IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 43, NO. 1, FEBRUARY 1994 21

Autonomous Time Synchronization Among Radio Ports in Wireless Personal Communications

Justin (2-1. Chuang, Senior Member, IEEE

Absh.acf-In digital wireless access communications systems, a large number of radio ports are deployed to provide wide- area coverage. Achieving time synchronization among ports is beneficial to these systems, especially for systems providing access to the infrastructure networks such as local exchange networks. This leads to better cochannel interference management and easier control for automatic link transfer. This paper describes a practical “over-the-air” algorithm which is autonomously per- formed by individual ports and hierarchically controlled by the ports having the most reliable timing. This process involves only small overhead for demodulating special timing bits transmitted by other ports and adjusting timing accordingly. Computer sim- ulations based on a time division multiple access (TDMA) system with port spacing of 200&3000 feet and 500 kb/s transmission rate are used as an example to evaluate possible impacts on wireless access.

I. INTRODUCTION

VOLVING SYSTEMS for wireless mobile and personal E communications require a large number of fixed radio ports to provide seamless radio coverage throughout widespread service areas [ 11. Achieving time synchronization among ports is beneficial to these systems, especially for systems providing access to the infrastructure networks such as local exchange networks. For example, radio link transfer between two ports can be performed smoothly with minimum- time overhead, which results in minimum-network overhead. Time synchronization is also crucial for providing pilot or beacon signals in CDMA systems [2] or in TDMA systems using dynamic channel selection [3], [4]. For TDMA systems, time synchronization helps to reduce co-channel interference [5], [6]. Specifically, a strong signal will interfere with only those co-channel users occupying the same time slot in a time-synchronized system; while all users occupying partially overlapped time slots are interfered with in a non synchronized system. Synchronization becomes more crucial when time-division duplexing (TDD) is used to separate uplink and downlink transmissions. Using TDD without port synchronization results in port-to-port interference which is likely to be strong compared to the desired signal transmitted by portables [6 ] . Even for a TDMA system using frequency- division duplexing (FDD) and planned frequency reuse, synchronizing timing among ports could improve the uplink signal to interference ratio by about 3 4 dB [6].

Manuscript received April 16, 1993; revised June 9, 1993. The author was with Bellcore, NVC 3X 339, Red Bank, NJ 07701. He is

now with the Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.

IEEE Log Number 9213564.

One popular approach for timing synchronization is to use a common timing reference that is made available to each port. For example, timing reference can be derived from information provided by 1) satellites [2] or 2) the wireline distribution facilities [7]. The first method requires installation of a Global Positioning System (GPS) receiver in every port, which may become more feasible as the cost of such receivers is rapidly decreasing. However, in locations where the receiver has poor reception from the GPS satellites, some alternatives would be desirable. The second method requires accurate time-delay compensation for various distribution facilities. An alternative over-the-air autonomous synchronization technique was introduced by Akaiwa [ 5 ] , in which each port derives timing based on a weighted sum of timing differences with respect to all other ports in the entire system. All ports perform and iterate this averaging process autonomously to reach a time synchronous state for the system. The convergence time increases as the number of ports increases. Furthermore, without a perfect estimate of time delays over the air, a timing error exists and the timing for the entire system drifts.

This paper examines over-the-air synchronization in detail and proposes an improved method to reduce convergence time and residual timing error. We further introduce a hierarchi- cal scheme to flexibly combine the above synchronization methods.

Section I1 specifies system parameters and simulation mod- els. Section I11 compares performance results for several over-the-air synchronization algorithms. Section IV introduces a hybrid method to overcome limitations of existing methods and discusses some practical operation issues.

11. SIMULATION MODELS

We used some parameters considered in the Bellcore Techni- cal Advisory [8] as an example for 16 kbit/s wireless access in a residential outdoor environment. The same synchronization technique can be applied to other systems and environments.

A . System Model We consider a two-dimensional (2-D) square service area

with 289 or 144 ports placed in equally spaced 17 x 17 or 12 x 12 square-grid locations. These two sizes are used to study algorithm sensitivity to system size. Each port can serve up to 20 portables using 20 TDMA time-slots on a pre assigned carrier frequency. Twenty-five frequencies are reused every square cluster of 5 x 5 ports. The adjacent port spacing is 2000 feet and the transmission rate is 500 kbit/s.

0018-9545/94$04.00 0 1994 IEEE

28 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 43, NO. 1, FEBRUARY 1994

Each port demodulates signals received from other ports and performs a timing adjustment procedure described in Section 111. A TDMA frame is assumed to have 20 time slots (100 bits each) where each time slot contains timing bits to mark relative positions in a frame. The “timing” of a port is defined to be the position of a timing marker within a window containing a frame. We use the FDD case as an example to study the synchronization techniques. For the simulation, the initial timing of a port was randomly selected, in units of a time slot, from o to 20.’

We evaluate the synchronization performance by showing the statistics of port timings as a function of the number of iterations. These include standard deviation of timing for the central 100 ports,* as well as the distribution of timing differ- ence among the first tier co-channel ports. Statistics based on our limited simulation results are shown to indicate the trend and effectiveness of the proposed algorithms. Further work involving the analysis of synchronization procedure as well as the confidence intervals for the simulation results would help obtain exact system parameters such as the additional guard time required to avoid degradation caused by residual synchronization error.

B. Propagation Model Many propogation models have been reported for possi-

ble wireless access communications environment[9]-[ 191. We consider a model that is applicable for ports placed outdoors to serve the users in and around houses in residential areas [9]. The average received power is assumed to decrease with distance d as d-4 and the large-scale shadow-fading distribution is log-normal with a standard deviation of 10 dB (8 dB for port-to-port propagation paths). Rayleigh fading is included to account for small-scale variations. Two branch selection diversity is used to mitigate Rayleigh fading. This model results in a higher co-channel interference than some indoor models.

We used this model to test synchronization algorithms. Since both synchronization and access methods are measurement- based, relative effectiveness of these methods is not likely to vary significantly under other propagation conditions.

111. OVER-THE-AIR SYNCHRONIZATION ALGORITHMS

For a system with M ports, Akaiwa’s method requires a procedure by which a port, say, the ith port, can derive the timing differences with respect to all other M - 1 ports separately (no co-channel interference). This port then adjusts its own timing based on a weighted sum of these timing differences. Denoting the timing of the ith port as ti, the new

‘For the TDD system, this number would be doubled, ranging from 0 to 40, as a result of combining uplink and downlink slots on the same frequently camer.

*We show only the statistics of those ports that are influenced most severely by co-channel interference. Moreover, by considering the same 100 ports, we have a fairer comparison of the algorithm convergence for systems with different sizes (144 ports vs 289 ports). Results based on the statistics of all ports (not shown) reach the same conclusions.

P P

0.1 I I 0 200 400 600 800 1,m

Cumulative number of iterations, K

289 ports. 20 slols/port, 25 frequency-pairs Preassigned 5x5 frequency plan ~4 o=lOdB (port c) portable) 8dB (port u port) Spacing between nearest polts = 2000 feet 1 slot = 200 psec = 100 bits, FDD

Fig. 1 ~ Standard deviation of timings for the central 100 ports as a function of K > the number of iterations, for systems with 289 ports. Four algorithms are: 1) weighting by received powers from all ports, no co-channel interference; 2) weighting by received powers from the strongest ports on individual frequencies, co-channel interference included; 3) same as 2), from at most the 8 ports providing the best SIR; and 4) same as 3) but weighted equally. Twenty-five frequencies are considered. Gain factor ( a ) for timing adjustment is 0.5.

timing can be calculated by the following formula:

where a: is the gain factor in timing adjustment, to is the estimated nominal time delay between two ports, and PJz is the received power of the j th port as measured by the ith port. Be weighting the received powers, a port adjusts its timing mainly based on the neighboring ports.

Starting from an initially random asynchronous state, as described in Section 11-A, timing was updated for all ports, taken one at a time, and iterated in random order until each port completed K update^.^ Fig. 1 compares timing standard deviation as a function of K for the central 100 ports of a system with 289 ports. Case 1) is the result obtained from Akaiwa’s method. Other cases include conditions described below. This measure is useful for relative comparisons. We will later consider statistics of timing differences among co- channel ports for an improved method. The nominal delay to was set to be the time delay introduced by the nearest port spacing (2000 feet), Le., 2 psec, corresponding to 1 bit for the 500 kbit/s rate. Case 1) is Fig. 1 yields a residual timing standard deviation of about 3 bits after more than 200 iterations. It would require more than 6 bits of extra guard time to completely eliminate asynchronous co-channel

To demodulate timing information for individual ports with- out co-channel interference, significant centralized coordina- tion is required. If the synchronization were performed in the presence of co-channel interference, a higher degree of autonomy would be achievable. Several such methods are

By using random order of iteration, we remove the need for coordinating updating sequence among ports under autonomous operation. However, we ignored the probability of multiple ports performing the procedure at the same time, which can be reduced by requiring more iterations in practice. Proper operational procedures must be defined for practical application based on implementation considerations.

CHUANG: AUTONOMOUS TIME SYNCHRONIZATION AMONG RADIO PORTS IN WIRELESS PERSONAL COMMUNICATIONS 29

I21 Burst demodulation

- Adjust time based on t8me difference w r t the best polt on each frequency

(less nominal inter-pan dela Coordinated delay

Fig. 2. Block diagram for autonomous timing synchronization.

described in the following and results are included in Fig. 1 for comparison.

Fig. 2 shows a flowchart of autonomous time synchroniza- tion. Similar to Akaiwa’s method, it requires each radio port to demodulate timing information transmitted by other ports and then autonomously adjust timing based on a weighted sum of timing differences. But isolated port transmissions are not required. On the contrary, a port continuously transmits on its assigned frequency except when receiving transmissions from other ports. One iteration of this process includes receptions on all possible frequencies. A successful demodulation on a specific frequency yields the timing difference with respect to the port that provides the strongest signal on that frequency, while all other ports contribute to the co-channel interference. All ports iterate the timing adjustment process autonomously to synchronize the system timing. Since this process is similar to a self-organizing frequency assignment method introduced earlier [20], two processes can be combined to autonomously synchronize timing and assign frequency.

To simulate demodulation in the presence of interference, we calculated the SIR (signal-to-interference ratio) on a spe- cific frequency, say f n , and computed the corresponding word error ratio based on the following formula:

where the bit error ratio is [21]

and “erfc” is the complementary error function. We assume above: 1) 1 word = 88 bits (the remaining 12 bits in a time slot are not coded), 2) constant fading envelope in a word, 3) coherent 4-QAM demodulation (thus a factor of 0.5 to convert SIR per symbol to SIR per bit), and 4) uncorrelated bit errors (a pessimistic assumption, resulting in conservative estimation of successful demodulation). The demodulation for frequency fn was considered failed if a separately simulated random number (between 0 and 1) was lower then Pw(n). Under this condition, no timing difference information was available for

Similar to case I), this synchronization process was iterated for all ports, one at a time in random order, until K timing updates were completed for each port. We did not simulate

f n .

the effect of more than one port simultaneously performing the update. The effect is negligible if the update time is coordinated by a controller.

Cases 2)-4) in Fig. 1 use different weighting strategies. Case 2) is similar to case 1) (weighted by received powers) except that the received signals include co-channel interference and noise. As a result, the residual error is higher. For case 3), only contributions from up to the 8 ports (that are successfully demodulated) with highest SIR are included. This yields even worse results, perhaps due to incomplete information. Case 4) is similar to case 3) but employs a “hard-limited” weighting factor. Namely, Pji in 1) is replaced by 1 or 0 depending on the SIR measures; only up to the best 8 ports with successful demodulation are included in the weighting process. The result is actually better than that of case l)! This is because the qualified ports (ideally, the 8 nearest neighbors) are equally weighted without bias caused by fadings. This strategy is also easier to implement due to a simple weighting factor of either 1 or 0. The SIR measures can be estimated from a combination of received powers and side information derived in the demodulation process. One example of a side information is described in reference [22].

In Fig. 1, a gain factor CY less than unity (a = 0.5) was used to ensure stability, but the process converges after more than 200 iterations. Longer convergence time is expected for a system with higher number of ports. If we set a to be unity and Pj; to be 1 for the best 8 ports and 0 otherwise in (1), the new timing becomes the average timing for these 8 ports (minus the estimated nominal propagation delay). Averaging timing of multiple neighboring ports makes the synchronization process stable. Instability would occur if every port were to successfully demodulate only one other port. If this low-probability condition occurred, this type of over- the-air algorithm would not be suitable because all ports are practically isolated. For these type of systems, every port must derive its own timing from common timing references based on other methods. Using this algorithm with CY = 1, convergence time can be significantly shortened. The results are shown in Fig. 3 for both the cases of 289 and 144 ports. Both systems reach time-synchronous states within 80 iterations, although the convergence time is longer for higher number of ports. The residual timing error is not sensitive to system size because timing is always adjusted based on local information provided by at most 8 neighboring ports. The standard deviation is less than 1 bit (the time to propagate between two nearest ports).

Even though the system converges to a time-synchronous state, the absolute timings for all ports actually drift if propa- gation delay cannot be accurately estimated and removed. Fig. 4 shows the drift of mean timing for the case of 289 ports. The continuous timing drift with respect to the wireline network timing could complicate network interfaces significantly.

In summary, the simple averaging algorithm introduced above has improved convergence time and residual error. However, two inherent limitations for the over-the-air synchro- nization still exist. 1) The convergence time increases as the number of ports increases. 2) The timing for the entire system drifts due to the difficulty of compensating for propagation

30 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 43, NO. 1, FEBRUARY 1994

1,wO averaging timings of up to 8 ports (i.e., gain factor = 1) h T

off;“ in the system:

(2) 289 ports

203 UIO 600 600 l.m Cumulatlve number of Iteratlons, K

20 slotdport. 25 frequency-pairs Pre-assigned 5x5 frequency plan y=4, o=lOdB (port t) portable) 8dB (port u port) Spadng between nearest pals = 2000 feet 1 slot = 200 pse~ = 100 bas. FDD

Fig. 3. cy = 1.0.

Same as case 4) of Fig. 1 for systems with 289 and 144 ports.

1,m , I averaging timings of up to 8 ports

289 ports in the system

m 4w 600 Mo 1,m Cumulatlve number of Ibratlons, K

20 slatdport, 25 frequency-pairs Preassigned 5x5 frequency plan y=4, -1WB (port t) portable) 8dB (poll t) port) Spacing between neared ports = 2000 feet 1 slot = 200 psec = 100 bits, FDD

Fig. 4. same as those used in Fig. 3.

Drift of average timing as a function of IC. Other parameters are the

delay between two ports. A new method will be introduced in the next section to address these issues.

IV. HIERARCHICAL OVER-THE-AIR SYNCHRONIZATION

The synchronization method considered here uses a few master timing references as well as over-the-air self- synchronization to eliminate the two limitations discussed above.

A. Algorithm and Performance To bound convergence time and to avoid timing drift, a

master port which synchronizes to a common reference, such as that obtained from wireline networks or satellite-based global positioning system (GPS), is introduced on the order of every 100 ports. All master ports are given an initial hierarchical value, H = 0. Every other port is initialized a high H value, e.g., 8 if only up to 8 best ports are considered in timing adjustment. Fig. 5 is a flowchart for this method. In addition to the process introduced in Section I11 for over- the-air synchronization, the corresponding H value is also broadcast by all ports and obtained from demodulation. If the H value of the receiving port H, is greater than or equal to the lowest H value of the received source ports H L the receiving port adjusts timing based on the timing difference

(I) Bursl demodulation (2) Rank QMs and select

me be8t 8 10 adjust timing

For the sdecled pom: (1) Timing panem mtch to gel

(2) Gel HS (3) Get mean timing dflerence r’ lor pons wim lowest H(HL)

timing difference

(2) sot reti H=HL+t il HL c sell H

Fig. 5. and hierarchy.

Block diagram for autonomous time synchronization with masters

with respect to the set of ports with a H of H L . Similar weighting strategies as those in Section I11 can be applied. Here we focus on the simple averaging method. Further, H , is set to HL + 1 if H,. is greater than HL. The master timing propagates rapidly in a hierarchical way, which results in time synchronization of the entire system without drift. This process is similar to the synchronization method used to synchronize the entire wirelink network where a primary standard cesium beam atomic clock is used as the master clock and its timing is distributed hierarchically to switches in a master-slave fashion WI.

Computer simulations were performed for this method. One master port is introduced approximately in the center of every 64 port locations (at the 4 x 4 grid point of every 8 x 8 port grids). Fig. 6 shows standard deviation of timings for the central 100 ports for systems with 144 and 289 ports. Fig. 7 shows the drift of the mean timing for a system with 289 ports. Clearly, the convergence time is not sensitive to the system size and the average timing of the system is stable. In addition to overcoming the two limitations of the over-the-air synchronization, this method also maintains the residual standard deviation on the order of 1 bit, the time required to propagate between two nearest ports. More detailed simulations indicated that system timing converges after every port completes only two iterations of this process. We have also simulated the case where there is only one master timing (provided by the port located at the center of the service area). The same good attributes of this new method were preserved with small increases in convergence time (from 2 iterations to 3 iterations) and residual standard deviation (from 1.2 bit to 1.7 bit). Therefore, trade-offs can be made between implementation cost of master ports and synchronization performance.

To understand the interference probability due to residual timing error, we also gather the statistics for the timing difference of a port with respect to its first-tier co-channel ports. Fig. 8 shows the cumulative distribution functions of this parameter after 0, 1, and 2 or more iterations. After two iterations almost all groups of major co-channel ports are synchronized within 4 bits. This suggests that an additional guard time of 4 bits (2 symbols) should be sufficient to avoid interference from adjacent slots of co-channel ports.

CHUANG: AUTONOMOUS TIME SYNCHRONIZATION AMONG RADIO PORTS IN WIRELESS PERSONAL COMMUNICATIONS

~

31

averaging timings of up to 8 ports master ports installed every 64 ports 144 ports or 289 ports in the system iz 100

1 ~ " " ' " ' " " ' " ' ' ' . . . . I 0 100 400 00 800 1,m

Cumulative number ol itoratlone, K

20 slotdport, 25 frequency-palm Pre-asslgned 5x5 frequency plan .p4. u=lWB (port u portable) 8dB (port tt port) Spadng between nearest ports = 2000 feet 1 slot = 2W pse~ - 100 bib. FDD

Fig. 6. Same as Fig. 3 for the hierarchical synchronization method.

- t I

averaging timings of up to 8 ports master ports installed every 64 ports 289 ports in the system

f -lo: - - -25t ' " " " " " " " ' ' ' I

0 100 400 M)(I Bw 1,wo Cumulative number of iterations, K

20 sbtefport, 25 frequency-pairs Pre-assigned 5x5 frequency plan ~ 4 , u=lOdB (port u portable) 8dB (port c) port) Spacing between nearest ports = 2wO feet 1 sld = 200 pec = 100 bits. FDD

Fig. 7. Same as Fig. 4 for the hierarchical synchronization method.

3

i averaging timings of up to 8 ports master ports installed every 64 ports 289 ports in the system

x (bits)

20 sloh/port. 25 frequency-pairs Pre-assigned 5x5 frequency plan .p4, d W B (port c) portable) 8dB (pori tt port) Spacing between nearest ports = 2000 feet 1 slot E 200 psec = 1 00 bits, FDD

Fig. 8. Distributions of timing difference among the first tier co-channel ports for the hierarchical synchronization method in a system with 289 ports.

We have performed access SIR simulation [4] and confirmed this additional guard time to be sufficient for mitigating the degradation due to asynchronous ports.

B. Operation Issues Even though the port spacing was determined based on a

typical link budget [8] at the worst-case portable distance,

and noise figure at port receivers and higher port antennas than portable should compensate for the higher path loss experienced in the port-to-port paths. In a real system, this port-to-port coverage issue should be verified.

We assumed a reasonable connectivity in our propagation model. In a realistic environment, a port may have difficulty receiving signals from other ports and cannot synchronize with the rest of the system over the air. Under these conditions, operational procedures should be provided for ports to report failures and to obtain timing information directly from a radio port control unit (RPCU). If a master port loses its master timing, for example due to the failure of its GPS receiver, it should report the condition to RPCU and increase its H value to become a "slave."

It should be noted that the maximum number of surrounding ports to be used for timing averaging should be properly chosen based on the system layout. Computer simulations confirmed that averaging of up to only 4 ports can also achieve good synchronization.

In the simulation, we assumed continuous port transmission expect during the reception phase. Continuously performing synchronization is not practical especially for systems employ- ing dynamic channel assignment (DCA) [4], in which ports transmit only during active communications phase. Operation procedure and schedule should therefore be specified to update system timing on a regular basis. For example, the synchro- nization algorithm described above could be performed after midnight by the command from radio port control units. For the DCA based systems, this process could be performed on a common control frequency which is time-shared by all ports.

To further reduce residual timing error, the propagation delay must be accurately computed and removed in the timing adjustment process. One possibility is to use devices such as a GPS receiver to obtain the geographical coordinates of ports. We can then store location information in a data base. This implies a port identification number needs to be broadcast and demodulated for a data-base query. The location information can also be directly broadcast without requiring data-base queries. But this would probably increase the amount of broadcast information. If the direct-path delay between any two ports could be calculated, the residual timing error would be dominated by multipath delay spread, positioning errors and time/frequency drifts introduced by port circuitry. Simulations have confirmed that system timing would be perfectly synchronized to that of the master ports after only two iterations (three iterations needed if there is only one master port among 289 ports) if accurate location information is available.

This new synchronization method provides flexibility under various conditions. For examples, for systems relying mainly on the GPS receivers [2], this method not only reduces the number of GPS receivers required but also helps those ports that cannot receive signals from the GPS satellites. For systems relying mainly on reference timing from the wireline infrastructure [7], this method helps those areas where delays by wireline distribution facilities are difficult to measure.

This method can also be used to synchronize ports in the which is less than the port-to-port distance, better antenna gain overlapping areas of multiple systems. This possibility was

~

32 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY. VOL. 43, NO. 1, FEBRUARY 1994

verified by simulating two neighboring systems with different timings.

V. CONCLUSION

Over-the-air synchronization methods were studied using large-scale computer simulations. By demodulating signals transmitted from other ports and then averaging timings de- rived from selected nearest neighbors, a port can autonomously synchronize timing with other ports with reduced convergence time and residual error. But the sensitivity of convergence time to system size and the timing drift of the entire system limit the applicability of this method.

We further introduced a hybrid method based on over-the- air synchronization and a hierarchical scheme to synchronize timing to a few master ports that derive timings from a common reference, such as that provided by GPS satellites or wireline networks. This method preserves the autonomy and simplicity of over-the-air synchronization while maintaining the stability and accuracy of the common timing reference. With low operation overhead, it is applicable for different wireless access communications systems.

ACKNOWLEDGMENT The author would like to thank N. Sollenberger, A. Ranade,

S. Ariyavisitakul, D. Cox, and H. Amold for their comments and suggestions.

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Justin C.-I. Chuang (S’80-M’83SM’88), for a photograph and biography see p. 7 of this issue of this TRANSACTIONS.