Chapter 5: System Level Aspects for Multiple Cell Scenarios

1. Chapter 5: System Level Aspects for Multiple Cell Scenarios School of Info. Sci. & Eng. Shandong Univ.

2. 5.1 Link Adaptation • 5.2 System Concept for a MIMO-OFDM Based Self- Organizing Data Transmission Network • 5.3 Pricing Algorithms for Power Control, Beamformer Design, and Interference Alignment in Interference Limited Organizing Data Transmission Network • 5.4 Interference Reduction: Cooperative Communication with Partial CST in Mobile Radio Cellular Networks

3. Link Adaptation Link adaptation means the dynamic choice of individual link parameters within a given OFDM-framework. As the question of optimum link adaptation is closely related to the environment of the links, many different options exist. In order to restrict our discussion to a limited complexity, we will focus on a certain application scenario which includes many aspects of general interest.

4. Transmission efficiency and quality of service are demanded for discussing different aspects of link adaptation . The transmission of live media streams in home environments may serve as such an example. Assuming a typical household in many industrial countries one might assume that a critical network situation is the simultaneous use of different video services by several members of the household. Figure 5.1 shows a typical scenario.

6. Figure 5.2 shows the levels of system organization. The final goal of link adaptation will be the best selection of parameters for all links such that overall efficiency will be maximized.

7. Efficient link adaptation requires knowledge about the channel, e.g., transfer function or packet transmission statistics. In order to simulate and discuss the options, a channel model is required to deliver the required information. Figure 5.3 gives examples of typical transfer functions. These have been measured using a channel sounder which provided a radio signal of 100 MHz bandwidth. Measurements have been taken for the ISM bands at 2.4 GHz and 5.75 GHz. One WLAN channel covers a portion of 20 MHz of these bands.

9. Adaptation of Physical Link Parameters If channel bandwidth, duration of guard interval, number of carriers, and carrier spacing are fixed according to the standard, link adaptation in the physical layer means individual,dynamic selection of the following parameters: • transmission channel (within the number of available channels) • total transmit power • modulation and coding scheme (and thus the physical data rate) • transmit power/modulation per carrier

10. Some of these options can be used within the boundaries of existing standards, others require extensions. 1. Dynamic Frequency Selection

11. 2.Transmit Power Control (TPC) 3. Modulation and FEC 4. Transmit Power/Modulation per Carrier

14. Link Efficiency as Optimization Criterion we start with the definition of the packet transmission efficiency To obtain the efficiency of a single link, ηP,i is averaged over the NT transmitted packets. This leads to the following definition of link efficiency ηL:

15. Cross-Layer Adaptation Besides the adaptation of the physical transmission parameters as discussed above, optimization also has to cover aspects of the MAC layer. Typical networks transmit packets containing payload data and overhead for medium access, synchronization, and addressing.

16. 5.2 System Concept for a MIMO-OFDM-Based Self-Organizing Data Transmission Network Introduction • Future wireless communication networks will provide numerous different services with user-specific Quality-of-Service (QoS) demands. • In cellular networks, the OFDM transmission technique has the additional advantage that all base stations and mobile terminals can be synchronized in time and carrier frequency. • The OFDM transmission technique is very suitable for broadband radio channels due to its ability of equalization with low computation complexity. • The resource allocation scheme is integrated into the scheduler. Based on the optimization objectives (fairness, capacity, ...), the scheduling procedure is organized in a cross-layer approach by taking the QoS parameters of the data link control (DLC) layer as well as the radio channel knowledge of the physical layer into account

17. Beamforming Concepts Beamforming is an efficient technique which uses appropriate weighting of multiple antenna elements to concentrate the energy in a desired direction. The determination of the weighting is dependent on the channel knowledge.

18. Fixed Beams Fixed beams are uniquely precalculated without considering the current position of the users inside the cell. The weighting coefficients are generated using the Dolph-Chebychev method to achieve a constant sidelobe magnitude. Zeroforcing Beams Zeroforcing beams are calculated user-specifically. Therefore, full channel knowledge is required at the base station. For zeroforcing beams, ideal channel knowledge is assumed to be known at the transmitter. The calculation of the weighting coefficients wk is given

19. System Concept

21. Allocation of New Resources New resources are requested by new mobile terminals coming into the cellular network. Alternatively, all users who need a higher data rate ask for additional resources. The resource allocation procedure for users is based on the interference power measured by the base station and the mobile terminal. The interference power at the base station is measured continuously in frequency and space on resources during the uplink phase.

22. Results

23. Figure 5.11 shows the performance for the different beamforming techniques and the reference scenario.

24. The last point is visualized in Fig. 5.12, where a cellular system and a single subcarrier are considered.

25. Reallocation

26. The optimization task is subject to the following conditions:

27. Data Rate-Based Utility Function The overall data rate is given by the sum of data rates ci,d on single resources d. The resulting utility function is given

28. The optimization task is expressed as follows: Fig. 5.14 shows the characteristics of the utility function for different users and waiting times of the first packets.

34. 5.3 Pricing Algorithms for Power Control, Beamformer Design, and Interference Alignment in Interference Limited Networks System Model We examine a system with K transmitter-receiver pairs (synonymously called users), where each receiver is only interested in the signal from its associated transmitter and all interference is treated as additional noise. Each receiver (transmitter) has M (N) antennas, respectively. The received signal vector of user k is We assume the noise vector nk to be uncorrelated with variance σ2.

37. Distributed Interference Pricing • Power Control in SISO Systems

38. Beam former Design in MISO Systems

39. Power Allocation in OFDM Systems The total transmit power of user k is the sum of powers allocated to its subcarriers, therefore the power constraint is

40. MIMO Interference Networks and Interference Alignment

42. 5.4 Interference Reduction: Cooperative Communication with Partial CSI in MobileRadio Cellular Networks System Model and Reference Scenario

46. Significant CSI Selection Algorithm and Channel Matrix Formalism In order to reduce the computational load of the JD/JT algorithms and the communication load between the BSs, we consider only the significant CSI corresponding to the channels which play a significant role in the system performance. Here we have distinguished the significant useful channels from the significant interference channels for each MS. We obtain the estimated significant useful channel matrix and the estimated significant interference channel matrices as

48. During the calculation, the known 3 channel coefficients and the limited statistical knowledge of the other channel coefficient are considered. For a snapshot of the channel matrix H, we obtain

49. Decentralized JD/JT with Significant CSI for Interference Reduction