ground truth of Wi-Fi’s mul-tipath. Similarly, we can record the ground truth ofZigbee’s multipath. If two devices locate in the samedirection for any one subarray, we record this directionas ground truth of combined signal copy.

We use the following metrics to evaluate the per-formance of identification accuracy: 1) False positive:it measures the probability that SpaceHub incorrectlyalarms the presence of a path in one direction. 2) Falsenegative: it measures the probability that SpaceHubfails to detect the presence of a path in one direction.

Results: Table 1 shows that our algorithm has a su-per low False Negative Rate of multipath identification,which implies it achieves an average identification accu-racy rate of 99%. Overall, it performs well in identifyingsignal copies, which is the basis for further multipathcombination and signal separation from same direction.

Signal Type False Positive False Negative

Wi-Fi 0.030 0.008

Zigbee 0.018 0.010

Combined Signal 0.028 0

Table 1: Multipath Identification Accuracy.

5.3 Multipath Combination and Signal Sepa-ration from Same Direction

Multipath Combination: Based on the traces cap-tured in section 5.2, we measure the Zigbee SINR beforeseparation, SINR of direct path and SINR after combi-nation for 9 different locations. As shown in Fig. 4(a),multipath combination can enhance signal SINR on av-erage by about 4dB.

Signal Separation from Same Direction: Weplace Wi-Fi and Zigbee devices in 5 different locations.For each location, they locate in a line for one subar-ray. We measure the SINR increase of Zigbee signal asbefore, and plot the evaluation results in Fig. 4(b). Wecan see that even though two signal sources arrive atone subarray from the same angle, our system can stillseparate them, and improve the SINR after separation.

6. RELATED WORKCross-technology Interference: Cross-technology

interference increasingly becomes severe with the prolif-eration of wireless technologies. Literatures have triedto address the problem in different ways. Several meth-ods [11, 12] are proposed to dynamically switch to anunused channel based on spectrum sensing, while someother approaches [4,13] are based on time scheduling ortraffic control. Besides, Ref. [5] adds coding redundancy

-10

-5

0

5

10

15

20

1 2 3 4 5 6 7 8 9

Zigb

eeSI

NR

(U

nit

: d

B)

Different Location

Original Zigbee SINR

Zigbee SINR after Multipath Combine

Zigbee SINR of One Path

(a)

-10

-5

0

5

10

1 2 3 4 5

Zigb

ee

SIN

R (

Un

it:

dB

)

Different Location

Original Zigbee SINR Zigbee SINR after Seapration

(b)

Figure 4: The SINR comparison of Zigbee indifferent locations.

to protect Zigbee packets from Wi-Fi interference. Re-cent research works [2,10] utilize the MIMO technologyto protect Wi-Fi or Zigbee communications in the pres-ence of RF interference. Instead, SpaceHub mitigatesthe RF interference for all the wireless technologies ir-respective of their physical/MAC layer design.

AoA Estimation and Adaptive Beamforming:AoA estimation has been applied in wireless localizationsystems like ArrayTrack [9], PinPoint [3]. SpaceHub ismotivated by these works, but we target at smart relaysystem to mitigate wireless interference. SpaceHub isalso inspired by previous adaptive beamforming workin smart antenna field [1, 8]. Unlike traditional adap-tive beamforming which enhances receive SNR of oneintended signal, SpaceHub exploits its spatial filter de-sign to separate collided signal. Additionally, SpaceHubdevelops a multipath identification mechanism to com-bine multiple reflections of the same source using max-imal ratio combination to enhance the signal strength.

7. CONCLUSION AND FUTURE WORKThis paper presents SpaceHub that leverages a multi-

antenna relay node to mitigate cross-technology inter-ference for all communication devices even if all of themhave only single antenna. The core of SpaceHub is ablind signal separator which can separate collided sig-nals without a prior knowledge of the wireless signalstructures. We have implemented SpaceHub on latestSora MIMO kit and evaluate it performance. One im-mediate future work of SpaceHub is to enable simul-taneous forwarding of multiple heterogeneous signalsthrough beamforming. This will greatly reduce the du-ration of the forwarding phase in SpaceHub. Besides,we will also design a more comprehensive MAC proto-col to allow other devices to leverage SpaceHub relaybetter to improve the overall performance.

8. REFERENCES

[1] M. Chryssomallis. Smart antennas. Antennas andPropagation Magazine, IEEE, 42(3):129–136,2000.

[2] S. Gollakota, F. Adib, D. Katabi, and S. Seshan.Clearing the rf smog: making 802.11 n robust tocross-technology interference. ACM SIGCOMMComputer Communication Review, 41(4):170–181,2011.

[3] K. R. Joshi, S. S. Hong, and S. Katti. Pinpoint:Localizing interfering radios. USENIX Symposiumon Networked Systems Design andImplementation, 2013.

[4] B. H. Jung, J. W. Chong, C. Y. Jung, S. M. Kim,and D. K. Sung. Interference mediation forcoexistence of wlan and zigbee networks.Personal, Indoor and Mobile RadioCommunications, IEEE, 2008.

[5] C.-J. M. Liang, N. B. Priyantha, J. Liu, andA. Terzis. Surviving wi-fi interference in lowpower zigbee networks. ACM Conference onEmbedded Networked Sensor Systems, 2010.

[6] R. O. Schmidt. Multiple emitter location andsignal parameter estimation. IEEE Transactionson Antennas and Propagation, 34(3):276–280,1986.

[7] K. Tan, H. Liu, J. Zhang, Y. Zhang, J. Fang, andG. M. Voelker. Sora: high-performance softwareradio using general-purpose multi-core processors.Communications of the ACM, 54(1):99–107, 2011.

[8] B. D. Van Veen and K. M. Buckley.Beamforming: A versatile approach to spatialfiltering. IEEE ASSP magazine, 5(2):4–24, 1988.

[9] J. Xiong and K. Jamieson. Arraytrack: Afine-grained indoor location system. USENIXSymposium on Networked Systems Design andImplementation, 2013.

[10] Y. Yan, P. Yang, X. Li, Y. Tao, L. Zhang, andL. You. Zimo: Building cross-technology mimo toharmonize zigbee smog with wifi flash withoutintervention. In Proceedings of the 19th annualinternational conference on Mobile computing &networking, pages 465–476. ACM, 2013.

[11] S.-U. Yoon, R. Murawski, E. Ekici, S. Park, andZ. H. Mir. Adaptive channel hopping forinterference robust wireless sensor networks. IEEEInternational Conference on Communications,2010.

[12] J. Yun, B. Lee, J. Li, and K. Han. A channelswitching scheme for avoiding interference ofbetween ieee 802.15. 4 and other networks.Computer and Computational Sciences, IEEE,2008.

[13] G. Zhou, J. Lu, C.-Y. Wan, M. D. Yarvis,J. Stankovic, et al. Bodyqos: Adaptive andradio-agnostic qos for body sensor networks. IEEEConference on Computer Communications, 2008.

[14] P. Bahl, R. Chandra, P. Lee, V. Misra, J. Padhye,D. Rubenstein, and Y. Yu. Opportunistic Use ofClient Repeaters to Improve Performance ofWLANs. ACM CoNEXT, 2008.

[15] S. Katti, H. Rahul, W. Hu, D. Katabi. XORs inthe Air: Practical Wireless Network Coding.IEEE/ACM Transaction on Networking, 2008.