ns-3.29: comparison src/lte/doc/source/lte-design.rst

equal deleted inserted replaced

-:ab8a8cc75aa9
+:85fb8f3dc39d
 and one or a few UEs.
 #. It should be possible within the simulation to configure different cells
 so that they use different carrier frequencies and system bandwidths. The
 bandwidth used by different cells should be allowed to overlap, in order to
 support dynamic spectrum licensing solutions such as those described
-in [Ofcom2.6GHz]_ and [RealWireless]_. The calculation of interference should
+in [Ofcom2600MHz]_ and [RealWireless]_. The calculation of interference should
 handle appropriately this case.
 #. To be more representative of the LTE standard, as well as to be as
 close as possible to real-world implementations, the simulator
 should support the MAC Scheduler API published by the FemtoForum
 [FFAPI]_. This interface is expected to be used by femtocell manufacturers
 (see [Sesia2009]_, Section 9.2.2.1);
 hence in a given subframe each RB is always allocated to the same user in both
 slots.
 The allocation bitmap can be coded in
 different formats; in this implementation, we considered the *Allocation
-Type 0* defined in [TS36.213]_, according to which the RBs are grouped in
+Type 0* defined in [TS36213]_, according to which the RBs are grouped in
 Resource Block Groups (RBG) of different size determined as a function of the
 Transmission Bandwidth Configuration in use.
 For certain bandwidth
 values not all the RBs are usable, since the
 channel quality indicator (CQI), rounding to the lowest value, and is mapped to the corresponding MCS
 scheme.
 Finally, we note that there are some discrepancies between the MCS index
 in [R1-081483]_
-and that indicated by the standard:  [TS36.213]_ Table
+and that indicated by the standard:  [TS36213]_ Table
 7.1.7.1-1 says that the MCS index goes from 0 to 31, and 0 appears to be a valid
 MCS scheme (TB size is not 0) but in [R1-081483]_ the first useful MCS
 index
 is 1. Hence to get the value as intended by the standard we need to subtract 1
 from the index reported in [R1-081483]_.
-The alternative model is based on the physical error model developed for this simulator and explained in the following subsections. This scheme is able to adapt the MCS selection to the actual PHY layer performance according to the specific CQI report. According to their definition, a CQI index is assigned when a single PDSCH TB with the modulation coding scheme and code rate correspondent to that CQI index in table 7.2.3-1 of [TS36.213]_ can be received with an error probability less than 0.1. In case of wideband CQIs, the reference TB includes all the RBGs available in order to have a reference based on the whole available resources; while, for subband CQIs, the reference TB is sized as the RBGs.
+The alternative model is based on the physical error model developed for this simulator and explained in the following subsections. This scheme is able to adapt the MCS selection to the actual PHY layer performance according to the specific CQI report. According to their definition, a CQI index is assigned when a single PDSCH TB with the modulation coding scheme and code rate correspondent to that CQI index in table 7.2.3-1 of [TS36213]_ can be received with an error probability less than 0.1. In case of wideband CQIs, the reference TB includes all the RBGs available in order to have a reference based on the whole available resources; while, for subband CQIs, the reference TB is sized as the RBGs.
 Round Robin (RR) Scheduler
 --------------------------
 instantaneous channel quality is high relative to its own average channel
 condition over time. Let :math:`i,j` denote generic users; let :math:`t` be the
 subframe index, and :math:`k` be the resource block index; let :math:`M_{i,k}(t)` be MCS
 usable by user :math:`i` on resource block :math:`k` according to what reported by the AMC
 model (see `Adaptive Modulation and Coding`_); finally, let :math:`S(M, B)` be the TB
-size in bits as defined in [TS36.213]_ for the case where a number :math:`B` of
+size in bits as defined in [TS36213]_ for the case where a number :math:`B` of
 resource blocks is used. The achievable rate :math:`R_{i}(k,t)` in bit/s for user :math:`i`
 on resource block :math:`k` at subframe :math:`t` is defined as
 .. math::
 LTE Spectrum Model
 ^^^^^^^^^^^^^^^^^^
 The usage of the radio spectrum by eNBs and UEs in LTE is described in
-[TS36.101]_. In the simulator, radio spectrum usage is modeled as follows.
+[TS36101]_. In the simulator, radio spectrum usage is modeled as follows.
 Let :math:`f_c` denote the  LTE Absolute Radio Frequency Channel Number, which
 identifies the carrier frequency on a 100 kHz raster; furthermore, let :math:`B` be
 the Transmission Bandwidth Configuration in number of Resource Blocks. For every
 pair :math:`(f_c,B)` used in the simulation we define a corresponding spectrum
 model using the Spectrum framework described
 will automatically use the spectrum model of the eNB it is attached to. Using
 the MultiModelSpectrumChannel described in [Baldo2009]_, the interference
 among eNBs that use different spectrum models is properly accounted for.
 This allows to simulate dynamic spectrum access policies, such as for
 example the spectrum licensing policies that are
-discussed in [Ofcom2.6GHz]_.
+discussed in [Ofcom2600MHz]_.
 PHY Error Model
 ---------------
 The simulator includes an error model of the data plane (i.e., PDSCH) according to the standard link-to-system mapping (LSM) techniques. The choice is aligned with the standard system simulation methodology of OFDMA  radio transmission technology. Thanks to LSM we are able to maintain a good level of accuracy and at the same time limiting the computational complexity increase. It is based on the mapping of single link layer performance obtained by means of link level simulators to system (in our case network) simulators. In particular link the layer simulator is used for generating the performance of a single link from a PHY layer perspective, usually in terms of code block error rate (BLER), under specific static conditions. LSM allows the usage of these parameters in more complex scenarios, typical of system/network simulators, where we have more links, interference and "colored" channel propagation phenomena (e.g., frequency selective fading).
-To do this the Vienna LTE Simulator [Vienna]_ has been used for what concerns the extraction of link layer performance and the Mutual Information Based Effective SINR (MIESM) as LSM mapping function using part of the work recently published by the Signet Group of University of Padua [PaduaPEM]_.
+To do this the Vienna LTE Simulator [ViennaLteSim]_ has been used for what concerns the extraction of link layer performance and the Mutual Information Based Effective SINR (MIESM) as LSM mapping function using part of the work recently published by the Signet Group of University of Padua [PaduaPEM]_.
 MIESM
 ^^^^^
 .. figure:: figures/miesm_scheme.*
 :align: center
 MIESM computational procedure diagram
-The mutual information (MI) is dependent on the constellation mapping and can be calculated per transport block (TB) basis, by evaluating the MI over the symbols and the subcarrier. However, this would be too complex for a network simulator. Hence, in our implementation a flat channel response within the RB has been considered; therefore the overall MI of a TB is calculated averaging the MI evaluated per each RB used in the TB. In detail, the implemented scheme is depicted in Figure :ref:`fig-miesm-architecture`, where we see that the model starts by evaluating the MI value for each RB, represented in the figure by the SINR samples. Then the equivalent MI is evaluated per TB basis by averaging the MI values. Finally, a further step has to be done since the link level simulator returns the performance of the link in terms of block error rate (BLER) in a addive white guassian noise  (AWGN) channel, where the blocks are the code blocks (CBs) independently encoded/decoded by the turbo encoder. On this matter the standard 3GPP segmentation scheme has been used for estimating the actual CB size (described in section 5.1.2 of [TS36.212]_). This scheme divides the the TB in :math:`N_{K_-}` blocks of size :math:`K_-` and :math:`N_{K+}` blocks of size :math:`K_+`. Therefore the overall TB BLER (TBLER) can be expressed as
+The mutual information (MI) is dependent on the constellation mapping and can be calculated per transport block (TB) basis, by evaluating the MI over the symbols and the subcarrier. However, this would be too complex for a network simulator. Hence, in our implementation a flat channel response within the RB has been considered; therefore the overall MI of a TB is calculated averaging the MI evaluated per each RB used in the TB. In detail, the implemented scheme is depicted in Figure :ref:`fig-miesm-architecture`, where we see that the model starts by evaluating the MI value for each RB, represented in the figure by the SINR samples. Then the equivalent MI is evaluated per TB basis by averaging the MI values. Finally, a further step has to be done since the link level simulator returns the performance of the link in terms of block error rate (BLER) in a addive white guassian noise  (AWGN) channel, where the blocks are the code blocks (CBs) independently encoded/decoded by the turbo encoder. On this matter the standard 3GPP segmentation scheme has been used for estimating the actual CB size (described in section 5.1.2 of [TS36212]_). This scheme divides the the TB in :math:`N_{K_-}` blocks of size :math:`K_-` and :math:`N_{K+}` blocks of size :math:`K_+`. Therefore the overall TB BLER (TBLER) can be expressed as
 .. math::
 TBLER = 1- \prod\limits_{i=1}^{C}(1-CBLER_i)
 With respect to the mathematical channel propagation model, we suggest the one provided by the ``rayleighchan`` function of Matlab, since it provides a well accepted channel modelization both in time and frequency domain. For more information, the reader is referred to  [mathworks]_.
 The simulator provides a matlab script (``/lte/model/JakesTraces/fading-trace-generator.m``) for generating traces based on the format used by the simulator.
 In detail, the channel object created with the rayleighchan function is used for filtering a discrete-time impulse signal in order to obtain the channel impulse response. The filtering is repeated for different TTI, thus yielding subsequent time-correlated channel responses (one per TTI). The channel response is then processed with the ``pwelch`` function for obtaining its power spectral density values, which are then saved in a file with the proper format compatible with the simulator model.
-Since the number of variable it is pretty high, generate traces considering all of them might produce a high number of traces of huge size. On this matter, we considered the following assumptions of the parameters based on the 3GPP fading propagation conditions (see Annex B.2 of [TS36.104]_):
+Since the number of variable it is pretty high, generate traces considering all of them might produce a high number of traces of huge size. On this matter, we considered the following assumptions of the parameters based on the 3GPP fading propagation conditions (see Annex B.2 of [TS36104]_):
 * users' speed: typically only a few discrete values are considered, i.e.:
 * 0 and 3 kmph for pedestrian scenarios
 * 30 and 60 kmph for vehicular scenarios
 * 0, 3, 30 and 60 for urban scenarios
-* channel taps: only a limited number of sets of channel taps are normally considered, for example three models are mentioned in Annex B.2 of [TS36.104]_.
+* channel taps: only a limited number of sets of channel taps are normally considered, for example three models are mentioned in Annex B.2 of [TS36104]_.
 * time granularity: we need one fading value per TTI, i.e., every 1 ms (as this is the granularity in time of the ns-3 LTE PHY model).
 * frequency granularity: we need one fading value per RB (which is the frequency granularity of the spectrum model used by the ns-3 LTE model).
 * length of the trace: the simulator includes the windowing mechanism implemented during the GSoC 2011, which consists of picking up a window of the trace each window length in a random fashion.
 * per-user fading process: users share the same fading trace, but for each user a different starting point in the trace is randomly picked up. This choice was made to avoid the need to provide one fading trace per user.
 According to the parameters we considered, the following formula express in detail the total size :math:`S_{traces}` of the fading traces:
 .. math::
 S_{traces} = S_{sample} \times N_{RB} \times \frac{T_{trace}}{T_{sample}} \times N_{scenarios} \mbox{ [bytes]}
-where :math:`S_{sample}` is the size in bytes of the sample (e.g., 8 in case of double precision, 4 in case of float precision), :math:`N_{RB}` is the number of RB or set of RBs to be considered, :math:`T_{trace}` is the total length of the trace, :math:`T_{sample}` is the time resolution of the trace (1 ms), and :math:`N_{scenarios}` is the number of fading scenarios that are desired (i.e., combinations of different sets of channel taps and user speed values). We provide traces for 3 different scenarios one for each taps configuration defined in Annex B.2 of [TS36.104]_:
+where :math:`S_{sample}` is the size in bytes of the sample (e.g., 8 in case of double precision, 4 in case of float precision), :math:`N_{RB}` is the number of RB or set of RBs to be considered, :math:`T_{trace}` is the total length of the trace, :math:`T_{sample}` is the time resolution of the trace (1 ms), and :math:`N_{scenarios}` is the number of fading scenarios that are desired (i.e., combinations of different sets of channel taps and user speed values). We provide traces for 3 different scenarios one for each taps configuration defined in Annex B.2 of [TS36104]_:
 * Pedestrian: with nodes' speed of 3 kmph.
 * Vehicular: with nodes' speed of 60 kmph.
 * Urban: with nodes' speed of 3 kmph.

changeset 8825	85fb8f3dc39d
parent 8794	a68aeda2d85b
child 8853	88563ea950da
child 9314	c893b53ea178