Precoding and Scheduling Techniques for Increasing Capacity of MIMO Channels

MIMO Precoding Scheduling

Special Articles on Multi-dimensional MIMO Transmission Technology －The Challenge to Create the Future－ Precoding and Scheduling Techniques for Increasing Capacity of MIMO Channels

With IMT-Advanced imposing further demands for increas- DOCOMO Beijing Communications Xiaoming She Laboratories Co., Ltd. ing capacity, advanced MIMO control techniques are Lan Chen becoming extremely important. At DOCOMO Beijing Labs, we are studying precoding and scheduling techniques to achieve higher spatial diversity gain, multiplexing gain, and multi-user diversity gain in MIMO systems.

improvements in spectral efficiency is techniques are generally capable of 1. Introduction to use more antennas together with improving the first two types of gain, IMT-Advanced offers a wide enhanced Multiple Input Multiple while scheduling techniques are bandwidth of up to 100 MHz and Output (MIMO)*2 control techniques. In generally capable of improving the requires higher performance while a Multi-User MIMO (MU-MIMO) latter. In particular, precoding using maintaining compatibility with the environment, this entails somehow closed-loop control is expected to result Long Term Evolution (LTE)*1. With improving the spatial diversity*3 gain, in greater performance improvements regard to spectral efficiency, Table 1 the spatial multiplexing gain*4 and the than open-loop control due to its ability shows the values specified for multi-user diversity gain*5. Precoding to optimize transmissions by exploiting LTE [1]-[3] and the requirements of IMT-Advanced indicated by the Table 1 Minimum requirements of IMT-Advanced (extract) LTE IMT-Advanced minimum requirements International Telecommunication Standard (TR25.913, TR25.912, TR25.814) (Base coverage urban environment) Union - Radiocommunication sector -40 (variable) (ITU-R) [4]. Compared with LTE Bandwidth (MHz) 1.4-20 (variable) (Expansion up to approx. 100 recommended) (downlink 2× 2, uplink 1× 2), IMT- Peak spectral efficiency Downlink 15 (4×4) 15 (4×4) Advanced requires that the average (bit/s/Hz) Uplink 3.75 (1×4) 6.75 (2×4)

throughput and cell edge throughput are Cell spectral efficiency Downlink 1.69 (2×2) 2.20 (4×2) increased by approximately 1.5 to 2 (bit/s/Hz/cell) Uplink 0.74 (1×2) 1.40 (2×4) Cell edge user spectral Downlink 0.05 (2×2) 0.06 (4×2) times. efficiency Uplink 0.024 (1×2) 0.030 (2×4) The key to making further (bit/s/Hz)

*1 LTE: An evolutional standard of the Third- and receiver to perform spatial multiplexing Generation mobile communication system and improve communication quality and spec- specified at 3GPP; LTE is synonymous with tral efficiency. Super 3G proposed by NTT DOCOMO. *2 MIMO: A signal transmission technology that uses multiple antennas at both the transmitter

38 NTT DOCOMO Technical Journal Vol. 10 No. 4 the channel state information at the aims and technical issues of precoding of degrees of freedom: Single-User transmitter side [5]. and scheduling, and the techniques pro- MIMO (SU-MIMO), MU-MIMO and Figure 1 shows an overview of posed by DOCOMO Beijing Labs. multi-cell Cooperative MIMO (Co- precoding and scheduling techniques, These techniques are classified as fol- MIMO). and Table 2 shows an overview of the lows in increasing order of the number SU-MIMO is aimed at making improvements to the cell peak spectral efficiency and cell edge user (a) SU-MIMO performance, and is adopted in LTE R8 Base station User 2 downlink. The technical issue of SU- MIMO User 2 User 1 detection data MIMO is precoding to further increase data S2 S'2

S2 User 2 Channel estimation the multi-user diversity gain and peak data Feedback control S2 S'2

S'2 (UP) ・ ・ spectral efficiency. ・ Scheduler SU precoder ・ User k MU-MIMO offers a greater degree data (mode / user selection) Codebook Feedback of freedom than SU-MIMO in the (DFT/ Householder/CDD) spatial dimension because multiple users are multiplexed in the spatial (b)MU-MIMO channel [6]. MU-MIMO is aimed at Base station User 2 MIMO User 2 making improvements to the cell User 1 detection data data S2 average spectral efficiency, and is also S2 User 2 Channel estimation data Feedback control adopted in LTE R8, and it is expected S2 Sk ・ ・ ・ Scheduler (UP / ZFBF)

・ MU precoder that further enhancements will be User k data (mode / user selection) User k studied for R9. The technical issues in Sk Codebook (DFT/ Householder/Grassmanian) MIMO User k detection data MU-MIMO are improving the cell Sk

Channel estimation average spectral efficiency in a limited Feedback Feedback control feedback environment, developing an DFT : Discrete Fourier Transform effective precoding technique that Figure 1 Precoding and scheduling supports Space Division Multiple

Table 2 Issues of precoding and scheduling techniques, and overview of proposal MIMO mode Implementation period Target of Technical issues Summary of proposals by DOCOMO Beijing Labs classification (forecast) improvements (precoding, scheduling) LTE R8 Peak, ･ Precoding for improved ･ CDD-based precoding SU-MIMO Cell average, multi-user diversity gain ･ MB precoding Cell edge ･ Precoding for improved peak rate LTE R9 Cell average ･ Precoding / scheduling for improved ･ Dynamic CQI update / feedback method for cell average spectral efficiency in improved scheduling precision MU-MIMO limited feedback environments ･ Two-stage feedback for improved precoding ･ Precoding to support SDMA precision

IMT-Advanced Cell edge, ･ Reduction of feedback overhead ･ Multi-cell cooperative precoding and Co-MIMO Cell average ･ Precoding and scheduling aimed at scheduling using selective feedback and reducing computational complexity partial channel state information

*3 Spatial diversity: A technique for improving tiple independently faded replicas of the data through space in parallel. communication quality by transmitting or symbol can be obtained and more reliable *5 Multi-user diversity gain: The improvement receiving with multiple antennas. Each pair of reception is achieved. in system throughput derived from using a transmit and receive antennas provides a signal *4 Spatial multiplexing gain: The perfor- packet scheduler to exploit disparities in fading path, and by sending signals that carry the mance improvement derived from using multiple and interference characteristics between users. same information through different paths, mul- antennas to transmit multiple signal flows

NTT DOCOMO Technical Journal Vol. 10 No. 4 39 Precoding and Scheduling Techniques for Increasing Capacity of MIMO Channels

Access (SDMA)*6, and implementing of SU-MIMO, MU-MIMO and Co- books are switched at the transmitter scheduling with lower computational MIMO, we describe the scheme and receiver sides. complexity. proposed by DOCOMO Beijing Labs Figure 2 compares the average In systems based on Orthogonal with a focus on closed-loop precoding spectral efficiency of the conventional Frequency Division Multiple Access and scheduling techniques in low Single codeBook (SB) scheme with that (OFDMA)*7, inter-cell interference has mobility environments. of the proposed MB scheme. We evalu- a large effect on the system capacity, ated a 2×1 MIMO system with vari- particularly when the frequency reuse 2. The Issues of SU-MIMO ous number of users in a Typical Urban factor is equal to 1. As cell sizes and Their Solution (TU) environment. The detailed simula- decrease in the future, inter-cell In a Rice channel*8 or a slow fading tion parameters can be found in Ref. interference will become more of a environment, insufficient channel fluc- [12]. Since user fairness is considered problem. In conventional inter-cell tuations can make it impossible to in Proportional Fair (PF) scheduling, resource coordination [7][8], it is achieve adequate multi-user diversity the conventional scheme has perfor- possible to improve the performance for gain. At DOCOMO Beijing Labs, we mance loss in channels with insufficient cell edge users, but an improvement in have proposed a precoding scheme fluctuations, whereas the spectral effi- the cell average capacity cannot be based on Cyclic Delay Diversity ciency of the proposed scheme is expected. On the other hand, Co- (CDD)*9 which combines open-loop improved by about 7%. In particular, MIMO [9][10] allows a signal from CDD with a closed-loop precoding the channel fluctuation range is small in another cell to be used as the desired technique. In this scheme, multi-user a Line Of Sight (LOS)*10 environment, signal, and has thus become a prime diversity gain can be further exploited so the effectiveness of the proposed candidate for improving not only the by increasing channel fluctuations in scheme is significantly better than that throughput at cell edge but also the the frequency domain. Details of this in a Non-Line Of Sight (NLOS)*11 envi- average cell throughput. But so far, scheme and the results of evaluation ronment. almost all of the studies of this have been published in Ref. [11]. Fur- technique have been performed on paper thermore, in order to increase the chan- and under ideal assumptions, and it has nel fluctuations in both the frequency 2.6 not yet been shown to be practical enough and time domains, we have proposed a Max C/I+SB 2.5 Max C/I+MB + for real environments. Co-MIMO is Multi-codeBook (MB) precoding 2.4 PF SB PF+MB aimed at making improvements to the scheme [12]. In the proposed scheme, a 2.3

performance of cell edge users and the different codebook is used in each 2.2 cell average spectral efficiency, and is Resource Block (RB) and each time 2.1 LOS being studied as a technology for IMT- interval. The MB is generated by multi- 2.0 1.9 NLOS Advanced. The technical issues in Co- plying the left side of a conventional Spectral efficiency (bit/s/Hz) (l) 1.8 MIMO are reduction of feedback codebook W by a unitary matrix Q , 0 5 10 15 20 25 30 35 No. of users overhead and computational where l is a number from 1 to the num- Max C/I : Maximum Carrier to Interference ratio complexity associated with precoding ber of codebooks L. After generating and scheduling. MB, the signaling can be reduced by Figure 2 Average spectral efficiency of SB and MB In this article, to resolve the issues presetting the pattern in which the code-

*6 SDMA: A technique for spatially separating *7 OFDMA: A wireless access scheme that uses highly robust to multipath interference (inter- each user's signals to achieve higher spectral Orthogonal Frequency Division Multiplexing ference from delayed waves). efficiency by using mutually different direc- (OFDM). OFDM uses multiple low data rate *8 Rice channel: A channel where a strong tional beams with a narrow beam width to multi-carrier signals for the parallel transmission wave with little fluctuation (e.g., a direct wave) transmit to and receive from multiple users in of wideband data with a high data rate, thereby is accompanied by many reflected waves with the same cell. implementing high-quality transmission that is large fluctuations.

40 NTT DOCOMO Technical Journal Vol. 10 No. 4 compensated differ depending on the feedback and fixed backoff, the pro- 3. The Issues of MU- channel status. In the proposed scheme, posed scheme, and also the case where MIMO and Their by concentrating on the fact that the CQI of rank 1 and 2 are both fed back Solution rank values fluctuate gradually on the for confirming the upper limit of perfor- Unitary Precoding (UP) [13] and time axis, the user feeds back CQI mance. Compared with the convention- Zero-Forcing BeamForming (ZFBF) value corresponding to the rank value al schemes, the proposed scheme [14] are being studied as useful precod- used in the previous scheduling interval achieved an increase of 20-40%, and it ing schemes for limited feedback envi- [15]. At the base station, the CQI is was confirmed that a capacity close to ronments. In UP, the performance updated by using a lookup table pre- the upper limit value could be achieved degrades when there is insufficient pared in advance based on the previous (Figure 3). feedback information, and in ZFBF, the rank value and the received CQI. feedback precision affects the capacity. ¥ Step 1 3.2 Two-stage Feedback We investigated two schemes that have In an offline simulation, deter- In ZFBF, each individual mobile been proposed to resolve these issues: mine the CQI distribution of rank 2 terminal feeds back a Channel Vector dynamic Channel Quality Indicator corresponding to each CQI value of Quantization (CVQ) value, and at the (CQI) feedback/updating, and two- rank 1. Based on this distribution, base station, scheduling is performed stage feedback. generate a lookup table and store it by calculating a precoding matrix based in the base station. on the CVQ values. In the conventional 3.1 Dynamic CQI Feedback/Updating ¥ Step 2 scheme, loss of capacity occurs because In UP, each individual mobile ter- The base station determines the the limited amount of feedback leads to minal reports back to the base station to rank values at fixed time intervals inadequate precoding precision. In the provide the preferred Precoding Matrix and reports them to the users. proposed scheme, by focusing on the Index (PMI), Precoding Vector Index ¥ Step 3 fact that the CVQ values need to be (PVI) and CQI. At the base station, Each individual mobile terminal more precise for precoding than for groups of users are scheduled from feeds back the CQI value corre- scheduling, we proposed a two-stage users that selected different vectors sponding to the reported rank. from the same matrix and have the ¥ Step 4 3.6 Conventional (rank 1 CQI feedback, fixed backoff update) maximum total capacity or the total The base station uses the lookup 3.4 Proposed (dynamic CQI feedback, updates) Upper limit (rank 1, 2 CQI feedback) weighted capacity. In Evolved UTRA table to determine the CQI of the 3.2 *12 3.0 (E-UTRA) , only the rank 1 CQI is other ranks from the CQI of the 2.8 fed back so as to reduce the amount of reported rank. It determines the 2.6 4TX antennas feedback. However, to perform rank rank and performs scheduling so as 2.4 *13 2.2 adaptation , the CQIs corresponding to to maximize the total capacity or 2.0 2TX antennas Spectral efficiency (bit/s/Hz) other rank values are required at the weighted values. 1.8 4 6 8 101214161820 base station. Hitherto, the rank 2 CQI No. of users value has been calculated by using a The simulation parameters can be Figure 3 Dynamic feedback and fixed offset, but precise scheduling is found in Ref. [15]. We evaluated the updating method not possible because the values to be conventional scheme with rank 1 CQI

*9 CDD: A diversity technique that is also used in receiver, allowing them to communicate via refracted, etc. OFDM-based systems. Transforms spatial direct waves. *12 E-UTRA: An air interface used for advanced diversity into frequency diversity while avoid- *11 NLOS: Describes an environment where there wireless access schemes in 3GPP mobile com- ing inter-symbol interference. are obstacles between the transmitted and munication networks. *10 LOS: Describes an environment where there receiver. In this case, communication can only are no obstacles between the transmitter and take place over waves that have been reflected,

NTT DOCOMO Technical Journal Vol. 10 No. 4 41 Precoding and Scheduling Techniques for Increasing Capacity of MIMO Channels

feedback method that makes effective average SNR is 10 dB. At speeds of up resources from multiple transmitters is use of limited feedback resources. to 25 km/h, the proposed scheme shows thought to be effective. This technique ¥ Stage 1 significant improvement, which indi- calls for high-speed sharing of channel The base station and mobile ter- cates that it is effective in low-speed information between transmitters, so it minals have two (large and small) mobility environments. is more feasible under optical fiber con- codebooks B1 and B2. The users nection based deployment (Figure 6). use B1 for the feedback of CVQ 4. The Issues of Co-MIMO Here, we describe a selective feedback values. The base station performs and Their Solution and cooperative precoding and schedul- scheduling and reports the results to To improve the cell edge user ing technique proposed by DOCOMO the mobile terminals. throughput and average spectral effi- Beijing Labs for use in real multi-cell ¥ Stage 2 ciency, the cooperative precoding and and multi-user environments. Only scheduled mobile termi- scheduling on the same wireless A cooperative area refers to an area nals perform feedback using B2.

14 9 Figure 4 compares the capacity B=3 bits B=3 bits B1=2 bits/B2=8 bits 12 8 B1=2 bits/B2=8 bits with that of a conventional scheme. To B=4 bits B=4 bits B1=3 bits/B2=8 bits B =3 bits/B =8 bits 10 7 1 2 ensure fairness, the overall amount of 6 feedback is kept the same. In other 8 5 words, in the conventional scheme, a 3- 6 4 bit codebook B is used, and in the pro- 4

Spectral efficiency (bit/s/Hz) 3 posed scheme, 2-bit and 8-bit code- Spectral efficiency (bit/s/Hz) 2 0 2 4 6 8 10 12 14 16 18 20 2 books (B1, B2) are used for stages 1 0 7.2 14.4 21.6 28.8 36.0 Average SNR (dB) Speed (km/h) and 2 respectively (3 ×16 = 2 ×16 + Figure 4 Variation of capacity with Figure 5 Variation of capacity with 8 × 2). Similarly, for a conventional average SNR mobilty speed scheme using a 4-bit codebook B, we used 3-bit and 8-bit codebooks in the proposed scheme. Compared with the

conventional scheme, the proposed Base station Base station scheme improves the spectral efficiency by approximately 22% without incur- ring any increased overhead. Further- A

more, there is also a big improvement B when the Signal to Noise Ratio (SNR) is large because at that time the preci- sion of the CVQ has a larger effect on RRE performance improvement. Figure 5

shows how the spectral efficiency Figure 6 Cooperative area selection method varies with speed of mobility when the

*13 Rank adaptation: A technique for adaptive- ations in fading between antennas). ly switching the rank of signals transmitted in parallel in the same time slot and at the same frequency by switching the MIMO transmis- sion method according to the channel state (the correlation between received SINR and fluctu-

42 NTT DOCOMO Technical Journal Vol. 10 No. 4 where cooperative precoding and We evaluated the performance for 2.0 scheduling are performed by multiple the case where a threshold value of 10 No. of RRE transmitting antennas=2 1.9 No. of user receive antennas=2 Remote Radio Equipments (RREs). dB was used to identify the cooperative 1.8 Considering the performance, signaling area. The detailed simulation parame- 1.7 overhead and computational complexi- ters can be found in Ref. [16]. Figure 7 1.6 ty, the cooperative area is decided and 8 show the cell average and cell 1.5 *14 under two considerations: (i) The coop- edge user spectral efficiencies for 24 1.4 Conventional (cell independent MIMO)

Spectral efficiency (bit/s/Hz) 1.3 erative area consists of multiple users. Compared with the conventional Co-MIMO 1.2 cells/sectors, and there are no overlap- scheme where precoding and schedul- 4 8 12 16 20 24 ping between cooperative areas, and (ii) ing are performed independently in No. of users the users in a cooperative area are made each cell, we have confirmed that Co- Figure 7 Cell average spectral efficiency characteristics capable of receiving reference signals MIMO is able to simultaneously from as many related transmitters as improve the cell average and cell edge possible. With this in mind, we consid- user spectral efficiencies. er the scenario shown in Fig. 6 where 1.0 0.9 cooperative area B is suitable for Co- 5. Conclusion 0.8 MIMO. In this article, the technical issues of 0.7 0.6 The principle of the proposed precoding and scheduling which 0.5 CDF scheme is as follows. A mobile terminal increase the gain of multidimensional 0.4 measures the received Signal to Inter- MIMO are clarified, and the schemes 0.3 0.2 Single BS transmission ference plus Noise Ratio (SINR) over a proposed by DOCOMO Beijing Labs 0.1 Co-MIMO long interval from multiple RREs. The are described. At DOCOMO Beijing 00.1 0.2 0.3 0.4 0.5 0.6 RRE with the best received SINR is Labs, we have drafted and submitted Cell edge user spectral efficiency (bit/s/Hz) designated as the primary station, and a contributions to 3GPP LTE cooperating Figure 8 Cell edge user spectral efficiency RRE for which the difference between with the NTT DOCOMO Radio Access the received SINR and that of the pri- Network Development Department. In mary station is within a given range is the future, towards the realization of UTRAN (E-UTRAN).” selected as the secondary station. The mobile communication systems for [2] 3GPP TR 25.912 V7.2.0: “Feasibility study mobile terminal reports to the primary IMT-Advanced and beyond, we plan to for evolved Universal Terrestrial Radio Access (UTRA) and Universal Terrestrial station with the channel information on continue with studies aimed at further Radio Access Network (E-UTRAN).” the secondary station. After each indi- improving spectral efficiency, guaran- [3] 3GPP TR 25.814 V7.1.0: “Physical layer *15 vidual RRE has received feedback from teeing Quality of Service (QoS) , aspects for evolved Universal Terrestrial each mobile terminal, it reports back to reducing delay and enhancing battery- Radio Access (UTRA).” [4] ITU-R, WP5D: “Draft Report on Require- the base station. At the base station, a saving*16 technology. ments Related to Technical System combined channel matrix H is con- Performance for IMT-Advanced Radio structed, and cooperative precoding and References Interfaces(s) [IMT.TECH],” Jun. 2008. scheduling are performed between the [1] 3GPP TR 25.913 V7.3.0: “Requirements [5] E. Telatar: “Capacity of Multi-antenna for Evolved UTRA (E-UTRA) and Evolved Gaussian Channels,” Euro. Trans. Com- RREs in this area.

*14 Cell edge user spectral efficiency: other quality factors are the main parameters. Defined as the 5% value of the Cumulative *16 Battery-saving: Refers to technology that Density Function (CDF) of the user spectral strives to reduce power consumption by such efficiency. means as discontinuous reception and power- *15 QoS: A level of quality on the network that is saving control techniques. set for each service. Delay, packet loss and

NTT DOCOMO Technical Journal Vol. 10 No. 4 43 Precoding and Scheduling Techniques for Increasing Capacity of MIMO Channels

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