Interference-Aware Joint Scheduling

The uplink of a cellular network as shown in Fig. 5.8 is considered, where dif- ferent BSsites are interconnected with aCSUvia high-capacity backhaul links, assumed to facilitate a fast information exchange. It should be noted that the depictedCSUin Fig.5.8is not necessarily a separate device, but it may also be incorporated in one of the involvedBSs. As illustrated in Fig.5.8,all cooperating BSs periodically send multi-cell CSIof the associatedUEs to the corresponding CSU,which thus becomes aware of the interference a certainUEscheduled in one cell would cause to another cell within the same cooperation cluster. This way, strong interference situations—which may occur, for example, if cell-edge UEs of neighboring cells are allocated to the same radio resources—can be avoided by taking the predicted inter-cell interference caused by the variousUEs located within the cooperation cluster into account. The avoidance of high interference levels may not only significantly increase the overall system performance in terms of the average cell throughput, but it also contributes to a better fairness since UEs located close to the cell-edge generally benefit most from it.

A flow chart of the considered joint scheduling algorithm is depicted in Fig.5.9. In a first step, eachCSUreserves certain radio resources for the requested retrans-

5.2 Uplink Joint Scheduling and Cooperative Interference Prediction 57

HARQ management Ordering of the cooperating BSs

Resource allocation performed for

all cooperating BSs? yes

no

Determine joint scheduling priorities for

current BS

Perform resource allocation Link adaptation based

on exchanged multi-cell CSI Interference-aware joint

scheduling completed

Figure 5.9 Flow chart of the interference-aware joint scheduling algorithm[FMDS10]. c

2010IEEE.

missions of all associatedBSs, and then the actual joint scheduling process is car- ried out. Since the simultaneous allocation of radio resources to allUEs located within the respective cooperation cluster would cause a tremendous increase in computational complexity, we assume in the following that the joint scheduling procedure is carried out stepwise for each set ofUEs assigned to one of the coop- erating BSs. This way, the computational effort can be significantly reduced. However, this entails also that theBSsassociated to a certain CSU have to be ordered by means of a certain fairness criterion in order to sustain fairness among the variousUEs. For that purpose, the long-term cell throughput averaged over the number of assigned UEs is considered as fairness criterion, which can be expressed for the m-thBSby

T_avg,m(t + 1) = τ T_avg,m(t) + (1− τ) Tinst,m(t)

|Km|

, (5.14)

where T_avg,m(t) denotes the long-term throughput for the m-thBSat the time interval t, T_inst,m(t) the instantaneous throughput, τ the forgetting factor and

Km the set of UEs assigned to BS m. The actual BS ordering is then done

in such a way that the corresponding average long-term throughputs according to (5.14) are non-decreasing, i.e., the resource allocation always starts with the BSassociated with the lowest long-term throughput, then it is done for the one with the second smallest one, etc.

Having determined the ordering of the cooperatingBSs, the radio resources are allocated to the variousUEs based on the exchanged multi-cellCSI. T o this end, not only the current channel conditions between the UEs and their serving BSs are taken into account, but also the expected inter-cell interference caused

58 CoMPSchemes Based on Interf.-Aware Transceivers or Interf. Coord.

by assigning these UEs to certain radio resources. Thus, the joint scheduling priority for the b-th radio resource and k-th UEassociated to its servingBSm

can be expressed by

S_k,b(t) = G_k,b,Kb(t) + 

j∈ Kb G_{j,b, ˜K}

b(t) , k∈ Km, (5.15)

where G_k,b,Kb(t) denotes the scheduling priority for the k-th UE allocated to the b-th radio resource on which the UEs in setK_b are already scheduled. Fur- thermore, G_{j,b, ˜K}

b(t) indicates the updated scheduling priority for the already

scheduled UE j, taking into account that the k-thUE will be allocated to the

b-th radio resource. In this regard, the updated set of interferingUEs allocated

to the b-th radio resource for the j-thUEis given by ˜

Kb = (Kb\ j) ∪ k. (5.16)

In the following, only the calculation of the scheduling priority G_{j,b, ˜K}

b(t) is

explicitly outlined, but the scheduling priority G_k,b,Kb(t) can be determined in a similar way and therefore is not further considered in more detail here. It is assumed that the radio resources are shared between the various UEs by means of the well-known proportional fair approach, but it should be noted that any other scheduling metric may be used in conjunction with our joint scheduling scheme as well. The basic idea of proportional fair scheduling is to realize a reasonable trade-off between the maximal total throughput and cell-edge throughput. Clearly, on the one hand, fair resource allocation among the UEs will lower the overall throughput compared to the maximum possible one, but in return it provides a higher throughput for UEs with relatively poor channel conditions, thus improving the system fairness. In general, the proportional fair metric is given by the ratio between instantaneously supportable and long-term throughput of a certainUE [VTL02], i.e., G_{j,b, ˜K}

b(t) can be determined by G_{j,b, ˜K} b(t) = R_{j,b, ˜K} b(t) Tα j (t) , (5.17) with R_{j,b, ˜K}

b(t) as the instantaneous supportable throughput and α as the fair-

ness factor, which determines the trade-off between efficiency in terms of total throughput and fairness. Furthermore, T_j(t) denotes the long-term average throughput given by T_j(t + 1) = - β T_j(t) j /∈ Ktotal(t) β T_j(t) + (1− β) ¯R_j(t) j ∈ Ktotal(t) , (5.18)

where β denotes the forgetting factor and Ktotal(t) as well as ¯Rj(t) denote the

set of all scheduled UEs at time interval t and the aggregated throughput of the scheduled UE j, respectively. The instantaneous supportable throughput R_{j,b, ˜K}

b(t) may be estimated by means of the Shannon capacity formula R_{j,b, ˜K} b(t) = log2  1 + γ_{j,b, ˜K} b  , (5.19)

5.2 Uplink Joint Scheduling and Cooperative Interference Prediction 59

with γ_{j,b, ˜K}

b as the uplink signal-to-interference-and-noise ratio (SINR) of the

UE j on the b-th radio resource. Let us assume in the sequel that all BSs are

equipped with Nbs antenna elements whereas allUEs have only a single antenna element (i.e., Nue= 1). Then, the uplinkSINRγ_{j,b, ˜K}

b can be expressed by γ_{j,b, ˜K} b = P_j,bwH_j,bh_j,bhH_j,bw_j,b wH j,b  E i_{j,b, ˜K} bi H j,b, ˜Kb ! + σ2_Iw j,b , (5.20)

with P_j,bas the transmit power ofUEj for the b-th radio resource, h_j,b∈ C[Nbs×1]

as the channel vector from the j-thUEto its servingBS,w_j,b∈ C[Nbs×1] _{as the}

corresponding weight vector for coherent detection, i_{j,b, ˜K}

b∈ C

[Nbs×1] _{as inter-}

cell interference caused by the set of UEs ˜K_b and σ2 _{as thermal noise variance.} Based on the exchanged multi-cellCSI, theCSUis able to predict the interference covariance matrix Φii= E{i_{j,b, ˜K} bi H j,b, ˜Kb} ∈ C [Nbs×Nbs] _{in (5.20), which is given by} Φii=  q∈ ˜Kb P_q,bh_q,j,bhH_q,j,b, (5.21) where P_q,b and h_q,j,b∈ C[Nbs×1] _{denote the transmit power ofUEq for the b-th}

radio resource and the channel vector from the q-th UE to the serving BS of

UE j on the considered radio resource b, respectively. Clearly, Φiiin(5.21) con-

tains both the inter-cell interference level caused by the already scheduledUEs associated to the cooperating BSs as well as the one that will be generated by assigning the k-th UE to the considered radio resource. As a result, the joint scheduling priorities in (5.15) reflect the weighted sum-throughput taking the current inter-cell interference situation into account. This consequently leads to an interference-aware joint scheduling, aiming at reducing the inter-cell interfer- ence within the given cooperation cluster while still taking channel-dependent scheduling as well as user fairness into account.

Having determined the joint scheduling priorities in (5.15) for all UEs asso- ciated to a certain BS, the central scheduler generally aims at maximizing the priority for each radio resource. The complexity of the resource allocation pro- cess depends on the used access scheme. In case of single carrier frequency domain multiple access (SC-FDMA), for example, which is used in the 3GPP LTEuplink, the allocated radio resources of eachUEhave to be either adjacent or evenly spaced in frequency in order to achieve a low peak-to-average power ratio (PAPR)[MLG06]. However, this leads to a significantly reduced allocation flexibility and a higher complexity. To overcome this problem, a resource alloca- tion algorithm presented in[CRA+08] may be applied after determining the joint scheduling priorities in (5.15). The basic idea of this algorithm is that adjacent radio resources are assigned to a certainUE until either a different UE has a higher scheduling priority or the maximum transmit power is reached. This way, the allocation constraints due to SC-FDMA can be met, while still exploiting the multi-user diversity and the frequency selectivity of the uplink channel.

60 CoMPSchemes Based on Interf.-Aware Transceivers or Interf. Coord. 0 10 20 30 40 50 60 70 80 90 100 110 120 30 60 100 bandwidth occupancy [%] sp ectr a l efficiency g a in [%] +71% +102% +14% +37% +3% +25% interference coord. joint scheduling

(a) Gain in average spectral efficiency.

0 10 20 30 40 50 60 70 80 90 100 110 120 30 60 100 bandwidth occupancy [%] cell- edg e thr o ug hput g a in [%] +32% +105% +26% +67% +21% +58%

(b) Gain in cell-edge throughput.

Figure 5.10 Relative uplink performance gains of the presented joint scheduling scheme as well as of a dynamic interference coordination scheme compared to a 3GPP

LTERelease 8 system with 500 m inter-site-distance and six cooperating cells perBS.

Finally, after completing the resource allocation of all cooperating BSs, the link adaptation selects for eachUEthe spectrally most efficient modulation and coding scheme (MCS)that can be supported by its current uplink channel with- out exceeding a given target block error rate (BLER). To this end, the corre- spondingSINRis estimated by evaluating the available multi-cellCSI,resulting in a more accurate link adaptation. This is because the knowledge of whichUEs are scheduled in the cooperating cells together with the available multi-cellCSI facilitate an accurate prediction of the interference situation that will occur dur- ing the actual (future) data transmission. Especially in the uplink, this may lead to significant additional performance gains since the interference situation there is usually rather volatile. This is because from one transmit time interval (TTI) to the other completely different sets ofUEs may be scheduled in nearby cells.

An example for the achievable uplink performance of the presented joint scheduling scheme for different bandwidth utilizations is depicted in Fig.5.10, where the relative gains compared to anLTERelease 8 system in terms of aver- age spectral efficiency as well as cell-edge throughput are shown. The detailed simulation assumptions, parameter settings as well as further results will be intro- duced later in Section14.3. In order to achieve a certain bandwidth occupancy, the scheduling is performed until the intended degree of bandwidth utilization is reached. In addition to the joint scheduling results, Fig.5.10shows for compari- son also the performance of a state-of-the-art dynamic interference coordination scheme based on high interference indicator signaling [3GP07c,FMDS10]. First of all, it can be seen that the achievable performance is heavily dependent on the bandwidth occupancy. The gains increase with decreasing bandwidth occupancy, which indicates that the flexibility in assigning radio resources to the variousUEs is considerably increased at a low bandwidth occupancy. As a result, severe inter-

5.2 Uplink Joint Scheduling and Cooperative Interference Prediction 61

cell interference situations can be avoided by exploiting the whole bandwidth, i.e. preventing theUEs associated to the cooperatingBSsfrom being allocated to the same radio resources. Furthermore, it is shown in Fig.5.10that the joint schedul- ing scheme outperforms the dynamic interference coordination scheme due to the higher flexibility in jointly allocating radio resources to the variousUEs, which consequently leads to an improved avoidance of severe inter-cell interference. The better system performance, however, comes at the cost of an increased backhaul load due to the required exchange of multi-cell CSI [FMDS10].